eo4sd-urban project: cpl denpasar city report...this project has received funding from the european...
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Earth Observation for Sustainable Development
Urban Development Project
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 685761.
ESA Ref: AO/1-8346/15/I-NB
Doc. No.: City-Operations Report
Issue/Rev.: 1.1
Date: 13.10.2017
EO4SD-Urban Project: CPL Denpasar City Report
Lead: Partners: Financed by:
Earth Observation for Sustainable Doc. No.: City-Operations Report
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EO4SD-Urban Denpasar City Operations Report Page I
Consortium Partners
No. Name Short Name Country
1 GAF AG GAF Germany
2 Système d'Information à Référence Spatiale SAS SIRS France
3 GISAT S.R.O. GISAT Czech Republic
4 Egis SA EGIS France
5 Deutsche Luft- und Raumfahrt e. V DLR Germany
6 Netherlands Geomatics & Earth Observation B.V. NEO The Netherlands
7 JOANNEUM Research Forschungsgesellschaft mbH JR Austria
8 GISBOX SRL GISBOX Romania
Disclaimer:
The contents of this document are the copyright of GAF AG and Partners. It is released by GAF AG on
the condition that it will not be copied in whole, in section or otherwise reproduced (whether by
photographic, reprographic or any other method) and that the contents thereof shall not be divulged to
any other person other than of the addressed (save to the other authorised officers of their organisation
having a need to know such contents, for the purpose of which disclosure is made by GAF AG) without
prior consent of GAF AG.
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Summary
This document contains information related to the European Space Agency (ESA) supported project
“Earth Observation for Sustainable Development” Urban Applications (EO4SD-Urban) provision of
geo-spatial products to the World Bank City Planning Labs (CPL) programme for Denpasar, Indonesia.
Affiliation/Function Name Date
Prepared GAF AG S. Gomez, A. Broszeit 13/10/2017
Contributions Joanneum Research M. Hirschmugl, H. Proske 11/10/2017
Reviewed Quality Assurance Responsible K. Druessler 13/10/2017
Approved GAF AG, Project Coordinator T. Haeusler 13/10/2017
The document is accepted under the assumption that all verification activities were carried out correctly
and any discrepancies are documented properly.
Distribution
Affiliation Name Copies
ESA Z. Bartalis electronic copy
WB TTL G. Singh electronic copy
Document Status Sheet
Issue Date Details
1.0 30/08/2017 First Draft Document Issue
1.1 13/10/2017 Final Document Issue
Document Change Record
# Date Request Location Details
1 13/10/2017 Update of Draft
Version
New sections for
Flood Risk
product
description.
Report updated with Flood Risk product
description.
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Executive Summary
The European Space Agency (ESA) has been working closely together with the International Finance
Institutes (IFIs) and their client countries to demonstrate the benefits of Earth Observation (EO) in the
IFI development programmes. Earth Observation for Sustainable Development (EO4SD) is a new ESA
initiative, which aims to achieve an increase in the uptake of satellite based information in the regional
and global IFI programmes. The overall aim of the EO4SD Urban project is to integrate the application
of satellite data for urban development programmes being implemented by the IFIs or Multi-Lateral
Development Banks (MDBs) with the developing countries. The overall goal will be achieved via
implementation of the following main objectives:
To provide a service portfolio of Baseline and Derived urban-related geo-spatial products
To provide the geo-spatial products and services on a geographical regional basis
To ensure that the products and services are user-driven
This report describes the generation and the provision of EO-based information products to the World
Bank (WB) supported City Planning Labs (CPL) programme and the counterpart City Authorities in
Denpasar (Indonesia). The report provides a Service Description by referring to the user driven service
requirements and the associated product list with the detailed product specifications. The following
products were requested:
Urban Land Use/Land Cover current and historic
Urban Extent and Change
Transport Infrastructure - Road Network
Flood History Assessment
The current Version of this Report contains the description of the generation and delivery of the Land
Use/Land Cover (LU/LC) and the LU/LC Change between two time periods of 2006 and 2016. The
Derived products of Transport, Infrastructure and the Flood History product will be included in an
updated next Version of this Report.
This City Operations Report for Denpasar systematically reviews the main production steps involved
and importantly highlights the Quality Control (QC) mechanisms involved; the steps of QC and the
assessment of quality is provided in related QC forms in the Annexe of this report. There is also the
provision of standard analytical work undertaken with the products which can be further included as
inputs into further urban development assessments, modelling and reports.
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Table of Contents
1 INTRODUCTION GENERAL BACKGROUND OF EO4SD-URBAN .................................. 1 2 SERVICE DESCRIPTION........................................................................................................... 1
2.1 STAKEHOLDERS AND REQUIREMENTS ..................................................................................... 1
2.2 SERVICE AREA SPECIFICATION ............................................................................................... 2
2.3 PRODUCT LIST AND PRODUCT SPECIFICATIONS ...................................................................... 3
2.3.1 Land Use/Land Cover Nomenclature ................................................................................................ 3
2.3.2 Transport Infrastructure – Road Networks ........................................................................................ 7
2.4 TERMS OF ACCESS ................................................................................................................... 7
3 SERVICE OPERATIONS ............................................................................................................ 8
3.1 SOURCE DATA ......................................................................................................................... 8
3.2 PROCESSING METHODS ........................................................................................................... 9
3.3 ACCURACY ASSESSMENT OF MAP PRODUCTS ........................................................................ 9
3.3.1 The Applied Sampling Design .......................................................................................................... 9
3.3.2 The Applied Response Design ........................................................................................................ 10
3.3.3 The Applied Analysis Design .......................................................................................................... 11
3.4 ACCURACY ASSESSMENT OF TRANSPORT NETWORK ........................................................... 12
3.5 QUALITY CONTROL/ASSURANCE .......................................................................................... 14
3.6 METADATA ............................................................................................................................ 15
4 ANALYSIS OF MAPPING RESULTS ..................................................................................... 17
4.1 URBAN EXTENT – DEVELOPMENTS FROM 2000, 2005, 2010 AND 2015 ................................ 17
4.2 LAND COVER/ LAND USE 2006 AND 2016 ............................................................................. 21
4.2.1 Spatial Distribution of Main LU/LC Change Categories ................................................................ 23
4.2.2 Changes of Agricultural Areas ........................................................................................................ 25
4.3 TRANSPORT NETWORK .......................................................................................................... 27
4.4 FLOOD RISK ASSESSMENT ..................................................................................................... 28
4.4.1 EO Data Used .................................................................................................................................. 28
4.4.2 Short Description of Methodological Approach ............................................................................. 28
4.4.3 Product Description and Accuracy Assessment .............................................................................. 30
4.4.4 Results ............................................................................................................................................. 32
5 REFERENCES ............................................................................................................................ 37
Annexes
Annex 1: Land Use and Land Cover Nomenclature and Definitions
Annex 2: Processing Methods for EO4SD-Urban Products
Annex 3: Filled Quality Control Sheets
Urban Land Use / Land Cover
Flood Risk Assessment
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List of Figures
Figure 1: Illustration of Core and Peri-Urban Areas for Mapping.........................................................2 Figure 2: Land Use Map of Denpasar, 2012 (Reference: World Bank, CPL Programme, 2017)..........4 Figure 3: Mapping result of the city of Denpasar of the year 2016 overlaid with randomly
distributed sample points for accuracy assessment ..............................................................11 Figure 4: Example of the applied sampling design to generate randomly distributed point for the
accuracy assessment of the road network .............................................................................13 Figure 5: Secondary sampling grid to generate the sampling points at spatial intersection of roads
and grid cells; roads are represented as white lines, grid as black lines and final sampling
point as black dots ................................................................................................................13 Figure 6: Quality Control process for EO4SD-Urban product generation; at each intermediate
processing step output properties are compared against pre-defined requirements .............15 Figure 7: Urban Extent developments in the epochs 2000 to 2005, 2005 to 2010 and 2010 to 2015
in Denpasar and surrounding region.....................................................................................18 Figure 8: Increase of Urban Extent between 2000 and 2015, in percent per administrative units.......18 Figure 9: Increase of Urban Extent between 2000 and 2005, in percent per administrative units.......19 Figure 10: Increase of Urban Extent between 2005 and 2010, in percent per administrative units.......19 Figure 11: Increase of Urban Extent between 2010 and 2015, in percent per administrative units.......20 Figure 12: Detailed Land Cover/ Land Use 2016 - Spatial distribution ................................................21 Figure 13: Detailed Land Cover/ Land Use 2006 structure: presented as Overall, Core City and in
Larger Urban Zone in % (left) and km2 (right) ....................................................................22 Figure 14: Detailed Land Cover/ Land Use 2016 structure: presented as Overall, Core City and in
Larger Urban Zone in % (left) and km2 (right) ....................................................................22 Figure 15: Spatial Distribution of Land Cover and Land Use Change Types from 2006 to 2016 ........24 Figure 16: Land Cover Land Use Change Types 2006-2016: presented as Overall, Core City and
in Larger Urban Zone in % (left) and km2 (right) ................................................................25 Figure 17: Spatial distribution of changes from Agricultural Areas to other classes between 2006
and 2016 ...............................................................................................................................26 Figure 18: Changes of Agricultural Areas into other LU classes between 2006 and 2016; presented
as Overall, Core City and in Larger Urban Zone in % (left) and km2 (right) .......................27 Figure 19: Transport Network of Denpasar in 2006 and 2016 ..............................................................27 Figure 20: Subset of Flood Hazard Map of Denpasar (Downtown area) (Image: Quickbird
2017/01/03) ..........................................................................................................................31 Figure 21: Subset of Flood Risk Map of Denpasar (Downtown area) (Image: Quickbird
2017/01/03) ..........................................................................................................................32 Figure 22: Proportion of Flood Hazard Zones in Denpasar urban (left) and peri-urban region (right)
..............................................................................................................................................32 Figure 23: Proportion of Flood Risk Zones in Denpasar urban (left) and peri-urban region (right) .....33 Figure 24: Proportion of Residential and Public Urban Fabric in flood prone areas
(high/medium/low/no hazard) – in Denpasar urban (left) and peri-urban region (right) .....33 Figure 25: Proportion of Residential and Public Urban Fabric in Flood Risk areas (very
high/high/medium/no risk) – in Denpasar urban (left) and peri-urban region (right) ..........34 Figure 26: Map of Residential and Public Urban Fabric combined with Flood Risk Zoning in the
centre of Denpasar (Image: Quickbird 20170103) ...............................................................34 Figure 27: Proportion of high-ranking infrastructure in flood prone areas (high/medium/low/no
hazard) – in Denpasar urban (left) and peri-urban region (right) .........................................35 Figure 28: Proportion of high-ranking infrastructure in Flood Risk areas (high/medium/no risk) –
in Denpasar urban (left) and peri-urban region (right) .........................................................35 Figure 29: Proportion of construction sites in flood prone areas (low/no hazard) – in Denpasar Core
City .......................................................................................................................................35 Figure 30: Proportion of commercial and industrial units in flood prone areas
(high/medium/low/no hazard) – in Denpasar Core City ......................................................36 Figure 31: Proportion of agricultural land in flood prone areas (high/medium/low/no hazard) – in
Denpasar urban (left) and peri-urban region (right) .............................................................36
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Figure 32: Proportion of natural and semi-natural areas in flood prone areas (high/medium/low/no
hazard) – in Denpasar urban (left) and peri-urban region (right) .........................................36
List of Tables
Table 1: LU/LC Nomenclature used for Denpasar for the years 2006 and 2016 ................................ 5 Table 2: Number of sampling points for the EO4SD-Urban mapping classes after applied
sampling design ................................................................................................................... 10 Table 3: Validation result of the complemented transport network in Denpasar, which is based
on OSM data ........................................................................................................................ 14 Table 4: Overall LU/LC Statistics 2006 and 2016 ............................................................................ 23 Table 5: Statistics of change categories ............................................................................................. 25 Table 6: Statistics of changes of Agricultural Areas ......................................................................... 26 Table 7: Land use classes and reclassification to pre-defined damage levels ................................... 29 Table 8: Flood hazard and risk classification (Flood Risk Matrix) ................................................... 30
List of Abbreviations
AoI Area of Interest
AWEInsh Automated Water Extraction Index
CS Client States
DEM Digital Elevation Model
DLR German Space Agency
DOS Dark Object Subtraction
EEA European Environmental Agency
EGIS Consulting Company for Environmental Impact Assessment and Urban Planning, France
ENVISAT Environmental Satellite, ESA's successor to ERS
EO Earth Observation
EO4SD Earth Observation for Sustainable Development
ERS European Remote Sensing satellites by ESA
ESA European Space Agency
EU European Union
GAF GAF AG, Geospatial Service Provider, Germany
GIS Geographic Information System
GISAT Geospatial Service Provider, Czech Republic
GISBOX Romanian company with activities of Photogrammetry and GIS
GPS Global Positioning System
GPS Global Positioning Systems
GUF Global Urban Footprint
HHWL Highest High Water Level
HR High Resolution
HRL High Resolution Layer
IFI International Financing Institute
InSAR Interferometric SAR
INSPIRE Infrastructure for Spatial Information in the European Community
ISGNSS International Symposium on Global Navigation Satellite System (GNSS)
ISO/TC 211 Standardization of Digital Geographic Information
JR JOANNEUM Research, Austria
LC / LU Land Cover/ Land Use
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LULUC Land Use and Land Use Change
MMU Minimum Mapping Unit
MSL Mean Sea Level
NDVI Normalized Difference Vegetation Index
NEO Geospatial Service Provider, The Netherlands
NNE North-Northeast
OSM OpenStreetMap
QA Quality Assurance
QC Quality Control
QM Quality Management
RTRW Rencana Tata Ruang Wilyah
SAR Synthetic Aperture Radar
SBAS Small Baseline Subset Method
SP Service Provider
SRTM Shuttle Radar Topography Mission
SSW South-Southwest
TEP Thematic Exploitation Platform
ToC Table of Contents
VHR Very High Resolution
WB World Bank
WBG World Bank Group
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1 Introduction General Background of EO4SD-Urban
Since 2008 the European Space Agency (ESA) has worked closely together with the International
Finance Institutes (IFIs) and their client countries to demonstrate the benefits of Earth Observation (EO)
in their operations. Earth Observation for Sustainable Development (EO4SD) is a new ESA initiative,
which aims to achieve an increase in the uptake of satellite based information in the regional and global
IFI programmes. The EO4SD-Urban project initiated in May 2016 (with a duration of 3 years) has the
overall aim to integrate the application of satellite data for urban development programmes being
implemented by the IFIs and Multi-Lateral Development Banks (MDBs) with the developing countries.
The overall goal will be achieved via implementation of the following main objectives:
To provide the services on a regional basis (i.e. large geographical areas); in the context of the
current project with a focus on S. Asia, SE Asia, Latin America and Africa, for at least 35-40
cities.
To ensure that the products and services are user-driven; i.e. priority products and services to
be agreed on with the MDBs in relation to their regional programs and furthermore to implement
the project with a strong stakeholder engagement especially in context with the validation of the
products/services on their utility.
To provide a service portfolio of baseline and derived urban-related geo-spatial products that
have clear technical specifications, and are produced on an operational manner that are
stringently quality controlled and validated by the user community.
To provide a technology transfer component in the project via capacity building exercises in the
different regions in close co-operation with the MDB programmes.
This report supports the fulfilment of the third objective which requires the provision of geo-spatial
baseline and derived geo-spatial products to various stakeholders in the MDBs and counterpart City
Authorities. The report provides a service description in Chapter 2, and then in Chapter 3 systematically
reviews the main production steps involved and importantly highlights whenever there are Quality
Control (QC) mechanisms involved; the related QC forms are provided in the Annexe of this report. The
description of the processes are kept intentionally at a top level and avoiding technical details as the
report is considered mainly for non-technical MDB staff/experts and City Authorities. Finally Chapter
4 presents the standard analytical work undertaken with the products which can provide further inputs
into urban development assessments, modelling and reports.
2 Service Description
The following Section summarises the service as it has been realised for the city of Denpasar in
Indonesia within the EO4SD-Urban Project and as it had been delivered to the User in the month of
August 2017.
2.1 Stakeholders and Requirements
The EO4SD-Urban products will be used as part of the World Bank City Planning Labs (CPL)
programme. CPL is a technical assistance program that is developing the capacity for evidence-based
planning in Indonesian cities. This will be achieved by developing municipal spatial data infrastructures
(MSDI) and an integrated ICT platform, or "geoportal", for data sharing. In addition, CPL is committed
to developing sustainable practices, so the programme will have a capacity building component. The
program will conduct training for municipal government personnel to use geospatial planning tools, and
further develop and maintain the MSDI and geoportal.
Currently, the city of Denpasar has partnered with the CPL technical assistance initiative to develop
Denpasar’s ability to perform geospatial planning and data sharing. Denpasar is interested to use remote
sensing to develop data about urban growth, Land Use/Land Cover changes, transportation
infrastructure and accessibility, population density/distribution, and flooding issues in the city. The
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EO4SD-Urban project datasets and analyses will help the city develop planning policies, and inform its
medium-term and long-term plans towards the goal of making Denpasar a more resilient and sustainable
city.
2.2 Service Area Specification
The approach taken to demarcate the service area for map production for Denpasar was to present the
border (digitised) of the Core built up area and a wider extent for the Peri-Urban Area using Google
Earth as a background. These drafted boundaries were then sent to the World Bank team who shared it
with the City Authorities to fine tune the boundaries. The resulting Areas of Interest (AoIs) for both
Core and Peri-Urban agreed on for the service area for production is depicted in Figure 1 below.
Figure 1: Illustration of Core and Peri-Urban Areas for Mapping
The Core region has an area of 132km2 and the Peri-Urban an area of 409 km2 for a total service area of
541 km2.
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2.3 Product List and Product Specifications
During the discussions related to the AoIs the planned geo-spatial products were also presented and
reviewed with the WB Team and users. It was noted that the Baseline Land Use products (for the Core
and Peri-Urban Areas) were a standard product that would be provided for all cities as it is required for
the derived products. In the case of Denpasar the full list of products for both the Core and Peri-Urban
Areas are as follows:
Urban Land Use/Land Cover and the change between two points in time
Transport Infrastructure – Road Network
Flood History Assessment
This report will focus on the Baseline products of LU/LC as well as the change between two points in
time; for each EO4SD-Urban city two time slots of 2006 and 2016 were offered to the Users for the
assessment of changes in a 10 year epoch (for the different geo-spatial products). Due to EO data
availability the time epochs varied with plus or minus a year or two around these 2 time slots.
2.3.1 Land Use/Land Cover Nomenclature
A pre-cursor to starting production was the establishment with the stakeholders on the relevant Land
Use/Land Cover (LU/LC) nomenclature as well as class definitions. The approach taken was to use a
standard remote sensing based LU/LC nomenclature and then adapt it to the user’s LU requirements.
Thus the remote-sensing based LU/LC classes in the urban context can be grouped into 5 Level 1 classes,
which are Artificial areas, Natural/ Semi Natural, Agricultural, Wetland, Water bodies. These classes
can then be sub-divided into several different more detailed classes such that the dis-aggregation can be
down to Level 2 to 4 (with Level 4 being the most detailed classes). This hierarchical classification
system is often used in operational urban mapping programmes and is the basis for example of the
European Commission’s Urban Atlas programme which provides pan-European comparable LU/LC
data with regular updates. A depiction of the way the levels and classes are structured is presented as
follows:
Level I Artificial surfaces
- Level II Urban Fabric
Level III
Continuous Urban Fabric (Sealing Layer-SL > 80%)
Discontinuous Urban Fabric (S.L. 10% - 80%)
Discontinuous Dense Urban Fabric (S.L. 50% - 80%)
Discontinuous Medium Density Urban Fabric (S.L. 30% - 50%)
Discontinuous Low Density Urban Fabric (S.L. 10% - 30%)
Discontinuous Very Low Density Urban Fabric (S.L. < 10%)
- Level II
Industrial, commercial, public, military, private and transport units
Level III
Industrial, commercial, public, military and private units zoning data
Road and rail network and associated land (Open Street Map or in-country data needed)
- Level IV Fast transit roads and associated land
(Reference: European Union, 2011)
It should be noted that in the current project, the Level 1 classes were used as the basis for classification
of the Peri-Urban Areas using the High Resolution (HR) data such as Landsat or Sentinel-2. However,
for the Core Urban Areas using the Very High Resolution (VHR) data with higher spatial resolution it
was possible to go down to Level 3 and 4. The different levels, classes and sub-classes from the remote
sensing based urban classification, were adapted to the User requirements based on existing Master
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Plans for cities and/or direct advice from the User on critical classes required. The final LU/LC
nomenclature had to be endorsed by the User before production started.
In order to link the Urban Atlas classes described in the previous Section with the two Indonesian cities
of Semarang and Denpasar, the Consortium used the documentation provided by the cities for their
Master Plans. The urban planning in Indonesia requires cities to develop regional spatial planning or
Rencana Tata Ruang Wilayah (RTRW) for each city. The information provided for Denpasar from the
City Authorities included an English translated version of the RTRW for 2011, and geo-spatial data
provided included the Land Use Map for Denpasar from 2012 as presented in Figure 2.
Figure 2: Land Use Map of Denpasar, 2012 (Reference: World Bank, CPL Programme, 2017)
The main LU classes depicted in the RTRW, were reviewed to assess which classes could be linked to
the LU/LC Nomenclature from the Urban Atlas and therefore observed using the VHR data. See LU/LC
Nomenclature for Denpasar in Table 1.
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Table 1: LU/LC Nomenclature used for Denpasar for the years 2006 and 2016
2006 2016
Level I Level II Level III Level IV Level I Level II Level III Level IV
1000
Artificial Surfaces
1100 Residential 1100 Very
High Density
1000
Artificial Surfaces
1100 Residential 1100 Very
High Density
1120 High
Density
1120 High
Density
1130 Medium
Density
1130 Medium
Density
1140 Low
Density
1140 Low
Density
1150 Super
Low Density
1150 Super
Low Density
1200 Industrial,
Commercial, Public, Military,
Private and
Transport Units
1210
Industrial, Commercial,
Public,
Military and Private Units
1200 Industrial,
Commercial, Public, Military,
Private and
Transport Units
1210
Industrial, Commercial,
Public,
Military and Private Units
1211
Commercial Area
1212
Industrial Area
1213
Business
District
1214
Education
Facilities
1215
Military
1216 Health
Facilities
1217 Public
Buildings
1220 Roads 1221
Arterial Road
1220 Roads 1221
Arterial Road
1222
Toll Line
1222
Toll Line
1223 Collector
Road
1223 Collector
Road
12.3 Railway 123 Railway
124 Port 124 Port
125 Airport 125 Airport
1300 Mine,
Dump and
1310
Mineral
Extraction
1311
Mining
Area
1300 Mine,
Dump and
1310
Mineral
Extraction
1311
Mining
Area
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2006 2016
Level I Level II Level III Level IV Level I Level II Level III Level IV
Construction
Sites
and Dump
Sites 1312
Landfill
Construction
Sites
and Dump
Sites 1312
Landfill
1320 Construction
Sites
1320 Construction
Sites
1330 Open
Space
1330 Open
Space
1400 Artificial
Non-Agricultural
Vegetated Areas
1410 Urban
Green
Spaces
1411 Urban
Parks
(Parks, Gardens)
1400 Artificial
Non-
Agricultural Vegetated Areas
1410 Urban
Green
Spaces
1411 Urban
Parks
(Parks, Gardens)
1412
Cemeteries
1412
Cemeteries
1420 Sport Facilities
(Sport
Fields, Sport Stadiums,
Golf
Courses, …)
1420 Sport Facilities
(Sport
Fields, Sport Stadiums,
Golf
Courses, …)
2000
Agricultural Area
2000
Agricultural Area
3000 Natural
and Semi-Natural areas
3100 Forest 3000 Natural
and Semi-Natural Areas
3100 Forest
3200 Fisheries 3200 Fisheries
3300 Grassland
and Shrubs/Natural
Area
3300 Grassland
and Shrubs/Natural
Area
3400 Bare Soil 3400 Bare Soil
3500 Mangrove 3500 Mangrove
3600 Beach 3600 Beach
4000 Peat/
Wetland/
Swamp
4000 Peat/
Wetland/
Swamp
5000 Water 5000 Water
It is important to note that the possibility to classify at Level IV was highly dependent on the availability
of reliable reference datasets from the city or sources such as Google Earth and Open Street Map (OSM)
data. This aspect is further discussed in Chapter 3.
See Annex 1 for finalised nomenclature and class definitions for Denpasar.
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2.3.2 Transport Infrastructure – Road Networks
The road hierarchy used in the classification is based on the international road classification standards;
this is for example defined by the European Commission (https://ec.europa.eu/transport/road_safety/-
specialist/knowledge/road/designing_for_road_function/road_classification_en).
Roads are divided into three groups-arterial or through traffic flow routes (in our case Arterial Roads),
distributor road (in our case Collector Roads), and access roads (in our case Local Roads). The three
road types are defined as follows:
Arterial Roads:
Roads with a flow function allow efficient throughput of (long distance) motorized traffic. All
motorways and express roads as well as some urban ring roads have a flow function. The number of
access and exit points is limited. (https://ec.europa.eu/transport/road_safety/specialist/knowledge/-
road/designing_for_road_function/road_classification_en)
Collector Roads:
Roads with an area distributor function allow entering and leaving residential areas, recreational areas,
industrial zones, and rural settlements with scattered destinations. Junctions are for traffic exchange
(allowing changes in direction etc.); road sections between junctions should facilitate traffic in flowing.
(https://ec.europa.eu/transport/road_safety/specialist/knowledge/road/designing_for_road_function/roa
d_classification_en)
Local Roads:
Roads with an access function allow actual access to properties alongside a road or street. Both junctions
and the road sections between them are for traffic exchange. (https://ec.europa.eu/transport/-
road_safety/specialist/knowledge/road/designing_for_road_function/road_classification_en).
Arterial roads and collector roads were the main focus of the classification. These types of roads were
identified for the entire AoI. Within the geospatial dataset the road features can be identified within the
attribute table. A value of 1 is assigned to the arterial roads and a value of 2 to the collector lines.
Spatial Accuracy:
The Collector Roads and Arterial Roads are integrated within the LULC mapping by applying a buffer
around the road centre lines of 12.0 m for the Arterial Roads and 7.5m for Collector Roads. The 7.5m
are set as the maximum allowable difference of the mapped centre line in comparison to the location in
the VHR imagery.
2.4 Terms of Access
The dissemination of the digital data and the report was undertaken via FTP.
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3 Service Operations
This Chapter presents all the main steps of the service operations including the necessary input data, the
processing methods, the accuracy assessment and Quality Control procedures. Methods are presented
in a top-level and standardised manner for all the EO4SD-Urban City Reports.
3.1 Source Data
This Section presents the remote sensing and ancillary datasets that were used. Different types of data
from several data providers have been acquired. A complete list of source data as well as a quality
assessment is provided in Annex 3.
A summary of the main EO data used overall in the project is described herewith.
High Resolution Optical EO Data
The major data sources for the Peri-Urban current and historic mapping of urban LULC, urban extent
and imperviousness were Sentinel-2 and Landsat data which were accessible and downloadable free of
charge.
Sentinel-2: the most recent data coverage comprises of 2 Sentinel-2 from 07 June 2016. Level-
1A data were downloaded.
Landsat 7: As a source of historical data two scenes of Landsat TM 7 from 09 December 2000
and 21 May 2002 has been acquired to get a cloud free image of the whole area of interest.
All images have been used as baseline data in the production process of the Peri-Urban LU/LC. The
ortho-rectification was achieved by an image to image registration using the Global Landcover-Ortho
image product. The NASA accuracy specification for the Global Landcover-Ortho product was 50m
RMSE, everywhere in the world.
Very High Resolution Optical EO Data
For Denpasar the VHR data used were WorldView-2 and Quickbird-2. The VHR data for the Core
Urban Area mapping had to be acquired and purchased through commercial EO Data Providers such as
Airbus Defence and Space and European Space Imaging.
It has to be noted that under the current collaboration project the VHR EO data had to be purchased
under single-user license agreements between GAF AG and the EO Data Providers. If EO data would
have to be distributed to other stakeholders then further licence up-grades for multiple users would have
to be requested from the EO Data Providers which may result in additional costs.
The following VHR sensor data have been acquired:
WorldView-2: the most recent data coverage for the Core Urban Area comprises of 2 scenes,
both acquired on 08 September 2015.
Quickbird-2: for the historic data 2 scenes from 28 May 2008 and one scene 10 June 2006
were used.
Detailed lists of the used EO data as well as their quality is documented in the attached Quality
Control (QC) sheets in Annex 3.
Ancillary Data
A variety of reference data was provided by the City Authorities and the WB team at the inception of
production. This constituted existing VHR data as well as *.shp files for Land Use features and other
datasets such as Land Use Map 2012, spatial data for hospitals/clinics, schools/universities, parks, and
cemeteries. For the datasets that could be used as reference information to support the current
classification a QC was done and the results are provided in the QC sheets in Annex 3. It should be
noted that these datasets had limited metadata and no QC sheets provided and therefore there were
constraints to use them in an integrated manner during the production process in the current project.
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3.2 Processing Methods
Data processing starts at an initial stage with quality checks and verification of all incoming data. This
assessment is performed in order to guarantee the correctness of data before geometric or radiometric
pre-processing is continued. These checks follow defined procedures in order to detect anomalies,
artefacts and inconsistencies. Furthermore all image and statistical data were visualised and interpreted
by operators.
The main techniques and standards used for data analysis, processing and modelling for each product
are described in Annex 2.
3.3 Accuracy Assessment of Map Products
Data and maps derived from remote sensing contain - like any other map - uncertainties which can be
caused by many factors. The components, which might have an influence on the quality of the maps
derived from EO include quality and suitability of satellite data, interoperability of different sensors,
radiometric and geometric processing, cartographic and thematic standards, and image interpretation
procedures, post-processing of the map products and finally the availability and quality of reference
data. However, the accuracy of map products has a major impact on secondary products and its utility
and therefore an accuracy assessment was considered as a critical component of the entire production
and products delivery process. The main goal of the thematic accuracy assessment was to guarantee the
quality of the mapping products with reference to the accuracy thresholds set by the user requirements.
The applied accuracy assessments were based on the use of reference data, and applying statistical
sampling to deduce estimates of error in the classifications. In order to provide an efficient, reliable and
robust method to implement an accuracy assessment, there are three major components that had to be
defined: the sampling design, which determines the spatial location of the reference data, the response
design that describes how the reference data is obtained and an analyses design that defines the accuracy
estimates. These steps were undertaken in a harmonised manner for the validation of all the geo-spatial
products.
3.3.1 The Applied Sampling Design
The sampling design specifies the sample size, sample allocation and the reference assessment units
(i.e. pixels or image blocks). Generally, different sampling schemes can be used in collecting accuracy
assessment data including: simple random sampling, systematic sampling, stratified random sampling,
cluster sampling, and stratified systematic unaligned sampling. In the current project a single stage
stratified random sampling based on the method described by Olofson et al (2013) was applied which
used the map product as the basis for stratification. This ensured that all classes, even very minor ones,
were included in the sample.
However, in complex LU/LC products with many classes, this usually results in a large number of
strata (one stratum per LU/LC classes), of which some classes cover only very small areas (e.g. sport
fields, cemeteries) and not being adequately represented in the sampling. In order to achieve a
representative sampling for the statistical analyses of the mapping accuracy it was decided to extend
the single stage stratified random sampling. At the first stage the number of required samples was
allocated within each of the Level I strata (see Table 2). In the second stage all Level III classes that
were not covered by the first sampling, were grouped into one new stratum. Within that stratum the
same number of samples was randomly allocated as the Level I strata received. To avoid a clustering
of point samples within classes and to minimise the effect of spatial autocorrelation a minimum
distance in between the sample points was set to be 150 m. The final sample size for each class can be
considered to be as close as possible to the proportion of the area covered by each stratum considering
that the target was to determine the overall accuracy of the entire map.
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The total sample size per stratum was determined by the expected standard error and the estimated
error rate based on the following formula which assumes a simple random sampling (i.e. the
stratification is not considered):
n = 𝑃∗𝑞
(𝐸
𝑧)²
n = number of samples per strata / map class
p = expected accuracy
q = 1 – p
E = Level of acceptable (allowable) sample error
Z = z-value (the given level of significance)
Hence, with an expected accuracy of p = 0.89, a 95% confidence level and an acceptable sampling
error of 5%, the minimum sample size is 196. A 10% oversampling was applied to compensate for
stratification inefficiencies and potentially inadequate samples (e.g. in case of cloudy or shady
reference data). For each Level I strata 215 samples have been randomly allocated. Afterwards, within
all classes of Level III (see Table 2) that did not received samples in the first run, additionally 215
samples were randomly drawn across all these classes.
Table 2: Number of sampling points for the EO4SD-Urban mapping classes after applied sampling design
Class Name Class
ID
No. of
Sampling
Points
Km²
Coverage of
the Class
Residential 1100 167 202.55
Industrial, Commercial,
Public, Education
1210 44 18.59
Roads 1220 1 5.83
Port 1240 1 0.39
Airport 1250 29 2.34
Mining Area, Landfill 1310 31 0.27
Construction Site 1320 26 0.27
Open Space 1330 5 0.88
Urban Parks, Cemeteries 1410 2 0.81
Sport Facilities 1420 3 0.66
Agriculture 2000 227 170.67
Forest 3100 135 56.56
Fisheries 3200 7 0.60
Grassland 3300 60 5.41
Bare Soil 3400 5 0.31
Mangroves 3500 9 10.98
Beach 3600 4 1.39
Wetlands 4000 63 0.76
Water 5000 201 62.23
3.3.2 The Applied Response Design
The response design determines the reference information for comparing the map labels to the reference
labels. Collecting reference data on the ground by means of intensive fieldwork is both costly and time
consuming and in most projects not feasible. The most cost effective reference data sources are VHR
satellite data with 0.5 m to 1 m spatial resolution. Czaplewski (2003) indicated that visual interpretation
of EO data is acceptable if the spatial resolution of EO data is sufficiently better compared to the
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thematic classification system. However, if there are no EO data with better spatial resolution available,
the assessment results need to be checked against the imagery used in the production process.
The calculated number of necessary sampling points for each mapping category was randomly
distributed among the strata and overlaid to the VHR data of each epoch. The following Figure is
showing the mapping result with the overlaid sample points.
Figure 3: Mapping result of the city of Denpasar of the year 2016 overlaid with randomly distributed sample
points for accuracy assessment
In this way a reference information could be extracted for each sample point by visual interpretation of
the VHR data for all mapped classes. The size of the area to be observed had to be related to the
Minimum Mapping Unit (MMU) of the map product to be assessed. The reference information of each
sampling point was compared with the mapping results and the numbers of correctly and not-correctly
classified observations were recorded for each class. From this information the specific error matrices
and statistics were computed (see next Section).
3.3.3 The Applied Analysis Design
Each class usually has errors of both omission and commission, and in most situations, these errors for
a class are not equal. In order to calculate these errors as well as the uncertainties (confidence intervals)
for the area of each class a statistically sound accuracy assessment was implemented.
The confusion matrix is a common and effective way to represent quantitative errors in a categorical
map, especially for maps derived from remote sensing data. The matrices for each assessment epoch
were generated by comparing the “reference” information of the samples with their corresponding
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classes on the map. The Reference represented the “truth”, while the Map provided the data obtained
from the map result. Thematic accuracy for each class and overall accuracy is then presented in error
matrices (see Tables below). Unequal sampling intensity resulting from the random sampling approach
was accounted for by applying a weight factor (p) to each sample unit based on the ratio between the
number of samples and the size of the stratum considered:
�̂�𝑖𝑗 = (1
𝑀) ∑
1
𝜋𝑢ℎ∗
𝑥∈(𝑖,𝑗)
Where i and j are the columns and rows in the matrix, M is the total number of possible units (population)
and π is the sampling intensity for a given sample unit u in stratum h.
Overall accuracy and User and Producer accuracy were computed for all thematic classes and 95%
confidence intervals were calculated for each accuracy metric.
The standard error of the error rate was calculated as follows: 𝜎ℎ = √𝑝ℎ(1−𝑝ℎ)
𝑛ℎ where nh is the sample
size for stratum h and ph is the expected error rate. The standard error was calculated for each stratum
and an overall standard error was calculated based on the following formula:
𝜎 = √∑ 𝑤ℎ2. 𝜎ℎ
2
In which 𝑤ℎ is the proportion of the total area covered by each stratum. The 95% Confidence Interval
(CI) is +/- 1.96*𝜎.
The confusion matrices are provided Quality Control documentation the Annex 3 and showing the
mapping error for each relevant class. For each class the number of samples which are correctly and not
correctly classified are listed, which allows the calculation of the user and producer accuracies for each
class as well as the confidence interval at 95% confidence levels based on the formulae above.
The Land Use/Land Cover product for Denpasar has an overall mapping accuracy of 89.11% with
a Confidence Interval ranging from 87.14% to 91.07% at a 95% CI. The specific class accuracies
are given in Annex 3.
3.4 Accuracy Assessment of Transport Network
The road network was partially integrated in the LULC map by selecting first and second level roads.
These are the Arterial Lines and the Collector Lines. For the accuracy assessment of the road network
it should be noted that the sampling design, response design and analyses design are different from the
one used for validating the LULC maps. The Accuracy Assessment of the Transport Network is related
to the geospatial precision of the collected and digitised centerlines of the roads.
Sampling Methodology
A systematic random sampling was applied to define the primary and secondy sampling units. Over the
entire AoI a regular grid of 450m by 450m was created. Based on these grid cells a random selection of
2% samples cells were selected. An example is given in Figure 4 with the road network in grey, the grid
cells in black and the randomly selcted cells in green.
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Figure 4: Example of the applied sampling design to generate randomly distributed point for the accuracy
assessment of the road network
Within the randomly selected cells another grid of 150m distance was created (see Figure 5). All
intersection between the created road layer and the 150m grid were extracted as points. At all points the
road locations were visually checked and if any, the differences between spatial location on VHR
imagery and spatial location of the digitised lines recorded.
Figure 5: Secondary sampling grid to generate the sampling points at spatial intersection of roads and grid
cells; roads are represented as white lines, grid as black lines and final sampling point as black
dots
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Overall 280 sampling points were created and their differences recorded. The result is presented in Table
3 as histogram of deviations. For the entire sampling population a Mean Difference of 0.67 m and a
Standard Deviation of 1.14 m was calculated.
Table 3: Validation result of the complemented transport network in Denpasar, which is based on OSM
data
Distance in m Frequency
0.0 183
0-1 13
1-2 50
2-3 17
3-4 11
4-5 5
5-6 0
6-7 1
Above 7.5 meters 0
By setting a maximum allowable difference of 7.5 m the distances are separated into two classes. Correct
street locations and in-correct street locations.
3.5 Quality Control/Assurance
A detailed Quality Control and Quality Assurance (QC/QA) system has been developed which records
and documents all quality relevant processes ranging from the agreed product requirements, the different
types of input data and their quality as well as the subsequent processing and accuracy assessment steps.
The main goal of the QC/QA procedures was the verification of the completeness, logical consistency,
geometric and thematic accuracy and that metadata are following ISO standards on geographic data
quality and INSPIRE data specifications. These assessments were recorded in Data Quality Sheets
which are provided in Annex 2. The QC/QA procedures were based on an assessment of a series of
relevant data elements and processing steps which are part of the categories listed below:
Product requirements;
Specifications of input data: EO data, in-situ data, ancillary data;
Data quality checks: EO data quality, in-situ data quality, ancillary data quality;
Geometric correction, geometric accuracy, data fusion (if applicable), data processing;
Thematic processing: classification, plausibility checks;
Accuracy: thematic accuracy, error matrices
Delivery checks: completeness, compliancy with requirements
After each intermediate processing step a QC/QA was performed to evaluate products appropriateness
for the subsequent processing (see Figure below).
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After the initial definition of the product specifications (output) necessary input data were defined and
acquired. Input data include all satellite data and reference data e.g. in-situ data, reference maps,
topographic data, relevant studies, existing standards and specifications, statistics. These input data were
the baseline for the subsequent processing and therefore all input data had to be checked for
completeness, accuracy and consistency. The evaluation of the quality of input data provides
confidence of their suitability for further use (e.g. comparison with actual data) in the subsequent
processing line. Data processing towards the end-product required multiple intermediate processing
steps. To guarantee a traceable and quality assured map production the QC/QA assessment was
performed and documented by personnel responsible for the Quality Control/Assurance. The results of
all relevant steps provided information of the acceptance status of a dataset/product.
The documentation is furthermore important to provide a comprehensive and transparent summary of
each production step and the changes made to the input data. With this information the user will be able
to evaluate the provided services and products. Especially the accuracy assessment of map products and
the related error matrices are highly important to rate the quality and compare map products from
different service providers.
The finalised QC/QA forms are attached in Annex 3.
3.6 Metadata
Metadata provides additional information about the delivered products to enable it to be better
understood. In the current project a harmonised approach to provide metadata in a standardised format
applicable to all products and end-users was adopted. Metadata are provided as XML files, compliant
to the ISO standard 19115 "Metadata" and ISO 19139 "XML Scheme Implementation". The metadata
files have been created and validated by the GIS/IP-operator for each map product with the Infrastructure
for Spatial Information in Europe (INSPIRE) Metadata Editor available at: http://inspire-
geoportal.ec.europa.eu/editor/.
The European Community enacted a Directive in 2007 for the creation of a common geo-data
infrastructure to provide a consistent metadata scheme for geospatial services and products that could
be used not only in Europe but globally. The geospatial infrastructure called INSPIRE was built in a
close relation to existing International Organization for Standardization (ISO) standards. These are ISO
191115, ISO 19119 and ISO 15836. The primary incentive of INSPIRE is to facilitate the use and
sharing of spatial information by providing key elements and guidelines for the creation of metadata for
geospatial products and services.
The INSPIRE Metadata provides a core set of metadata elements which are part of all the delivered geo-
spatial products to the users. Furthermore, the metadata elements provide elements that are necessary to
perform queries, store and relocate data in an efficient manner. The minimum required information is
specified in the Commission Regulation (EC) No 1205/2008 of 3 December 2008 and contains 10
elements:
Figure 6: Quality Control process for EO4SD-Urban product generation; at each intermediate processing
step output properties are compared against pre-defined requirements
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Information on overall Product in terms of: Point of contact for product generation, date of
creation
Identification of Product: Resource title, Abstract (a short description of product) and Locator
Classification of Spatial Data
Keywords (that define the product)
Geographic information: Area Coverage of the Product
Temporal Reference: Temporal extent; date of publication; date of last revision; date of
creation
Quality and Validity: Lineage, spatial resolution
Conformity: degree of conformance to specifications
Data access constraints or Limitations
Responsible party: contact details and role of contact group/person
These elements (not exhaustive) constitute the core information that has to be provided to meet the
minimum requirements for metadata compliancy. Each element and its sub-categories or elements have
specific definitions; for example in the element “Quality” there is a component called “Lineage” which
has a specific definition as follows: “a statement on process history and/or overall quality of the spatial
data set. Where appropriate it may include a statement whether the data set has been validated or quality
assured, whether it is the official version (if multiple versions exist), and whether it has legal validity.
The value domain of this element is free text,” (INSPIRE Metadata Technical Guidelines, 2013). The
detailed information on the metadata elements and their definitions can be found in the “INSPIRE
Metadata Implementing Rules: Technical Guidelines,” (2013). Each of the EO4SD-Urban products will
be accompanied by such a descriptive metadata file. It should be noted that the internal use of metadata
in these institutions might not be established at an operational level, but the file format (*.xml) and the
web accessibility of data viewers enable for the full utility of the metadata.
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4 Analysis of Mapping Results
This Chapter will present and assess all results which have been produced within the framework of the
current project, in the context of presentation of the Urban Extent product, the LU/LC products, the
Transport Infrastructure product and the Flood Risk product. Furthermore the Sections that follow will
provide the results of some standard analytics undertaken with these products including the following:
Urban Extent – Developments from 2000, 2005, 2010 to 2015
Land Cover Land Use - Status and Trends between 2006 and 2016
Transport Infrastructure – Development between 2006 and 2016
Flood Risk Assessment
It is envisaged that these analytics provide information on general trends and developments in the Core
and Peri-Urban Areas which can then be further interpreted and used by Urban Planners and the City
Authorities for city planning.
It should be noted that all digital data sets for these products are provided in concurrence with this City
Report with all the related metadata and Quality Control documentation. Furthermore, it has to be
acknowledged that this Chapter presents only a summary and overview of what is possible with the geo-
spatial datasets provided for Denpasar in the current EO4SD Urban project. Further geospatial analyses
with the presented products are beyond the scope of this project and could be part of future
collaborations.
4.1 Urban Extent – Developments from 2000, 2005, 2010 and 2015
The Urban Extent product in the EO4SD-Urban project is provided by the German Aerospace Centre
(DLR) and is provided for 4 points in time; the 2015 Global Urban Footprint (GUF) Plus product has
been produced jointly exploiting multi-temporal 30m Landsat-8 and ESA Sentinel-1 data with 10m
resolution acquired in 2014-2015. And for the years 2000, 2005 and 2010, the Urban Extent products
generated – given the unavailability of freely and easily accessible multi-temporal radar data at high
resolution – were based only on multi-temporal 30m Landsat-5 and Landsat-7 imagery, and scaled up
to 10m resolution.
As the Urban Extent 2015 product was based on the ESA Sentinel-1 dataset which is a Synthetic
Aperture Radar (SAR) in C band it should be noted that some structures which are flat in nature such as
airport runways were not classified; this is due to the fact that radar relies on backscatter which is more
prominent from vertical features. The GUF+ 2015 products will be validated and available as public
domain data from October 2017 onwards on the Urban Thematic Exploitation Platform (TEP) supported
by the DLR.
In the current project the Urban Extent product for Denpasar was first used to assess historical
developments from 2000-2015 and then overlaid with Ward boundaries to assess urbanisation extent
patterns based on administrative units.
Results:
The first result provided using the different Urban Extent products from 2000 to 2015 is illustrated in
Figure 7 which shows the urban development in the Core and Peri-Urban Areas as well as surrounding
regions of Denpasar. The Urban Extent developments after 2000 can be examined by Urban Planners to
identify different patterns of growth such as “Edge Growth” or “Leapfrog Growth” depending on the
location of the developments.
From the urban extent developments between 2000 and 2015 depicted in Figure 7, one can note that
urban extent development occurred in large patches specifically in the epochs between 2000 and 2005
(red patches); in the Core Urban Area it occurred notably in the west and northern borders and in the
Peri-Urban in the west. The urban extent between 2010 and 2015 then seemed to cluster around the
growth spots of 2005. And the growth in 2015 (blue patches) was notable in the southern Peninsula-
Bukit. A more quantitative depiction of the urban extent in percent is presented in Figure 8 which
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illustrates the extent of built up area per administrative units between 2000 and 2015 and shows that the
main areas of growth occurred in the very north and south regions of Denpasar.
Figure 7: Urban Extent developments in the epochs 2000 to 2005, 2005 to 2010 and 2010 to 2015 in Denpasar
and surrounding region
Figure 8: Increase of Urban Extent between 2000 and 2015, in percent per administrative units
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For the different 5 year epochs the analysis undertaken used the urban extent data overlaid with the
administrative units for the Core Urban Area of Denpasar and calculated the percent (%) change in
different classes with the low change categories ranging from 0-2% to 10% and the high change classes
being 40-69% or over 60%. Thus the Figure 9 illustrates that the urban extent started intensifying in the
northern and western parts in the epoch from 2000 to 2005 and a bit in the south. The urban extent
continued to be high in the northern part of the Core area in the next epoch from 2005 and 2010 (Figure
10).
Figure 9: Increase of Urban Extent between 2000 and 2005, in percent per administrative units
Figure 10: Increase of Urban Extent between 2005 and 2010, in percent per administrative units
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Finally between 2010 and 2015 the urban extent showed the highest change again in the northern areas
but also increased in the south-west and south (see Figure 11).
Figure 11: Increase of Urban Extent between 2010 and 2015, in percent per administrative units
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4.2 Land Cover/ Land Use 2006 and 2016
This Section will present the results of the LU/LC mapping for 2006 and 2016 as well the statistical
information on the changes between these two epochs.
The LU/LC overview map for 2016 is depicted in Figure 12 and a cartographic version with map layout
design is provided as geo-pdf files with the digital data.
Figure 12: Detailed Land Cover/ Land Use 2016 - Spatial distribution
For the epoch 2006 the main/dominant LU/LC classes occurring in the overall Core and Peri-Urban
Regions (combined) were Agricultural Area (38.97% of total area), Residential (32.03% of total area)
and forest (8.03% of total area). By 2016 these classes remained the main/dominant LU/LC classes with
slight increases in overall area of the Residential class (36.68%) and the Forest are (10.44% of total
area) coupled with a decrease of the Agricultural Area (31.52% of total area). This information on the
classes are dis-aggregated and presented as percentages and area coverages in Figure 13 and Figure 14
for the epochs 2006 and 2016 respectively. The Table 3 also presents the detailed information on area
and percentage of total area for each class for 2006 and 2016 as well as the changes.
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Figure 13: Detailed Land Cover/ Land Use 2006 structure: presented as Overall, Core City and in Larger
Urban Zone in % (left) and km2 (right)
Figure 14: Detailed Land Cover/ Land Use 2016 structure: presented as Overall, Core City and in Larger
Urban Zone in % (left) and km2 (right)
In the Core Urban Area in both 2006 and 2016 as depicted in Figure 13 and Figure 14 the specific
Residential class of high (50-80%) and very high (80-100%) density and the Industrial, Commercial,
Public class also have significant percentage cover. The next Section will highlight the LU/LC change
information between the two epochs in more detail.
Description of LULC Changes:
In addition to the overall LU/LC classification for the two epochs it is interesting to assess the different
trends between classes over the 10 year time period. The quantitative figures for each class (combined
Core and Peri-Urban) are first provided in Table 4 to get an overview.
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Table 4: Overall LU/LC Statistics 2006 and 2016
LU/LC Classes
2015 2005 Change Change per Year
sqkm % of total
sqkm % of total
sqkm % sqkm %
Residential 0-10 3.83 0.71% 2.52 0.46% 1.31 0.24% 0.13 0.02%
Residential 10-30 11.99 2.21% 15.68 2.90% -3.69 -0.68% -0.37 -0.07%
Residential 30-50 57.10 10.54% 61.11 11.28% -4.00 -0.74% -0.40 -0.07%
Residential 50-80 99.99 18.46% 73.53 13.58% 26.46 4.89% 2.65 0.49%
Residential 80-100 29.64 5.47% 23.11 4.27% 6.53 1.21% 0.65 0.12%
Industrial, Commercial, Public, Military 18.59 3.43% 14.39 2.66% 4.20 0.78% 0.42 0.08%
Arterial Line 2.43 0.45% 2.08 0.38% 0.35 0.06% 0.03 0.01%
Collector Line 3.41 0.63% 3.40 0.63% 0.01 0.00% 0.00 0.00%
Port 0.39 0.07% 0.35 0.07% 0.04 0.01% 0.00 0.00%
Airport 2.34 0.43% 2.34 0.43% 0.00 0.00% 0.00 0.00%
Mining Area 0.27 0.05% 0.27 0.05% 0.00 0.00% 0.00 0.00%
Construction Site 0.27 0.05% 0.18 0.03% 0.09 0.02% 0.01 0.00%
Open Space 0.88 0.16% 0.48 0.09% 0.40 0.07% 0.04 0.01%
Urban Park 0.71 0.13% 0.66 0.12% 0.05 0.01% 0.00 0.00%
Cemeteries 0.10 0.02% 0.10 0.02% 0.00 0.00% 0.00 0.00%
Sport Facilities 0.66 0.12% 0.52 0.10% 0.15 0.03% 0.01 0.00%
Agricultural Area 170.67 31.52% 211.02 38.97% -40.36 -7.45% -4.04 -0.75%
Forest 56.56 10.44% 43.46 8.03% 13.10 2.42% 1.31 0.24%
Fisheries 0.60 0.11% 0.79 0.15% -0.18 -0.03% -0.02 0.00%
Grassland and Shrubs 5.41 1.00% 9.07 1.67% -3.65 -0.67% -0.37 -0.07%
Bare Soil 0.31 0.06% 0.87 0.16% -0.56 -0.10% -0.06 -0.01%
Mangroves 10.98 2.03% 10.92 2.02% 0.06 0.01% 0.01 0.00%
Beach 1.39 0.26% 1.37 0.25% 0.01 0.00% 0.00 0.00%
Peat, Wetlands, Swamps 0.76 0.14% 0.62 0.11% 0.14 0.03% 0.01 0.00%
Water 62.23 11.49% 62.67 11.57% -0.44 -0.08% -0.04 -0.01%
Total 541.52 100.00% 541.52 100.00%
The area statistics of the LU/LC classes show a lot of change dynamics within the residential density
classes. For example it can be noted that there are losses of area in the lower density classes (10-30%,
30-50%) and increases of area in the very low (0-10%) and higher (50-80%, 80-100%) density
residential classes as well in the class Industrial, Commercial, Public, and Military. Furthermore there
is an overall decrease in the agricultural areas and an increase in forested area which can be attributed
to development of plantations.
4.2.1 Spatial Distribution of Main LU/LC Change Categories
In order to better analyse the growth trend and the spatial distribution of changes meaningful
aggregations of the LU/LC classes in both epochs were used. The following categories were developed:
Urban Densification: Changes from lower Residential Density class into higher Residential
Density class
Urban Residential Extension: all changes from non-urban Residential classes to Residential
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Other Urban Land Use Extension: all changes from non-residential urban classes to other urban
and non-urban classes
Changes within Natural and Semi-Natural Areas
The overlay analysis of these aggregated categories of the epochs 2006 and 2016 is depicted in Figure
15.
Figure 15: Spatial Distribution of Land Cover and Land Use Change Types from 2006 to 2016
The spatial distribution of the change types as depicted in Figure 15 shows that the densification of the
Residential areas in the 10 year period, mainly happened in the peripheral areas of the urban Core area
(western and southern regions) and in the surrounding Peri-Urban Area in the west and south with a bit
in the north. There is notable Urban Residential Extension in the Core Urban Area in all regions except
the very central part; the in the Peri-Urban Area the Urban Residential Extension is notable in the south
Peninsula and in the west. The statistics of the Change categories are presented in Figure 16 and Table
5. The statistics in Figure 16 provide a quantitative aspects to the LU change classes; for example it’s
interesting to note that Urban Densification was dominant (49%) in the Peri-Urban zone whereas in the
Core City the class of Residential Extension was the dominant LU change class (47%).
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Figure 16: Land Cover Land Use Change Types 2006-2016: presented as Overall, Core City and in Larger
Urban Zone in % (left) and km2 (right)
The class of Urban Densification, i.e. changes from lower to higher Residential Density has the highest
amount of overall change in the Overall with 48.22 %. The amount of densification was slightly higher
in the Peri-Urban zone with 48.86% compared to the densification in the Core City with 46.89%. The
second largest block of changes can be observed with the classes Residential Extension as well as urban
Land Use into non-urban LU/LC classes. These changes occurred mainly in the Core Urban Area. The
quantitative data is given in Table 5.
Table 5: Statistics of change categories
Change Classes Change Overall Change Core City Change Larger Urban Zone
km² % km² % km² %
Urban Densification 45.30 48.22% 14.41 46.89% 30.89 48.86%
Urban Residential Extension 27.96 29.76% 9.58 31.17% 18.38 29.07%
Other Urban Land Use Extension 4.54 4.83% 4.17 13.57% 0.37 0.59%
Change within Natural and Semi-Natural Areas 16.15 17.19% 2.57 8.37% 13.58 21.48%
Total 93.96 100.00% 30.73 100.00% 63.23 100.00%
4.2.2 Changes of Agricultural Areas
In order to analyse the relatively large loss of Agricultural areas as noted in the earlier part of Section
4.2, a further change analysis was performed. The following change categories were developed for this
analysis:
Agriculture to Residential area
Agriculture to Industry, Commercial; Public or Military area
Agriculture to Plantations
The spatial distribution of these changes are displayed in Figure 17.
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Figure 17: Spatial distribution of changes from Agricultural Areas to other classes between 2006 and 2016
The main overall changes is in the class of Agricultural areas converted to Residential (60%), and
Agricultural areas converted to Forest or Plantation developments. This pattern of land sue change is
reflects in both the Core and Peri-Urban Areas for Denpasar, with the conversion of Agriculture to
residential being the dominant LU change in the Core area (74%). In the Peri-Urban Area the conversion
of Agricultural areas to Forest (Plantation) is quite dominant as well (44%). The converted Agriculture
to Residential occurs all over the Core Urban Area with a concentration in the south-east area. In the
Peri-Urban zone the Agriculture to Residential conversion occurs mainly in the west, and the southern
Peninsula (Bikut) and to a lesser extent in the north. The main areas where Agriculture was converted
to Forest in the Peri-Urban zone is in south Peninsula.
The statistics in Figure 18 and Table 6 show that the majority of Agricultural area has been converted
into Residential area and Plantations in the ten year period between 2006 and 2016.
Table 6: Statistics of changes of Agricultural Areas
Change Classes Change Overall Change Core City Change Larger Urban Zone
km² % km² % km² %
Agricultural Area to Residential 23.18 60.04% 6.65 74.18% 16.53 55.76%
Agricultural Area to Industrial, Commercial, Public
or Military Area 1.62 4.19% 1.61 18.00% 0.00 0.01%
Agricultural Area to Forest 13.81 35.77% 0.70 7.83% 13.11 44.23%
Total 38.61 100.00% 8.97 100.00% 29.65 100.00%
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Figure 18: Changes of Agricultural Areas into other LU classes between 2006 and 2016; presented as
Overall, Core City and in Larger Urban Zone in % (left) and km2 (right)
The next Section summarises the noted changes in the transport network for Denpasar.
4.3 Transport Network
The transport network was created for both points in time (2006 and 2016) using three levels for the
road type classification. The Arterial roads and Collector roads were integrated in the LULC map by
applying a buffer of 12 m for the Arterial roads and a buffer of 8m for the collector roads. Local roads
are only part of the vector data set, which are provided to the user.
Figure 19 depicts the Transport Network for both points in time. The left figure presents the Transport
Network in 2006 and the right figure the Transport Network in 2016. The main changes of the Transport
Network occurred in terms of densification of Local roads in 2016 in the peripheral regions of the Core
Urban Area such as in the north where urban densification has occurred.
Figure 19: Transport Network of Denpasar in 2006 and 2016
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4.4 Flood Risk Assessment
Flood Hazard and Risk Mapping is a vital component of appropriate land use planning in flood-prone
areas. Flood Hazard and Risk Maps are designed to increase awareness of the likelihood of flooding
among the public, local authorities and other organisations, as well as support national disaster
management programmes.
Specific flood regimes and underlying causes for the flooding events in the area of interest have to be
analysed carefully, as these can be very different in different cities. For the Denpasar area generally
short-term local floods and river floods after heavy rainstorms are typical. In Bali, intense precipitation
events happen often between November and March. Areas that are prone to flooding are in most cases
along the rivers: Mati River, Badung River, Sidakarya, and smaller waterways (Gunawan et al. 2015).
According to local sources, flooding also occurs due to the poor quality of drainage and because of the
waste produced by housing and commercial activities not systematically disposed in waste dumps.
Terrain subsidence is to be expected in the future due to excessive groundwater extraction, and load
from buildings and structures but is not confirmed up to now (Abidin et al. 2012)
4.4.1 EO Data Used
In general, there are two types of data available for this purpose: optical and radar data. Available HR
optical data from the sensors Landsat 5, Landsat 7, Landsat 8, ASTER, and Sentinel-2 covering the
period from 1997 to 2017 was downloaded and analysed with regard to regional and/or local flooding.
VHR Imagery was provided by the Project Coordinators, covering the urban area:
Mosaic of Quickbird 20050911 and Quickbird 20060516
Quickbird Image 20170103
These datasets give a good impression of the rapid development and expansion of Denpasar. However,
there was no visual evidence for urban flooding. Additionally, numerous recent VHR images are
available in Google Earth. These images were also visually checked for indications of flooding, but no
flood events could be identified as well.
Radar data from the current European Space Agency (ESA) Sentinel-1 data is acquired constantly and
it is free of charge. The spatial resolution of this data is approximately 10 m. In order to go further back
in time (2002 – 2012), ERS/ENVISAT data could be used. Currently, these datasets are commercially
available, but for the future, there are concrete actions of ESA to make this data available also free of
charge during 2018. Sentinel-1 radar data covering the period from 2015-03-24 to 2017-04-06 (39
datasets) was downloaded and processed with regard to water extent. Flooded areas in the coastal zone
can be extracted but the data tend to give unreliable results in urban environments due to the high number
of low backscattering objects. In Peri-urban regions no relevant flood events were registered by this
data.
The flood risk product is a combination of flood hazard based on Land Use information derived from
the Very High Resolution (VHR) satellite data and thus these datasets are also indirectly used for this
product.
4.4.2 Short Description of Methodological Approach
Historic flood extent mapping
Flood extent mapping based on EO data heavily depends on available datasets as well as on the types of
floods. Whereas there is a good chance to identify large-scale river and coastal floods, normally no
information regarding short-term local floods (flash-floods) can be obtained from EO data due to the
temporal acquisition windows of the satellite systems and/or cloud cover. In some cases short-term local
floods can be recorded and localized based on reports (e.g. in social media) and press releases but such
inventory never will meet the claim to be complete.
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The relevant optical datasets were corrected atmospherically applying the Dark Object Subtraction
(DOS) approach. For defining the water extent in coastal areas the water cover was classified by
applying the Automated Water Extraction Index AWEInsh (Feyisa et al. 2014) which makes use of the
reflectance values of Green, Near Infrared and Shortwave Infrared spectral bands of the Landsat 5,
Landsat 7, Landsat 8, ASTER and Sentinel-2 sensors. The AWEInsh is an index formulated to effectively
eliminate non-water pixels, including dark built surfaces in areas with urban background.
Regarding the occurrence of short-term local floods (flash-floods), point data of reported and localized
urban floods (2009 – 2017) were buffered with 200 m to roughly estimate potential flooding hotspots.
Additionally, the critical sections of the river and waterway network in the lower parts of the catchment
areas (sections where the general slope reduces to less than 3 degrees) were identified. Waterways were
taken from OSM Layer and complemented by visual interpretation of VHR data. After classification in
two classes based on Stream Order, the lines were buffered with 50 m (Stream Order 1 and 2, as defined
by Strahler 1952) and 100 m respectively (Stream Order 3 and 4) to roughly estimate potential flooding
zones.
Furthermore, areas classified as “Flood Zones” were provided by the City of Denpasar. Although there
is no documentation available and no verification possible, these areas were taken into consideration in
the analysis as well.
Flood hazard mapping
The flood hazard map is taking into account all available data sources (EO based water extents, reports
and press releases, results of modelling of potential flooding along rivers and waterways) aiming at
covering all types of floods and thus all areas which are potentially endangered by flooding. The
classification in three qualitative hazard levels is expert-based under consideration of observed and
reported frequencies of floods.
Flood risk mapping
Risk is defined as a combination of probability and consequences. A detailed and uniform land-use map
is an important prerequisite to perform flood risk calculations, since it determines what is damaged in
case of flooding. The original land-use map as provided by EO4SD Urban project was recoded to pre-
defined categories (as given in Table 7) to ensure consistent results.
The exposition is classified following an approach developed by NEO (based on: Dasgupta et al. 2015)
integrating economic costs, social damage, physical damage and flood duration. Four land use damage
levels (A, B, C, D) are defined based on this estimation.
Table 7: Land use classes and reclassification to pre-defined damage levels
Classes Damage Total Level
Economic
Costs
0-2
Social
Damage
0-2
Physical
Damage
0-2
Flood
Duration
0-2
Agricultural Land 1.5 0.5 0 1 3 B
Commercial and Industrial Units 2 0.5 1 0.5 4 B
Dump site 0 1.5 0.5 0 2 A
Construction Sites 1 0.5 0 0 1.5 A
Forests 0.5 0 0 0 0.5 A
Formal high density residential -
Continuous urban fabric
(Sealing level: 50%-100%)
1.5 1.5 2 1.5 6.5 D
Formal low density residential -
Discontinuous urban fabric
(Sealing level: 10%-50%)
1.5 1 2 1 5.5 C
Land Without Current Use, Bare Soil 0 0 0 0 0 A
Mineral Extraction site 1 0 0.5 1 2.5 B
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Classes Damage Total Level
Economic
Costs
0-2
Social
Damage
0-2
Physical
Damage
0-2
Flood
Duration
0-2
Non-Residential Urban Fabric 1 1 0.5 1 3.5 B
Other Natural and Semi-Natural Areas
including Wetlands 0 0 0 0 0 A
Transportation units 1.5 1 2 1.5 6 C
Sports and leisure facilities, Beach 0.5 0.5 0 0.5 1.5 A
Other Urban / Artificial Area 1.5 1.5 1 0.5 4.5 C
Urban Greenery, Cemeteries 0.5 0.5 0.5 1 2.5 B
Village Settlements
(Sealing level 1-10%) 1.5 1.5 0.5 1.5 5 C
Water Bodies, Fisheries 0 0 0 0 0 A
The Flood Risk matrix (see Table 8) is generated based on the above code and Flood Hazard classified
into three hazard levels. The Flood Risk level is classified in four qualitative classes based on the
combination of flood hazard and land use damage.
Table 8: Flood hazard and risk classification (Flood Risk Matrix)
Damage cost on land use
A B C D
Flood Hazard
1 (low) 1A 1B 1C 1D
2 (medium) 2A 2B 2C 2D
3 (high) 3A 3B 3C 3D
Flood Risk classification
Low Risk 1A 1B 2A
Medium Risk 1C 1D 2B 2C 2D 3A 3B
High Risk 2D 3C
Very high Risk 3D
4.4.3 Product Description and Accuracy Assessment
There are three final layers in this product: (1) the raw data on past flood extents as derived from EO
data and ancillary data (flood history), (2) the Flood Hazard map which summarizes past flood events
and thus gives information about the likelihood of future events, and (3) the Flood Risk map combining
this data with information on urban and Peri-urban land use and its damage potential in case of flooding.
The delineation of coastal water extents is based on data from Landsat 8 (acquired on 15/04/2015,
12/01/2016 provided by the US Geological Survey), and Sentinel-2 (acquired on 21/10/2015,
30/12/2015, 06/08/2016, 25/10/2016 provided by the European Space Agency). The evaluation of the
data confirms the results of the Global Surface Water Explorer Product (Joint Research Centre) based
on Landsat Imagery. According to the current analysis and the latter product, no relevant increase of
permanent and seasonal water cover can be observed for the period from 1984 to 2015.
The accuracy assessment of the water extent classification was done based on stratified random
sampling. The following equation is applied to determine the number of points required for an accepted
standard error of the error of commission per class:
n_c=(p_c (1-p_c))/(σ_c^2 ), c = 1,…,L
n_c number of SSUs for category c
p_c estimated error rate for category c
σ_c accepted standard error of the error of commission for category c
L number of categories
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The following values were applied: p_c=0.1, σ_c=0.05, L=2 (Water or No Water)
- => n_c = 36
In Denpasar, the validation extent was limited to the coastal area. The validation was based on the visual
comparison of 72 points (randomly distributed and situated in the coastal lowlands only) on each satellite
image and the respective classification result since no independent reference data were available.
Overall accuracies for the classification range from 90.3% to 97.2%.
The Flood Hazard map (subset see Figure 20) displays flood hazard information (delivered in vector
format). This data is based on the occurrence of floods of the past 10 years. It takes into account both
the hazard from tidal floods in coastal areas as well as from short-term local floods after heavy
rainstorms in urban areas. The classification in three qualitative hazard levels is expert-based under
consideration of reported frequencies of floods.
Since no independent reference data are available no accuracy assessment is possible. The plausibility
of the results nevertheless was evaluated on basis of local reports and press releases.
The Flood Risk Map (subset see Figure 21) displays flood risk information (delivered in vector format).
This data is based on the occurrence of floods of the past 10 years combined with information of the
land use map provided by EO4SD Urban project. It takes into account both the hazard level and potential
damages, based on different land uses. The damages are assessed on 4 aspects: economic, social,
physical and flood duration.
Since this product is a direct derivation and combination of the Hazard Classification and the Land Use
Classification, its plausibility can be rated high when the mentioned input datasets are rated as being
plausible and reliable.
Figure 20: Subset of Flood Hazard Map of Denpasar (Downtown area) (Image: Quickbird 2017/01/03)
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Figure 21: Subset of Flood Risk Map of Denpasar (Downtown area) (Image: Quickbird 2017/01/03)
4.4.4 Results
With regard to the total calculated Flood Hazard zones it can be observed that the proportion of the total
affected area is significantly higher in Denpasar Core City than in the Peri-urban region: more than 16%
vs. approx. 9%. The proportion of medium and high hazard zones is significantly higher as well (cf.
Figure 22).
Figure 22: Proportion of Flood Hazard Zones in Denpasar urban (left) and peri-urban region (right)
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As the extension of Flood Risk zones is equal to that of Hazard Zones this results in a similar picture.
The medium, high and very high risk categories occur disproportionately high in the Core City
(approximately 11% vs. 3% in the Peri-urban region, cf. Figure 23).
Figure 23: Proportion of Flood Risk Zones in Denpasar urban (left) and Peri-urban region (right)
Selected land use categories and groups of land use categories were analysed more detailed both in the
urban and in the Peri-urban area regarding their position in hazardous zones:
Residential and public urban fabric: public buildings, business district, education facilities,
health facilities, residential area
Transportation units: airport, arterial lines, collector lines
Construction sites
Commercial and industrial units
Agricultural land
Semi-natural and natural area: forests, grasslands and shrubs
The analysis of Residential and Public Urban Fabric shows that more than 6% of such Land Use is
situated in medium and high hazard zones in the urban region (Figure 24). Including the low hazard
areas in the analysis, a total of 16% of Residential and Public Urban Fabric is located in the calculated
hazard zones.
In the peri-urban region, the proportion of Residential and Public Urban Fabric located in the calculated
hazard zones is significantly lower with a total of 7.7%, most of it situated in low hazard zones.
Figure 24: Proportion of Residential and Public Urban Fabric in flood prone areas (high/medium/low/no
hazard) – in Denpasar urban (left) and Peri-urban region (right)
Focusing on the risk aspect, the applied methodology implies that no low Flood Risk zones can exist in
the Residential and Public Urban Fabric class (cf. Section 4.2.2 and Table 7 and 8). Figure 25 displays
the proportions of Residential and Public Urban Fabric in the medium, high, and very high Flood Risk
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zones. As expected, the proportions of the high and very high Flood Risk zones are significantly higher
in the Core City.
Figure 25: Proportion of Residential and Public Urban Fabric in Flood Risk areas (very
high/high/medium/no risk) – in Denpasar urban (left) and Peri-urban region (right)
Figure 26: Map of Residential and Public Urban Fabric combined with Flood Risk Zoning in the centre of
Denpasar (Image: Quickbird 20170103)
The analysis of high-ranking infrastructure (airport, arterial lines, collector lines) reveals that the western
part of the airport is situated in a Peri-urban area classified as flood prone (low hazard). Moreover, many
main transport lines in the Peri-urban area are situated in coastal zones classified as flood prone. This
results in significantly higher percentages of high-ranking infrastructure in flood prone areas (most of it
classified as low hazard zones) for the Peri-urban region (approximately 32% versus 12% for the Core
City, cf. Figure 27).
Regarding the Flood Risk classification, most of the involved transportation units can be found in the
medium risk class (cf. Figure 27).
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Figure 27: Proportion of high-ranking infrastructure in flood prone areas (high/medium/low/no hazard) –
in Denpasar urban (left) and Peri-urban region (right)
Figure 28: Proportion of high-ranking infrastructure in Flood Risk areas (high/medium/no risk) – in
Denpasar urban (left) and Peri-urban region (right)
The results of the analysis of the land use categories Construction Sites, Commercial and Industrial
Units, Agricultural Land, and Semi-Natural and Natural Area are displayed in Figure 29 to Figure 32.
Figure 29: Proportion of Construction Sites in flood prone areas (low/no hazard) – in Denpasar Core City
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Figure 30: Proportion of Commercial and Industrial units in flood prone areas (high/medium/low/no
hazard) – in Denpasar Core City
Figure 31: Proportion of Agricultural Land in flood prone areas (high/medium/low/no hazard) – in
Denpasar urban (left) and Peri-urban region (right)
Figure 32: Proportion of Natural and Semi-Natural Areas in flood prone areas (high/medium/low/no
hazard) – in Denpasar urban (left) and Peri-urban region (right)
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5 References
Abidin, H.Z., Andreas, H., Gumilar, I., Sidiq, T.P. & Fukuda, Y. (2012): On the Roles of Geospatial
Information for Risk Assessment of Land Subsidence in Urban Areas of Indonesia.-The 8th
International Conference on Geo‐information for Disaster Management, 13‐14 December, 2012,
Enschede, The Netherlands.
Czaplewski, R. L. (2003). Chapter 5: accuracy assessment of maps of forest condition: statistical design
and methodological considerations, pp. 115–140. In Michael A. Wulder, & Steven E. Franklin (Eds.),
Remote sensing of forest environments: concepts and case studies. Boston: Kluwer Academic Publishers
(515 pp.).
Dasgupta, S., Asif, Z., Subhendu, R., Mainul, H., Sarwar, J. & Ainun, N. (2015): Urban Flooding of
Greater Dhaka in a Changing Climate: Building Local Resilience to Disaster Risk. Directions in
Development. Washington, DC: World Bank. doi:10.1596/978-1-4648-0710-7. License: Creative
Commons Attribution CC BY 3.0 IGO
European Union (2011). Mapping Guide for a European Urban Atlas, Version 11.0
European Union (2013). INSPIRE Metadata Implementing Rules: Technical Guidelines
Feyisa, L.G., Meilby, H., Fensholt, R. & Proud, S.R. (2014): Automated Water Extraction Index: A new
technique for surface water mapping using Landsat imagery.- Remote Sens. Environ, 140 (2014), pp.
23-35.
Gunawan, I., Sagala, S., Amin, S., Zawani, H. & Mangunsong, R. (2015): City Risk Diagnostic for
urban Resilience.-World Bank.
Olofsson, P., Foody, G. M., Stehman, S. V., & Woodcock, C. E. (2013). Making better use of accuracy
data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified
estimation. Remote Sensing of Environment, 129, 122–131. doi:10.1016/j.rse.2012.10.031
RTRW (2011). RTRW Denpasar City Year 2011-2031, Denpasar, Indonesia (English translated
version)
Selkowitz, D. J., & Stehman, S. V. (2011). Thematic accuracy of the National Land Cover Database
(NLCD) 2001 land cover for Alaska. Remote Sensing of Environment, 115(6), 1401–1407.
doi:10.1016/j.rse.2011.01.020.
Strahler, A. N. (1952): "Dynamic basis of geomorphology". Geological Society of America Bulletin 63:
pp. 923–938.
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Annex 1 – Land Use and Land Cover Nomenclature and Definitions
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Nomenclature according to User Requirements, including definitions from a Remote Sensing perspective.
Level and
Land Use Class Sub-Classes Definition
1.1 Residential
- Very High Density
- High Density
- Medium Density
- Low Density
- Super Low
Density
Built-up areas and their associated land, such as gardens, parks, planted areas
and non-surfaced public areas and the infrastructure, if these areas are not
suitable to be mapped separately with regard to the minimum mapping unit
size.
Very High: Average degree of soil sealing: 80 -100% Residential buildings,
roads and other artificially surfaced areas.
High: Average degree of soil sealing: 50 - 80% Residential buildings, roads
and other artificially surfaced areas.
Medium: Average degree of soil sealing: 30 - 50% Residential buildings,
roads and other artificially surfaced areas. The vegetated areas are
predominant, but the land is not dedicated to forestry or agriculture.
Low: Average degree of soil sealing: 10 - 30% Residential buildings, roads
and other artificially surfaced areas. The vegetated areas are predominant, but
the land is not dedicated to forestry or agriculture.
Super Low: Average degree of soil sealing: <10 % Residential buildings,
roads and other artificially surfaced areas. The vegetated areas are
predominant, but the land is not dedicated to forestry or agriculture. Example:
exclusive residential areas with large gardens.
1.2.1. Industrial,
Commercial,
Public, Military
and Private Units
- Commercial Area
- Industrial Area
- Education
Facilities
- Business District
(Government,
Offices)
- Military
- Public Building
Factories, warehouses, CBD, shopping malls, markets, other commercial
facilities, Schools and University and associated land, Government, Offices.
military and associated land, “Big” public buildings like churches, bibliotheca,
…
(Distinction depends strongly on availability of ancillary data)
1.2.2 Roads - Arterial Road
- Toll Line
- Collector Road
Transportation units such as roads with a minimum width of 4 m (Collector
Road) and 6 m (Arterial Road).
1.2.3 Railway Railway facilities including stations, cargo stations and associated land.
1.2.4 Port Infrastructure of port areas, including quays, dockyards, transport and storage
areas and associated area.
1.2.5 Airport Administrative area of airports, mostly fenced.
Included are all airport installations: runways, buildings and associated land.
1.3.1 Mineral
extraction and
dump sites
- Mining Area
- Landfill
Open pit extraction sites; public, industrial or mine dump sites.
1.3.2 Construction
Sites
Spaces under construction or development. Clear evidence of actual
construction needs to be identifiable in the data.
1.3.3 Open Space Areas in the vicinity of artificial surfaces still waiting to be used or re-used. No
actual agriculture or recreational use.
1.4.1 Urban Green
Space
- Urban Parks
- Parks
- Public Gardens
- Cemeteries
Urban Parks, Parks, Public Gardens:
Public green areas for predominantly recreational use such as gardens, zoos,
parks, castle parks.
Suburban natural areas that have become and are managed as urban parks.
Forests or green areas extending from the surroundings into urban areas are
mapped as green urban areas when at least two sides are bordered by urban
areas and structures, and traces of recreational use are visible.
1.4.2 Sport
Facilities
All sports and leisure facilities including associated land, whether public or
commercially managed:
Golf courses, Sports fields (also outside the settlement area), Camp grounds,
Riding grounds, Racecourses, Amusement parks, Swimming resorts etc.,
Glider or sports airports.
2. Agricultural
Area
Cultivated areas non-irrigated or permanently irrigated including rice fields:
arable land (annual crops), permanent crops, complex or mixed cultivation,
orchards; pasture and meadow under agricultural use, grazed or mechanically
harvested.
3.1 Forest High woody vegetation in natural forests; transitional woodland; low
vegetation cover with bushes and shrubs.
3.2 Fisheries Fishery Areas
3.3 Grassland and
Shrubs
Natural area where there is low to medium high vegetation
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 1 to EO4SD-Urban Denpasar City Operations Report Page 4
3.4 Bare Soil Bares Soil Areas (not within the urban area)
3.5 Mangroves Areas where the Mangrove Ecosystem occurs
3.6 Beach Beaches including small commercial facilities like restaurants.
4. Wetlands Areas flooded or liable to flooding during a large part of the year by fresh,
brackish or standing water with specific vegetation coverage made of low
shrub, semi-ligneous or herbaceous species; shallow water areas covered with
reed.
5. Water Visible water areas like lakes, rivers, ponds (natural, artificial).
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 1
Annex 2 – Processing Methods for EO4SD-Urban Products
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 2
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Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 3
Summary of Processing Methods
Urban and Peri-Urban Land Use/Land Cover and Change
The input includes Very High Spatial Resolution (VHR) imagery from different sensors acquired at
different time. The data is pre-processed to ensure a high level of geometric and radiometric quality
(ortho-rectification, radiometric calibration, pan-sharpening).
The complexity when dealing with VHR images comes from the internal variability of the information
for a single land-use. For instance, an urban area is represented by a high number of heterogeneous pixel
values hampering the use of automated pixel-based classification techniques.
For these VHR images, it is possible to identify textures (or pattern) inside an entity such as an
agricultural parcel or an urban lot. In other words, whereas pixel-based techniques focus on the local
information of each single pixel (including intensity / DN value), texture analysis provides global
information in a group of neighbouring pixels (including distribution of a group intensity / DN values
but also spatial arrangement of these values). Texture and spectral information are combined with a
segmentation algorithm in an Object Based Image Analysis (OBIA) approach to reach a high degree of
automation for most of the Peri-Urban rural classes. However, within urban land, land use information
is often difficult to obtain from the imagery alone and ancillary/in situ data needs to be used. The
heterogeneity and format of these data mean that another information extraction method based on
Computer Aided Photo-Interpretation techniques (CAPI) need to be used to fully characterise the LULC
classes in urban areas. Therefore, a mix of automated (OBIA) and CAPI are used to optimise the
cost/quality ratio for the production of the LULC/LUCC product. The output format is typically in vector
form which makes it easier for integration in a GIS and for subsequent analysis.
Level 4 of the nomenclature can be obtained based on additional information. These can be generated
by more detailed CAPI (e.g. identification of waste sites) or by an automated approach based on
derived/additional products. An example is illustration by categorising the density of the urban fabric
which is related to population density and can then subsequently used for disaggregating population
data.
Information on urban fabric density can be obtained through several manners with increasing level of
complexity. The Imperviousness Degree (IMD) or Soil Sealing (SL) layer (see separate product) can be
produced relatively easily based on the urban extent derived from the LULC product and a linear model
between imperviousness areas and vegetation vigour that can be obtained from Sentinel 2 or equivalent
NDVI time series. This additional layer can be used to identify continuous and discontinuous urban
fabric classes. Five urban fabric classes can be extracted based on a fully automated procedure:
Continuous urban fabric (IMD > 80%)
Discontinuous dense urban fabric: (IMD 50-80 %)
Discontinuous medium density urban fabric (IMD: 30-50 %)
Discontinuous low density urban fabric (IMD 10-30 %)
Discontinuous very low density urban fabric (IMD < 10 %)
Manual enhancement is the final post-processing step of the production framework. It will aim to
validate the detected classes and adjust classes’ polygon geometry if necessary to ensure that the correct
MMU is applied. Finally, a thorough completeness and logical consistency check is applied to ensure
the topological integrity and coherence of the product.
Change detection: Four important aspects have to be considered to monitor land use/land cover change
effectively with remote sensing images: (1) detecting that changes have occurred, (2) identifying the
nature of the change, (3) characterising the areal extent of the change and (4) assessing the spatial pattern
of the change.
The change detection layer can be derived based on an image-to-image approach provided the same
sensor is used. An original and efficient image processing chain is promoted to compare two dates’
images and provide multi-labelled changes. The approach mainly relies on texture analysis, which has
the benefits to deal easily with heterogeneous data and VHR images. The applied change mapping
approach is based on spectral information of both dates’ images and more accurate than a map-to-map
comparison.
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 4
Summary of Processing Methods
Urban Extent and Change
Reliably outlining urban areas is of high importance since an accurate characterization of the urban
extent is fundamental for accurately estimating, among others, the population distribution, the use of
resources (e.g., soil, energy, water, materials), infrastructure and transport needs, socioeconomic
development, human health and food security. Moreover, monitoring the change in the extent of urban
areas over time is of great support for properly modelling the spatial-temporal patterns of urbanisation
evolution and, thus, better estimating future trends and implementing suitable planning strategies.
The product is a binary mask outlining in the area of interest the urban areas (intended as built-up
structures) with respect to all other land-cover classes merged together into a single information class.
The urban class and the non-urban class are associated with value “255” and “0”, respectively.
Regrouping of relevant LULC thematic classes can be used to depict urban extent precisely. Instead, if
a detailed LULC product is not available for the selected study region, then the information will be
derived by the following approach.
The product is generated at 30 m spatial resolution by properly exploiting Landsat-4/5/7/8 multi-
temporal imagery acquired over the Peri-Urban and urban area within a given time interval of interest
in which no relevant changes are expected to occur (typically a time period of 1-2 years allows to obtain
very accurate results). For all the considered scenes, cloud masking and, optionally, atmospheric
correction are performed. Next, a series of features specifically suitable for delineating urban areas are
derived for each image. These include both spectral indexes (e.g., the normalized different vegetation
index (NDVI), the atmospherically resistant vegetation index (ARVI), the normalized difference water
index (NDWI), etc.) and texture features (e.g., occurrence textures, co-occurrence texture, local
coefficient of variation, etc.). The core idea is then to compute per each pixel key temporal statistics for
all the extracted features, like temporal maximum, minimum, mean, variance, median, etc. This allows
compressing all the information contained in the different multi-temporal acquisitions, but at the same
time to easily and effectively characterize the underlying dynamics. It is worth noting that for different
pixels in the study area, different number of scenes might be available. However, in the hypothesis of a
sufficient minimum number of acquisitions for computing consistent statistics, this does not represent
an issue. Moreover, in this framework it is also possible to obtain spatially consistent datasets to be
employed for the desired analyses even when investigating large areas. Training data for the urban and
non-urban class are then extracted by employing a strategy based on the analysis of the DLR Global
Urban Footprint (GUF) layer (which varies depending whether the target period of interest refers to a
time interval before or after that which the GUF refers to). Afterwards, a Support Vector Machines
(SVM) classifier is employed where a Radial Basis Function (RBF) kernel is used.
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 5
Summary of Processing Methods
Flood Risk Assessment
In order to generate the Flood Risk product, several processing steps are needed, which are shown in the
graph below. These processing steps generally lead to three sub-products: (1) Historic flood extent
products; (2) Flood hazard product and (3) Flood risk product.
Historic flood extent mapping
Flood extent mapping based on EO data heavily depends on available data sets. This depends on cloud-
free weather conditions as well as on types of floods in focus. Whereas there is a good chance to identify
large-scale river and coastal floods, normally no information regarding short-term local floods (flash-
floods) can be obtained from EO data due to short duration. In some cases short-term local floods can
be recorded and localized based on reports (e.g. in social media) and press releases but such inventory
never will meet the claim to be complete.
The relevant EO optical datasets were atmospherically corrected. For defining the extent of tidal floods
in coastal areas the water cover was classified by applying a water index such as for example the
Normalized Difference Water Index (NDWI) or the Automated Water Extraction Index AWEInsh
(Feyisa et al. 2014) which makes use of the reflectance values of Green, Near Infrared and Shortwave
Infrared spectral bands of the Landsat 5, Landsat 7, Landsat 8, ASTER and Sentinel-2 sensors. The
index is used to effectively eliminate non-water pixels, including dark built surfaces in areas with urban
background.
Additionally, to overcome the drawback of missing significant EO data in the urban area, the usability
of the Hazard Component of the “Tidal Floods Risk Online Map” (Nugraha et al. 2015,
http://geodesi.undip.ac.id/gis/) was verified. The plausibility verification was based on available reports
and press releases and resulted in the decision to include this data in the hazard assessment. Regarding
the occurrence of short-term local floods (flash-floods) point data of reported and localized urban floods
(2009 – 2017) were buffered with 200 m to roughly estimate potential flooding hotspots. Additionally
the critical sections of the river and waterway network in the lower parts of the catchment areas (sections
where the general slope reduces to less than 3 degrees) were identified. Waterways were taken from
OSM Layer and complemented by hydrologic modelling of potential catchment areas and flow routes
based on the combined ALOS-SRTM DEM and visual interpretation of VHR data. After classification
in two classes based on Stream Order the lines were buffered with 50 m (Stream Order 1 and 2, as
defined by Strahler 1952) and 100 m respectively (Stream Order 3 and 4) to roughly estimate potential
flooding zones. If available, local maps and data from the cities were also included.
Flood hazard mapping
The flood hazard map is taking into account all available data sources (EO based flood extents, reports
and press releases, results of modelling of potential flooding along rivers and waterways, ancillary data
– online tidal flooding map) aiming at covering all types of floods and thus all areas which are potentially
Review of occurring flood regimes
Review existing
flood data (EO and
non EO)
Localization of non-
EO data
Processing of EO data
Pre-processing
Flood classification
Flood
history
products
Flood
hazard
Flood
Risk
Land Use
Map
Subsidenc
e map (if
existing)
Existing
maps
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 2 to EO4SD-Urban Denpasar City Operations Report Page 6
endangered by flooding. Where available, a ten years period of EO data was used. The classification in
three qualitative hazard levels is expert-based under consideration of observed and reported frequencies
of floods. In principle, higher frequency means higher hazard. In case of occurrence and availability,
results of recent InSAR subsidence calculation were also taken into account, as for example done in the
city of Semarang.
Flood risk mapping
Risk is defined as a combination of probability and consequences. Probability follows from the flood
hazard product. Consequences were determined by damage assessment based on the land-use map. A
detailed and uniform land-use map is therefore an important prerequisite to perform flood risk
calculations, since it determines what is damaged in case of flooding. The original land-use map was
recoded to pre-defined categories to ensure consistent results.
The exposition is classified following an approach developed by NEO (based on: Dasgupta et al. 2015)
integrating economic costs, social damage, physical damage and flood duration. Four damage levels (A,
B, C, D) are defined based on this estimation. Flood risk follows from the combination of flood hazard
level and damage level.
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 3 to EO4SD-Urban Denpasar City Operations Report Page 1
Annex 3 – Filled Quality Control Sheets
Urban Land Use / Land Cover
Flood Risk Assessment
Earth Observation for Sustainable Doc. No.: City-Operations Report
Development – Urban Project Issue/Rev-No.: 1.1
Annex 3 to EO4SD-Urban Denpasar City Operations Report Page 2
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Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 1
Earth Observation for Sustainable Development - Urban
Quality Assurance and Quality Control Sheets These QA/QC Templates were prepared by GAF AG compliant with ISO 9001:2008 Quality Management System
standards and can only be used by Partners in the current EO4SD-Urban Project.
Project Title: EO4SD-Urban
Project Leader: GAF AG
Service Provider: GAF AG
Client: WB Editor: AB; FE
Product: Urban Land Use/ Land Cover Date: 30.08.2017
Overview of QC-Sheets and Processing Steps Sheet
used Sheet filled in
Requirements
0.1 Requirements Yes Yes
Specifications of Input Data
1.1 List of EO Data Yes Yes
1.2 List of In-situ Data Yes Yes
1.3 List of Ancillary Data Yes Yes
Data Quality Checks
2.1 EO Data Quality Yes Yes
2.2 In-situ Data Quality Yes Yes
2.3 Ancillary Data Quality Yes Yes
Pre-Processing of EO Data
3.1 Geometric Correction Yes Yes
3.1.1 Data Fusion Yes Yes
3.2 Data Processing Yes Yes
Thematic Processing
4.1 Classification Yes Yes
4.2 Intermediate Quality Control of Land Use Data Yes Yes
Accuracy Assessment
5.1 Thematic Accuracy Yes Yes
5.2 Error Matrices Yes Yes
Delivery Checks / Delivery
6.1 Completeness Yes Yes
6.2 Compliancy Yes Yes
Glossary (index numbers in the QA/QC tables refer to the glossary at the end of this document)
Further QC-relevant Documents:
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 2
Comments / Characteristics:
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 3
0.1 Requirements
Product 1 (28) Urban Land Use/ Land Cover Status 2006 and 2016
Abstract
The Land Use/Land Cover (LU/LC) product contains spatial explicit information on the different
occurring land use and land cover in both the Core and Peri-Urban areas of the City of Denpasar for the
years 2006 and 2016. The Core area has detailed LU/LC nomenclature whereas the Peri-Urban area
LU/LC nomenclature is at an aggregated Level. The input data for the Core area was the Very High
Resolution data (WorldView-2 for 2017, Quickbird-2 for 2005, 2006 ) and the input data for the Peri-
Urban area was Sentinel (2017) and Landsat-7 (2000, 2002) data. The LU/LC product is the Baseline
Product from which various derived products (such as Green Areas and Informal Settlements) are
produced.
Service / Product Specifications
Area Coverage
Country: Indonesia A) Wall-to-wall: yes
City: Denpasar Selected Sites: Core-Urban and Peri-Urban
Area km² Core Urban: 132 B) Sampling based: n.a.
Peri-Urban: 409
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
2006 and 2016 2 points in time, no future update
Comments: None
Geographic Reference System
EPSG: 32749. WGS 84 / UTM zone 50S
Mapping Classes and Definitions
Residential
Built-up areas and their associated land, such as gardens, parks, planted areas and non-
surfaced public areas and the infrastructure, if these areas are not suitable to be mapped
separately with regard to the minimum mapping unit size.
Very High: Average degree of soil sealing: 80 -100% Residential buildings, roads and other
artificially surfaced areas.
High: Average degree of soil sealing: > 50 - 80% Residential buildings, roads and other
artificially surfaced areas.
Medium: Average degree of soil sealing: > 30 - 50% Residential buildings, roads and other
artificially surfaced areas. The vegetated areas are predominant, but the land is not
dedicated to forestry or agriculture.
Low: Average degree of soil sealing: 10 - 30% Residential buildings, roads and other
artificially surfaced areas. The vegetated areas are predominant, but the land is not
dedicated to forestry or agriculture.
Super Low: Average degree of soil sealing: <10 % Residential buildings, roads and other
artificially surfaced areas. The vegetated areas are predominant, but the land is not
dedicated to forestry or agriculture. Example: exclusive residential areas with large gardens.
Commercial Area* Warehouses, Central Business Districts (CBD), shopping malls, markets, other commercial
facilities.
Industrial Area* Factories and associated land
Business District* Government, Offices.
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Development – Urban Project QA/QC Sheets developed by GAF AG
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
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Page 4
Education Facilities* Schools and Universities and associated land (including sport fields)
Military* Military and associated land
Health Facilities* Hospitals and associated land
Public Buildings* “Big” public buildings like churches, bibliotheca, …
Arterial Line Highways, connecting the city with other cities
Toll Road Public or private roadway for which a fee is assessed for passage.
Collector Line Bigger Connecting roads within the city
Railway Railway facilities including stations, cargo stations and associated land.
Port Port and associated area.
Airport
Administrative area of airports, mostly fenced. Included are all airport installations: runways,
buildings and associated land.
Mining Area
Open pit extraction sites (sand, quarries) including water surface, if <Minimum Mapping Unit
(MMU), open-cast mines, inland salinas, oil and gas fields;
Landfill Dump sites and associated land
Construction Site
Spaces under construction or development, soil or bedrock excavations for construction
purposes or other earthworks visible in the image.
Open Space
Areas in the vicinity of artificial surfaces still waiting to be used or re-used. The area is
obviously in a transitional position, “waiting to be used”.
Waste land, removed former industry areas, (“brown fields”) gaps in between new
construction areas or leftover land in the urban context (“green fields”).
No actual agricultural or recreational use. No construction is visible, without maintenance, but
no undisturbed fully natural or semi-natural vegetation (secondary ruderal vegetation).
Urban Parks
Public green areas for predominantly recreational use such as gardens, zoos, parks, castle
parks.
Suburban natural areas that have become and are managed as urban parks.
Forests or green areas extending from the surroundings into urban areas are mapped as
green urban areas when at least two sides are bordered by urban areas and structures, and
traces of recreational use are visible.
Cemeteries Cemeteries and associated area
Sport Facilities
All sports and leisure facilities including associated land, whether public or commercially
managed: Golf courses, Sports fields (also outside the settlement area), Camp grounds,
Riding grounds, Racecourses, Amusement parks, Swimming resorts etc., Glider or sports
airports.
Agricultural Area
Cultivated areas non-irrigated or permanently irrigated including rice fields: arable land
(annual crops), permanent crops, complex or mixed cultivation, orchards; pasture and
meadow under agricultural use, grazed or mechanically harvested.
Forest
High woody vegetation in natural forests; transitional woodland; low thickets. Includes
Plantations
Fisheries Fishery Areas
Grassland and Shrubs Natural area where there is little vegetation
Bare Soil Bare Soil Areas (not within the urban area)
Mangroves Areas where the Mangrove Ecosystem occurs
Beach Beaches including small commercial facilities like restaurants.
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Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 5
Peat_Wetlands_Swamps
Areas flooded or liable to flooding during a large part of the year by fresh, brackish or
standing water with specific vegetation coverage made of low shrub, semi-ligneous or
herbaceous species; shallow water areas covered with reed.
Water Visible water areas like lakes, rivers, ponds (natural, artificial).
Comment:
* These classes have only to be mapped in 2015. For the mapping of the historic land cover
these classes were merged to the class Commercial, Public, Military and Private Units.
Cloud and Cloud Shadow Detection and Removal
Information for the entire AOI is required and therefore clouded areas have to replace by other Earth Observation
(EO) data.
Spatial Resolution
n.a. (Product provided as Shapefile)
Minimum Mapping Unit (MMU)
Minimum Mapping Unit within urban core area is 0.25 ha. Peri-urban area is mapped with a MMU of 0.5 ha
Data Type & Format
Shapefile *.shp and GeoPDF
Bit Depth
n.a.
Class Coding
Class Code Class Name RGB Code [R; G; B]
1100 Residential 255; 0; 0 (main class only)
1211 Commercial Area 197; 0; 255
1212 Industrial Area 132; 0; 168
1213 Business District 0; 255; 197
1214 Education Facilities 232; 190; 255
1215 Military 115; 115; 0
1216 Health Facilities 115; 223; 255
1217 Public Buildings 192; 252; 234
1221 Arterial Line 78; 78; 78
1222 Toll Road 100; 100; 100
1223 Collector Line 120; 120; 120
1230 Railway 52; 52; 52
1240 Port 0; 168; 132
1250 Airport 168; 0; 132
1311 Mining Area 115; 76; 0
1312 Landfill 190; 232; 255
1320 Construction site 255; 115; 223
1330 Open space 242; 242; 242
1411 Urban Parks (Urban Green Spaces) 85; 255; 0
1412 Cemeteries 230; 230; 0
1420 Sport Facilities 255; 170; 0
2000 Agricultural Area 255; 235; 175
3100 Forest 38; 115; 0
3200 Fisheries 158; 170; 215
3300 Grassland and Shrubs 180; 215; 158
3400 Bare Soil 204; 204; 204
3500 Mangroves 185; 255; 150
3600 Beach 255; 255; 0
4000 Peat_Wetlands_Swamps 76; 0; 115
5000 Water 0; 112; 255
Metadata
Provided as INSPIRE conformant *xml data set, covering at least the mandatory elements.
Service / Product Quality
Thematic Accuracy
Overall Accuracy: >80%
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Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 6
Positional Accuracy
RMSE < 30 m.
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
End of August 2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 7
1.1 List of EO Data
Sensoren (8) Sentinel-2, Landsat 7, WV-2, QB-
2 Incoming
Date
Acquisit
ion
Date
Proc.
Level
Path /
Row
AOI - City
/ Region
/ Country
Spatial Res. No. of
Bands
Cloud
Cover
(Data
Provid
er)
Projectio
n /
Spheroid (16)
Data
Forma
t (3)
Bit
Depth (5)
Head
er /
Meta
data (2)
File Name [e.g yymmdd; tbd...]
Sentinel-2
1. S2A_OPER_MSI_L1C_TL_SGS__20160607T
091621_A005005_T50LKR
23.03.20
17
07.06.2
016 1C
50/L
KR
Denpasar
, IND 10m 4 1.1%
WGS 84
/ UTM
zone
50S
.tiff 16
Bit .xml
2. S2A_OPER_MSI_L1C_TL_SGS__20160607T
091621_A005005_T50LLR_N02.02
23.03.20
17
07.06.2
016 1C
50/LL
R
Denpasar
, IND 10m 4 1.2%
WGS 84
/ UTM
zone
50S
.tiff 16
Bit .xml
Landsat-7
3. LE07_L1TP_116066_20001209_2017020
8_01_T1
08.02.20
17
09.12.2
000 L1TP
116/
066
Denpasar
, IND
MUL: 30m;
PAN: 15m 5 28%
WGS 84
/ UTM
zone 50
.tiff 8 Bit .txt
4. LE07_L1TP_116066_20020521_2017013
0_01_T1
08.02.20
17
21.05.2
002 L1TP
116/
066
Denpasar
, IND
MUL: 30m;
PAN: 15m 5 4%
WGS 84
/ UTM
zone 50
.tiff 8 Bit .txt
WorldView-2
6.
17FEB21023512-M2AS_R1C1-
056358854060_01_P001
31.03.20
17
21.02.2
017 LV2A R1C1
Denpasar
, IND
MUL: 2m;
PAN: 0.5m 4
7.0e-
03% UTM 50S .tiff
16
Bit .xml
17FEB21023512-M2AS_R1C2-
056358854060_01_P001
31.03.20
17
21.02.2
017 LV2A R1C2
Denpasar
, IND
MUL: 2m;
PAN: 0.5m 4
7.0e-
03% UTM 50S .tiff
16
Bit .xml
17FEB21023512-M2AS_R2C1-
056358854060_01_P001
31.03.20
17
21.02.2
017 LV2A R2C1
Denpasar
, IND
MUL: 2m;
PAN: 0.5m 4
7.0e-
03% UTM 50S .tiff
16
Bit .xml
17FEB21023512-M2AS_R2C2-
056358854060_01_P001
31.03.20
17
21.02.2
017 LV2A R2C2
Denpasar
, IND
MUL: 2m;
PAN: 0.5m 4
7.0e-
03% UTM 50S .tiff
16
Bit .xml
17FEB21023512-M2AS_R3C1-
056358854060_01_P001
31.03.20
17
21.02.2
017 LV2A R3C1
Denpasar
, IND
MUL: 2m;
PAN: 0.5m 4
7.0e-
03% UTM 50S .tiff
16
Bit .xml
Quickbird-2
7. 06MAY16030316-M2AS_R1C1-
056358854070_01_P001
31.03.20
17
16.05.2
006 LV2A R1C1
Denpasar
, IND
MUL: 2m;
PAN: 0.6m 4
2.0e-
03% UTM 50S
GeoTI
FF
16
Bit
.imd,
rpb,
.til,
xml
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 8
06MAY16030316-M2AS_R2C1-
056358854070_01_P001
31.03.20
17
16.05.2
006 LV2A R2C1
Denpasar
, IND
MUL: 2m;
PAN: 0.6m 4
2.0e-
03% UTM 50S
GeoTI
FF
16
Bit
.imd,
rpb,
.til,
xml
06MAY16030316-M2AS_R2C2-
056358854070_01_P001
31.03.20
17
16.05.2
006 LV2A R2C2
Denpasar
, IND
MUL: 2m;
PAN: 0.6m 4
2.0e-
03% UTM 50S
GeoTI
FF
16
Bit
.imd,
rpb,
.til,
xml
8. 05SEP11025755-M2AS-
056358854070_01_P002
31.03.20
17
11.09.2
005 LV2A
Denpasar
, IND
MUL: 2m;
PAN: 0.6m 4 0% UTM 50S
GeoTI
FF
16
Bit
.imd,
rpb,
.til,
xml
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 9
1.2 List of In-situ Data
Dataset 1 (14) Incoming Date Acquisition Date
AOI - City
/ Region
/ Country
Data Type (4)
Projection /
Spheroid (16)
No. of Sample
Plots
Sampling Design (22)
Positional
Accuracy (11)
Purpose (9)
No In-situ Data Used
Lineage:
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 10
1.3 List of Ancillary Data
Dataset 1 (14)
Schools
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area/-
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Availability
of Class
Definitions
elementary_schools.sh
p 23.03.2017 incomplete
2016 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
junior_high_schools.sh
p 23.03.2017 incomplete
2016 /
26.09.2016.
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
senior_high_schools.sh
p 23.03.2017 incomplete
2016 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
vocational_schools.shp 23.03.2017 incomplete 2016 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
Lineage(29): This file contains the location and attribute information of the public elementary schools, junior high schools, senior high schools and vocational schools in Denpasar.
Source (30): Received from World Bank City Planning Lab programme; provided by CPL Team-Seetha Raghupathy on 25.11.2016
basic_education.shp 23.03.2017 incomplete n.a. /
22.07.2015
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 2 unknown No
education.shp 23.03.2017 incomplete 2017 /
01.07.2015
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 5 unknown No
Lineage(29): This shapefile includes basic education schools on the territory of Denpasar, which are divided into 2 classes and the other shapefile includes educational facilities on the territory of
Denpasar, which are divided into 5 classes.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 11
Dataset 2 (14)
Health
Facilities
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area /
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Class
Definitions
hospitals.shp 23.03.2017 incomplete 2016 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
clinics.shp 23.03.2017 Incomplete 2016 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown 1 unknown No
Lineage(29): This files contains the locations and attributes of the community health centers and hospitals in Denpasar.
Source (30): Received from Ms. Aurora Dias Lokita and Ms. Seetha Raghupathy.
poi_sarana_kesehatan.
shp 23.03.2017 not available
2017 /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 3 unknown No
Lineage(29): This shapefile includes health facilities within Denpasar, which are divided into the following 3 classes: hospitals, clinics and pharmacies.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Dataset 3 (14)
Street
Layers
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area/-
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Availability
of Class
Definitions
jalan_wgs84UTM50s.sh
p 23.03.2017 Incomplete
2010 /
12.08.2016
Denpasar
(municipality
boundary)
80% of
core_are
a
Vector *.shp WGS_1984_UTM
_Zone_50S unknown n.a. unknown No
Lineage(29): This file contains the road network of Denpasar from the year 2010. There are topological errors in this file where lines from streets may not connect as they do in reality.
Source (30): Data received from Ms. Seetha Raghupathy.
Status &Fungsi Jln Dps
Plan_polyline.shp 23.03.2017 not available
2009 /
19.11.2015
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UTM
_Zone_50S unknown n.a. unknown No
Lineage(29): This shapefile includes secondary streets which were identified by the user.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 12
Dataset 4 (14)
Commer
cial
areas
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area /
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Class
Definitions
poi_sarana_inudustri-
perdagangan.shp
23.03.2017 not available 2012 /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 2
unknown No
Lineage(29): This shapefile includes commercial areas on the territory of Denpasar, which are divided into 2 classes.
Source (30): Received from Ms. Aurora Dias Lokita
poi_sarana_perdagang
an_jasa_Markets.shp 23.03.2017 not available
2012 /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 7
unknown No
Lineage(29): This shapefile includes commercial areas on the territory of Denpasar, which are divided into 7 classes.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 13
Dataset 5 (14)
Public
Building
s
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area /
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Class
Definitions
poi_sarana_olahraga.sh
p 23.03.2017 not available
2012 /
19.11.2015
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 1
unknown No
Lineage(29): This shapefile includes sport facilities on the territory of Denpasar.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
poi_sarana_perkantora
n_dan_pelayanan_mas
yarakat.shp
23.03.2017 Incomplete 2012 /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 7
unknown No
Lineage(29): This shapefile includes public facilities on the territory of Denpasar, which are divided into 7 classes.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
poi_sarana_ibadah.shp 23.03.2017 not available 2012 /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 4
unknown No
Lineage(29): This shapefile includes religious buildings on the territory of Denpasar, which are divided into 4 classes.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
poi_kuburan.shp 23.03.2017 not available n.a. /
22.03.2017
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 1
unknown No
Lineage(29): This shapefile includes cemeteries within Denpasar.
Source (30): Received from Ms. Aurora Dias Lokita.
slums_point.shp 23.03.2017 not available n.a. /
19.11.2015
Denpasar
(municipality
boundary)
100% Vector *.shp GCS_WGS_1984 unknown 1
unknown No
Lineage(29): This shapefile includes slum areas on the territory of Denpasar.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 14
Dataset
6(14)
Land
Use Map
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area/-
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Availability
of Class
Definitions
PL_DENPASAR_GEO.sh
p 23.03.2017 incomplete
2012 /
26.09.2016
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UT
M_Zone_50S unknown 28 unknown No
Lineage(29): This shapefile is a LU map of the territory of Denpasar.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Dataset
6(14)
Census
Data,
Ward
Boundar
ies
Date of
Receipt from
Client
Metadata (2)
Reference
Mapping
Date / Date
of Creation
Geographic Area/-
City / Region /
Country
Area
Coverage
Data
Type (4)
Data
Format (3)
Projection /
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Thematic
Accuracy
Availability
of Class
Definitions
kelurahan_census.shp 23.03.2017 incomplete 2013 (?) /
n.a.
Denpasar
(municipality
boundary)
100% Vector *.shp WGS_1984_UT
M_Zone_50S unknown / unknown No
Lineage(29): This shapefile includes census data for the years 2004 to 2013 as well as the word boundaries of the territory of Denpasar.
Source (30): Received from World Bank City Planning Lab programme: provided by CPL team-Ms. Aurora Dias Lokita on 07.03.2017
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 15
2.1 EO Data Quality
Sensoren(8) Sentinel-2, Landsat 7, QB-2, WV-2
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2
)
Band Specifications
Pro
jecti
on
/ S
ph
ero
id (
16
)
Sce
ne
Lo
ca
tio
n
Co
mp
lete
ne
ss o
f
Ad
dit
ion
al D
ata
Da
ta F
orm
at
(3)
Bit
De
pth
(5
)
Clo
ud
Co
ve
r (i
nte
rna
l
ch
eck
)
Ra
dio
me
try
To
po
gra
ph
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7
)
Acce
pta
nce
Sta
tus
Com
ment
s File Name [e.g yymmdd; tbd...]
No
. o
f B
an
ds
Ba
nd
Re
gis
tra
tio
n
Sp
ectr
al/
Sp
ati
al
Re
so
luti
on
Sentinel-2
1. S2A_OPER_MSI_L1C_TL_SGS__20160607T0
91621_A005005_T50LKR Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q
Y - V
Q
Y - V
Q
Y -
V
N - V
Q Yes none
2. S2A_OPER_MSI_L1C_TL_SGS__20160607T0
91621_A005005_T50LLR_N02.02 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
Landsat-7
3. LE07_L1TP_116066_20001209_20170208
_01_T1 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
4. LE07_L1TP_116066_20020521_20170130
_01_T1 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
Worldview-2
6. 17FEB21023512-M2AS-
056358854060_01_P001 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
Quickbird-2
7. 06MAY16030316-M2AS-
056358854070_01_P001 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
8. 05SEP11025755-M2AS-
056358854070_01_P002 Y - Q Y - V Q Y - V Q Y - V Q Y - V Q Y - Q Y - V Y - V Y - V Q Y - Q
Y -
Q Y - V
Q
Y - V
Q
Y -
V N - V
Q Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 16
2.2 In-situ Data Quality
Dataset 1 (14)
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2)
Ext
en
t
Pro
jecti
on
/ S
ph
ero
id
(16
)
Sp
ati
al R
eso
luti
on
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Lo
ca
tio
n
Co
mp
lete
ne
ss
Ge
om
. M
isa
lign
me
nt
Pla
usib
ilit
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7)
Acce
pta
nce
Sta
tus
Comments
File Name [e.g yymmdd; tbd...]
No in-situ data used
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 17
2.3 Ancillary Data Quality
Dataset 1 (14) Schools
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (2
)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a (
%)
Pro
jecti
on
/ S
ph
ero
id
, E
PS
G(1
6)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
elementary_schools.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
junior_high_schools.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
senior_high_schools.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
vocational_schools.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
basic_education.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
education.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. Some points show schools, others not.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 18
Dataset 2 (14) Health Facility
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (2
)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a (
%)
Pro
jecti
on
/ S
ph
ero
id
EP
SG
(16
)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
hospitals.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☐ Partial
☒ Full
clinics.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☐ Partial
☒ Full
poi_sarana_kesehatan.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. This files contains the locations and attributes of the hospitals, community health centers, clinics and pharmacies in Denpasar.
Dataset 3 (14) Street Layers
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (2
)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a (
%)
Pro
jecti
on
/ S
ph
ero
id
, E
PS
G(1
6)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
jalan_wgs84UTM50s.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 80%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Status &Fungsi Jln Dps
Plan_polyline.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 32750
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. Streets were identified by the user.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 19
Dataset 4 (14) Commercial
Areas
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (
2)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a
(%)
Pro
jecti
on
/ S
ph
ero
id
, E
PS
G(1
6)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5
)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
poi_sarana_inudustri-
perdagangan.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
poi_sarana_perdagangan_jasa_Mar
kets.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. This shapefiles includes commercial areas on the territory of Denpasar.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 20
Dataset 5 (14) Public
Buildings
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (2
)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a
(%)
Pro
jecti
on
/ S
ph
ero
id
, E
PS
G(1
6)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
poi_sarana_olahraga.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
poi_sarana_perkantoran_dan_pelay
anan_masyarakat.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☒ Incomplete
☐ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
poi_sarana_ibadah.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
poi_kuburan.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
slums_point.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☒ Complete
☐Incomplete
☐ No
☐ Yes
☒ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. This shapefile includes sport facilities, public facilities, religious buildings, cemeteries and slum areas on the territory of Denpasar.
Dataset 6 (14) Land Use
Map 2012
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (2
)
Da
ta C
ove
rage
Ma
tch
es S
erv
ice
Are
a
(%)
Pro
jecti
on
/ S
ph
ero
id
, E
PS
G(1
6)
Sp
ati
al R
eso
luti
on
an
d u
nit
(e
.g.
m, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Co
mp
lete
ne
ss
(Ve
cto
r: A
ttri
bu
te
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t
Pro
ject
File Name [e.g yymmdd; tbd...]
PL_DENPASAR_GEO.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ Yes
☐ No
☐ Unknown
☒ Correct
☐ Incorrect
☐ Unknown
n.a. *.shp n.a. ☐ Complete
☒Incomplete
☐ No
☐ Yes
☒ Unknown
☐ No
☐ Yes
☒ n.a.
☐ None
☒ Partial
☐ Full
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 21
☒ not available If no: 100% EPSG: 4326 If yes: XX m If yes: xxx %
Comments: Accuracy of the dataset is unknown. This shapefile is a Land Use Map with 28 classes.
Dataset 7 (14)
Census Data,
Ward
Boundaries
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/M
eta
da
ta (
2)
Da
ta C
ove
rage
Ma
tch
es
Se
rvic
e A
rea
(%
)
Pro
jecti
on
/ S
ph
ero
id ,
EP
SG
(16
)
Sp
ati
al R
eso
luti
on
an
d
un
it (
e.g
. m
, k
m)
Da
ta F
orm
at
(3)
Bit
De
pth
(5
)
Co
mp
lete
ne
ss (
Ve
cto
r:
Att
rib
ute
Ta
ble
; R
aste
r:
Th
em
ati
c V
alu
es)
Ge
om
. M
isa
lign
me
nt
Dro
pp
ed
Lin
es /
Art
efa
cts
(E
O d
ata
on
ly)(
7)
Uti
lity
fo
r C
urr
en
t P
roje
ct
File Name [e.g yymmdd; tbd...]
kelurahan_census.shp ☒ Yes
☐ No
☐ Complete (INSPIRE/ISO19119)
☐ Incomplete
☒ not available
☒ Yes
☐ No
☐ Unknown If no: 100%
☒ Correct
☐ Incorrect
☐ Unknown EPSG: 4326
n.a. *.shp n.a. ☐ Complete
☒Incomplete
☐ No
☒ Yes
☐ Unknown If yes: XX m
☐ No
☐ Yes
☒ n.a. If yes: xxx %
☐ None
☒ Partial
☐ Full
Comments: Accuracy of the dataset is unknown. This shapefile was used for statistical analyses. Overlaps and gaps had to be corrected first, before it could be used for the analyses.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 22
3.1 Geometric Correction
Sensoren (8) Sentinel-2, Landsat 7, QB-2,
WV-2
Pro
ce
ssin
g D
ate
AO
I
Cit
y / R
egio
n /
Co
un
try
Pro
jecti
on
/ S
ph
ero
id (
16
)
No
. &
RM
S (
m)
of
GC
Ps (
17
)
No
. &
RM
S (
m)
of
TP
s (
18
)
No
. &
RM
S (
m)
of
CP
s (
19
)
Dig
ita
l E
leva
tio
n M
od
el
(DE
M)
Mo
de
l / A
lgo
rith
m (
13
)
Re
sa
mp
lin
g
Me
tho
d (
20
)
Va
lid
ati
on
Re
po
rts
Acce
pta
nce
Sta
tus
Output File Name [e.g
yymmdd; tbd...] N
o. File Name [e.g yymmdd; tbd...]
Sentinel-2
1. S2A_OPER_MSI_L1C_TL_SGS__201606
07T091621_A005005_T50LKR
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84 N/A N/A N/A
S2A_OPER_MSI_L1C_TL
_SGS__20160607T091
621_A005005_T50LLR
2. S2A_OPER_MSI_L1C_TL_SGS__201606
07T091621_A005005_T50LLR_N02.02
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84 N/A N/A N/A
S2A_OPER_MSI_L1C_TL
_SGS__20160607T091
621_A005005_T50LKR
Landsat-7
3. le07_l1tp_116066_20001209_201702
08_01_t1_b1-8_stack_toa_PSH
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84 N/A N/A N/A
le07_l1tp_116066_200
01209_20170208_01_
t1_b1-8_stack_toa_PSH
4. le07_l1tp_116066_20020521_201701
30_01_t1-b1-8_stack_toa_PSH
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84 N/A N/A N/A
le07_l1tp_116066_200
20521_20170130_01_
t1-b1-8_stack_toa_PSH
Worldview-2
6. 17FEB21023512-M2AS-
056358854060_01_P001_toa_PSH
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84 N/A N/A N/A
SRTM
30
0 order
poynom CC Yes Yes
o17FEB21023512-
M2AS-
056358854060_01_P0
01_toa_PSH
Quickbird-2
7. 05SEP11025755-M2AS-
056358854070_01_P002_toa_PSH
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84
GCPs 6;
RMSE
x0,96;
y0,64
TPs 4;
RMSE
x0,47;
y1,17
N/A SRTM
30
Affin, 1st
order
poynom
CC Yes Yes
o05SEP11025755-
M2AS-
056358854070_01_P0
02_toa_PSH
8. 06MAY16030316-M2AS-
056358854070_01_P001_toa_PSH
13.04.
2017
Denpas
ar IDN
UTM50S
/ WGS84
GCPs 6;
RMSE
x0,96;
y0,64
TPs 4;
RMSE
x0,47;
y1,17
N/A SRTM
30
Affin, 1st
order
poynom
CC Yes Yes
o06MAY16030316-
M2AS-
056358854070_01_P0
01_toa_PSH
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 23
3.1.1 Data Fusion
Dataset 1 (14) Input A Input B Output
Acce
pta
nce
Sta
tus
Comment
s
Filename 17FEB21023512-M2AS-
056358854060_01_P001
17FEB21023513-P2AS-
056358854060_01_P001
17FEB21023512-M2AS-
056358854060_01_P001_toa_PSH
none
Sensor Worldview-2 Worldview-2 Worldview-2
Method PCI / Pansharp2 PCI / Pansharp2 PCI / Pansharp2
Spatial Resolution /
(MS/Pan) 2m MS 0,5m Pan 0,5m MS
Band Combination RGB NIR PAN RGB NIR
Data Format (3) & Bit
Depth (5) *.tif 16 Bit u *.tif 16 Bit u *.pix 16 Bit u
Ye
s
Dataset 2 (14) Input A Input B Output
Acce
pta
nce
Sta
tus
Comment
s
Filename 06MAY16030316-M2AS-
056358854070_01_P001
06MAY16030316-P2AS-
056358854070_01_P001
06MAY16030316-M2AS-
056358854070_01_P001_toa_PSH
none
Sensor Quickbird2 Quickbird2 Quickbird2
Method PCI / Pansharp2 PCI / Pansharp2 PCI / Pansharp2
Spatial Resolution /
(MS/Pan) 2m MS 0,6m Pan 0,6m MS
Band Combination RGB NIR PAN RGB NIR
Data Format (3) & Bit
Depth (5) *.tif 16 Bit u *.tif 16 Bit u *.pix 16 Bit u
Ye
s
Dataset 3 (14) Input A Input B Output
Acce
pta
nce
Sta
tus
Comment
s
Filename 05SEP11025755-M2AS-
056358854070_01_P002
05SEP11025754-P2AS-
056358854070_01_P002
05SEP11025755-M2AS-
056358854070_01_P002_toa_PSH
none
Sensor Quickbird2 Quickbird2 Quickbird2
Method PCI / Pansharp2 PCI / Pansharp2 PCI / Pansharp2
Spatial Resolution /
(MS/Pan) 2m MS 0,6m Pan 0,6m MS
Band Combination RGB NIR PAN RGB NIR
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 24
Data Format (3) & Bit
Depth (5) *.tif 16 Bit u *.tif 16 Bit u *.pix 16 Bit u
Ye
s
Dataset 4 (14) Input A Input B Output
Acce
pta
nce
Sta
tus
Comment
s
Filename LE07_L1TP_116066_20001209_201702
08_01_T1_B8
LE07_L1TP_116066_20001209_201702
08_01_T1_MTL
le07_l1tp_116066_20001209_20170208_01_t1_
b1-8_stack_toa_PSH
none
Sensor Landsat-7 Landsat-7 Landsat-7
Method PCI / Pansharp2 PCI / Pansharp2 PCI / Pansharp2
Spatial Resolution /
(MS/Pan) 30m MS 15m Pan 0,5m MS
Band Combination RGB NIR PAN RGB NIR
Data Format (3) & Bit
Depth (5) *.tif 16 Bit u *.tif 16 Bit u *.pix 16 Bit u
Y
e
s
Dataset 5 (14) Input A Input B Output
Acce
pta
nce
Sta
tus
Comment
s
Filename LE07_L1TP_116066_20020521_201701
30_01_T1_MTL
LE07_L1TP_116066_20020521_201701
30_01_T1_B8
le07_l1tp_116066_20020521_20170130_01_t1-
b1-8_stack_toa_PSH
none
Sensor Landsat-7 Landsat-7 Landsat-7
Method PCI / Pansharp2 PCI / Pansharp2 PCI / Pansharp2
Spatial Resolution /
(MS/Pan) 30m MS 15m Pan 0,5m MS
Band Combination RGB NIR PAN RGB NIR
Data Format (3) & Bit
Depth (5) *.tif 16 Bit u *.tif 16 Bit u *.pix 16 Bit u
Y
e
s
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 25
3.2 Data Processing
Sensoren (8)
Sentinel-2, Landsat 7, QB-2,
WV-2
Atmospheric
Correction
Radiometric
Processing (15)
Topographic
Normalisation OTHER Calculation:
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment No
. File Name [e.g yymmdd; tbd...]
Processing
Date
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software
/ Method
Sentinel-2
1. S2A_OPER_MSI_L1C_TL_SGS__20160
607T091621_A005005_T50LKR 10.04.2017 N N/A N N/A N N/A N N/A Y Y
Data use as
delivered
2.
S2A_OPER_MSI_L1C_TL_SGS__20160
607T091621_A005005_T50LLR_N02.
02
10.04.2017 N N/A N N/A N N/A N N/A Y Y Data used as
delivered
Landsat-7
3. LE07_L1TP_116066_20001209_201
70208_01_T1_MTL 12.04.2017 N N/A N N/A N N/A Y
GAFmap /
TOA Y Y none
4. LE07_L1TP_116066_20020521_201
70130_01_T1_MTL 12.04.2017 N N/A N N/A N N/A Y
GAFmap /
TOA Y Y none
Worldview-2
6. 17FEB21023512-M2AS-
056358854060_01_P001 12.04.2017 N N/A N N/A N N/A Y
GAFmap /
TOA Y Y none
Quickbird-2
7. 06MAY16030316-M2AS-
056358854070_01_P001 12.04.2017 N N/A N N/A N N/A Y
GAFmap /
TOA Y Y none
8. 05SEP11025755-M2AS-
056358854070_01_P002 12.04.2017 N N/A N N/A N N/A Y
GAFmap /
TOA Y Y none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 26
4.1 Classification
Sensors (8) Sentinel-2, Landsat 7, WV-2,
QB-2
Processing
Date
Cloud
Masking Thematic Classification Manual Enhancement Mosaicking
Acce
pta
nce
Sta
tus
Ba
ck
up
Comme
nt N
o. File Name [e.g yymmdd; tbd...]
pro
ce
sse
d
Softwa
re /
Metho
d pro
ce
sse
d
Software / Method
pro
ce
sse
d
Software / Method
pro
ce
sse
d
Software /
Method
1.
S2A_OPER_MSI_L1C_TL_SGS__20160607T
091621_A005005_T50LKR
S2A_OPER_MSI_L1C_TL_SGS__20160607T
091621_A005005_T50LLR_N02.02
12.06.2017 N N/A Y eCognition/semi-
automatic approach Y
eCognition and
ArcGIS 10 / Visual
Interpretation
Y
ArcGIS 10 /
Mosaic Dataset
with manual
neatline selection
Y Y
Cloud
free
data.
2.
LE07_L1TP_116066_20001209_20170208
_01_T1_MTL
LE07_L1TP_116066_20020521_20170130
_01_T1_MTL
22.06.2017 N N/A Y
GAFMap and
ArcMap/visual
mapping
Y
GAFMap and
ArcMap/Visual
interpretation N N/A Y Y
Cloud
free
data.
4. 17FEB21023512-M2AS-
056358854060_01_P001
12.06.2017
N N/A Y
GAFMap and
ArcMap/visual
mapping
Y
GAFMap and
ArcMap/Visual
interpretation
Y
ArcGIS 10 /
Mosaic Dataset
with manual
neatline selection
Y Y
Cloud
free
data.
5.
06MAY16030316-M2AS-
056358854070_01_P001
05SEP11025755-M2AS-
056358854070_01_P002
22.06.201
7 N N/A Y
GAFMap and
ArcMap/visual
mapping
Y
GAFMap and
ArcMap/Visual
interpretation
Y
ArcGIS 10 /
Mosaic Dataset
with manual
neatline selection
Y Y
Cloud
free
data.
Earth Observation for Sustainable
Development – Urban
Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 27
4.2 Intermediate Quality Control of LCLU Data
No.
x = ok (checked/performed)
o = not performed
n/a = not applicable
Co
mp
lia
nt
Each item was checked during production and if
necessary the source of error was identified and
corrected.
Description of QC item Comment
1 Data in predefined coordinate system?
(e.g. UTM WGS84 system) x
2 Do all features have attributes? x
3
All feature attributes are valid (attribute
value range, flags, correct comments)?
1) Do all features have a valid class
name?
x
4 All feature attributes present and filled
in? x
5 Data coherence at the border of the
urban area checked? x
6 Positional Accuracy of the features
according to User Specifications? x
7 All feature geometries valid? x
8
Vertices of feature geometries adjusted?
(e.g. missing, duplicated/ very close
vertices)
x
9 Multipart features resolved (Ring loops)? x
10 No data gaps? (Clean Gaps only if there
are over ~200 gaps)
11 No data overlaps? (Clean Overlaps only if
there are over ~200 gaps) x
12
Feature geometries optimized (e.g.
spikes, cutbacks minimized) (Find acute
angles, remove angles < 15°)
x
13 Minimum Mapping Area checked? (Urban
0.25ha, peri-urban 0.5ha) x
14 Minimum Mapping Width checked? x
15 Data checked for unnecessary polygon
boundaries? (after final dissolve) x
16 Service Area completely covered by
requested data (no data gaps)? x
17 No data outside delivery AoI? x
18
Add two new columns with the code and
the name of the class.(Name them:
code_year and name_year of the actual
classification”
x
19
Feature attribution and feature relations
plausible? (Plausibility Check ) --> Change
product
x
20 Calculation of area [AREA_km2] adjusted
to final data? x
21 Re-calculation of [ID] (FID + 1)? x
22
LCLU product file naming and versioning
according to specifications?
(City_program_product_referenceDate_C
oordinateSystem)
x
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 28
5.1 Thematic Accuracy
No. Product
Name
Processing
Date Area Coverage
No
. o
f C
lasse
s
Re
fere
nce
Da
ta
Sa
mp
le S
ize
Sa
mp
lin
g U
nit
(2
1)
Sa
mp
lin
g
De
sig
n (2
2)
Sa
mp
le E
xclu
sio
n
Cri
teri
a (
23
)
Th
em
ati
c A
ccu
racy
(24
)
Acce
pta
nce
Sta
tus
Comment
1.
Land
Cover
Map
2015
18.05.2017
Entire AOI
(Urban Core and
Peri-Urban
areas)
17 VHR imagery
of 2017
215 per strata
(overall 1019
points were
sampled with
a minimum
distance of
150m).
points Stratified Random Sampling None 89,11 % Yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
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use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 29
5.2 Error Matrices
Class Name
(columns = Ground
Truth; Rows =
Mapped Class) Re
sid
en
tia
l
Co
mm
erc
ial
Ro
ad
s
Po
rt
Air
po
rt
Min
ing
Co
nstr
ucti
on
Op
en
Sp
ace
Gre
en
Are
as
Sp
ort
Agri
cu
ltu
re
Fo
rest
Fis
he
rie
s
Gra
ssla
nd
/S
h
rub
s
Ba
re S
oil
Ma
ngro
ve
s
Be
ach
We
tla
nd
s
Wa
ter
User Accuracy
and Confidence
Interval at 95%
Confidence
Level
Clas
s ID 11
12
1 122 124 125 131 132 133 141 142 2 31 32 33 34 35 36 4 5 Totals
Residential 11 158 10 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0 0 0 172 91.86% +4.4% Commercial 121 2 32 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 36 88.89% +11.7% Roads 122 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 100.00% n.a. Port 124 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 100.00% n.a. Airport 125 1 0 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 30 96.67% +8.1% Mining 131 0 0 0 0 0 30 0 0 0 0 0 0 0 0 0 0 0 0 0 30 100.00% n.a. Constructio
n 132 0 1 0 0 0 1 26 2 0 0 0 0 0 0 0 0 0 0 0
30 86.67% +13.8%
Open Space 133 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 3 66.67% +70% Green Areas 141 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 100.00% n.a. Sport 142 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 100.00% n.a. Agriculture 2 4 0 0 0 0 0 0 0 0 0 197 12 0 2 0 0 0 0 0 215 91.63% +3.9% Forest 31 2 1 0 0 0 0 0 0 0 0 15 113 0 4 0 0 0 1 0 136 83.09% +6.7% Fisheries 32 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 3 100.00% n.a. Grassland 33 0 0 0 0 0 0 0 0 0 0 6 6 0 47 0 1 0 0 0 60 78.33% +11.3% Bare Soil 34 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 0 0 0 0 5 80.00% +45.1% Mangroves 35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 1 0 7 85.71% +33.1% Beach 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 100.00% n.a. Wetlands 4 0 0 0 0 0 0 0 0 0 0 8 1 2 6 0 0 0 52 0 69 75.36% +10.9% Water 5 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 2 0 9 201 215 93.49% +3.5%
Totals 167 44 1 1 29 31 26 5 2 3 227 135 7 60 4 9 4 63 201 1019
Producer Accuracy
and Confidence
Interval at 95%
Confidence Level 94
.61
%
+3.7
%
72
.73
%
+14
.3%
10
0.0
0%
n
.a.
10
0.0
0%
n.a
.
10
0.0
0%
n.a
.
96
.77
%
+7.8
%
10
0.0
0%
n.a
.
40
.00
%
+52
.9%
50
.00
%
+94
.3%
33
.33
%
+70
.0%
86
.78
%
+4.6
%
83
.70
%
+6.6
%
42
.86
%
+43
.8%
78
.33
%
+11
.3%
10
0.0
0%
n.a
.
66
.67
%
+36
.4%
10
0.0
0%
n.a
.
82
.54
%
+10
.2%
10
0.0
0%
n.a
. Overall Accuracy: 89.11%
Confidence Interval
87.14% - 91.07%
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 30
6.1 Completeness
INPUT DATA
No
. Item
AOI Coverage
[km²]
Area Coverage
[km²]
Completeness of
Coverage (25) No. of Scenes
Scenes used in
Production
Completeness of
Verification (27) Metadata Comments
1. HR EO Data
541 km²
409 km² 100% 4 4 100% Yes none
2. VHR EO Data 132 km² 100% 3 3 100% Yes none
3. In-situ Data None None None None 100% Na Na
4. Ancillary Data Na Na Na Na 100% Incomplete
Ancillary data was
evaluated and
partially used,
Metadata often
incomplete.
PRODUCTS
No
. Product (28)
AOI Coverage
[km²]
Product
Coverage
[km²]
Completeness of
Coverage (25)
Completeness of
Classification (26)
Unclassifiable
Area [%]
Completeness of
Verification (27) Metadata Comments
1. Land Use 2006
541 km²
541 km² 100% 100% 0% 100% Yes none
2. Land Use 2016 541 km² 100% 100% 0% 100% Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 31
6.2 Compliancy
Product 1 (28) EO4SD_Denpasar_WB_LULC_2006_2016
Abstract
Land Use/Land Cover (LU/LC) information product contains spatial explicit information on different land
use and land cover occurring in both the Core and Peri-Urban areas of the City of Denpasar. The Core area
has detailed LU/LC nomenclature that is either at Level 3 or 4 whereas the Peri-Urban area LU/LC
nomenclature is at an aggregated Level 1 or 2. The input data for the Core area was the Very High
Resolution data of WorldView-2 for 2017, Quickbird-2 for 2005, 2006 and the input data for the Peri-Urban
area was Sentinel (2017) and Landsat-7 (2002, 2002). The LU/LC product is the Baseline Product from
which various derived products (such as Green Areas and Informal Settlements) are produced.
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia Country 1: Indonesia 100%
Country 2: N/A Country 2: N/A
Country 3: N/A Country 3: N/A
Country 4: N/A Country 4: N/A
A) Wall-to-wall: A) Wall-to-wall: 100%
Sub-national, Denpasar Sub-national, Denpasar
Test area of approx. 26,000 km², defined by the national user.
B) Sampling based: B) Sampling based:
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s):
Y
EO data used differs
from specified
Baseline Years,
within accepted
range
2005 (+/- 1 year)
2015 (+/- 1 year)
2005/2006
2017
B) Update Frequency B) Update Frequency
Na Na
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
EPSG: 32749. WGS 84 / UTM zone
50S EPSG: 32749. WGS 84 / UTM zone 50S Yes --
Mapping Classes and Definitions (Definitions see REDD+ MRV Design Document)
Requirements Achieved Specifications Compliancy
30 classes (see 0.1 Requirements sheet) All classes were mapped according to their
definition. Y
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
Cloud free Yes Y --
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 32
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
Na -- -- --
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
0.25 ha and 0.5 ha MMU 0.25 ha and 0.5 ha Y
Data Type
Requirements Achieved Specifications Compliancy Comments
Vector data yes Y --
GeoPDF None were set na --
Bit Depth
Requirements Achieved Specifications Compliancy Comments
None Na Na --
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile Y --
(open cross-platform format)
Class Coding
Requirements Achieved Specifications Compliancy
Na Na --
Metadata
Requirements Achieved Specifications Compliancy Comments
INSPIRE compliant INSPIRE compliant and attached to
product Y
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
Overall Accuracy: >80% 89.11 % Y
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
30m 15m Y
Delivery Procedure
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 33
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP Uploaded to FTP Yes online via FTP
Delivery Date
Requirements Achieved Specifications Compliancy Comments
August 2017 August 2017 Yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 34
Glossary
Quality Checks
Prefix Suffix Explanation
Y (Yes) - V Visually checked
N (No) - Q Quantitatively/qualitatively checked
N/A - V Q Visually and quantitatively/qualitatively checked
- N/A Not applicable
Readability (1) Check readability of all required input data. Can the data be stored again?
Header / Metadata (2) Check Image Header Information and/or Metadata for completeness / distinctive
features.
Data Format (3) For digital data, please give file format (e.g. *.tiff, *.shp).
Data Type (4) Please specify the type of the data (e.g. raster, vector or analogue).
Bit Depth (5) Please give pixel depth and sign of raster data (e.g. 8 bit unsigned integer).
Dynamic Range (6) Check dynamic range of all image bands. Visual check of dynamic range should be
accompanied by histograms and statistics.
Dropped Lines & Artefacts (7) Check Image for dropped lines and other artefacts. If such occurs, please give
description of extent and influence in the Comments section.
Sensor 1, 2, … (8) Please delete / add additional sensor sections as necessary.
Purpose (9)
The purpose and use of the given auxiliary or reference data should be stated:
ORHTOrectification, GEOmetric correction, REFerence, VERification source,
POSitional ACCuracy assessment, THEmatic ACCuracy assessment.
Sampling Methodology (10)
Methodology of in situ or reference/auxiliary data sampling scheme should be
outlined. In case of sample plots, also state how the plot positions have been
determined (e.g. from GPS measurements, topographic maps, terrestrial
triangulation, EO data, etc.) and how the sampling grid was established.
Positional Accuracy (11)
Positional accuracy of collected in situ data should be given. For reference/auxiliary
data it MUST be given. If unknown, the data’s use must be explained. For DEM or
other data with 3D information please specify both vertical and horizontal Positional
Accuracy. For analogue data (e.g. maps) try to give approximate accuracy related to
mapping scale.
Completeness (12) Data should be checked for spatial/temporal/content gaps.
Model / Algorithm (13)
Give the name of the software and its version. Specify the software
module/algorithm used for: a) geometric correction, e.g., Polynomial and its degree,
Rational Functions, Thin Plate Spline, etc.
b) classification, e.g., ISODATA, Maximum Likelihood, Neural Networks, etc.
Dataset 1, 2, … (14) Please delete / add additional dataset sections as necessary.
Radiometric Processing (15)
State whether (and which) radiometric processing was applied (e.g., contrast
enhancement, histogram matching, bundle block adjustment, radiometric
normalisation, filtering, etc.).
Projection; Spheroid /
Ellipsoid (16)
Always specify completely, i.e. at minimum the Projection (+Zone, if applicable),
Spheroid / Ellipsoid, Map Datum. Give additional information if necessary to
unambiguously define the reference system.
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
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Page 35
Ground Control Points (GCPs) (17)
Give the number, distribution and RMS of used Ground Control Points (as average
per scene) as obtained from the Geometric Correction, in meters [m]. Optionally, also
RMSx and RMSy may be given. Distribution of GCPs should be attached as a
snapshot, or described in the Comments section.
Tie Points (TPs) (18)
In case of mosaicking, give the number of used Tie Points and their total RMS (as
average per scene) as obtained from the Geometric Correction, in meters [m].
Optionally, also RMSx and RMSy may be given. Distribution of TPs should be
attached as a snapshot, or described in the Comments section.
Check Points (CPs) (19)
The real measure of positional accuracy and the only measure which should be
examined as to its Acceptable Range. Give the independent Check Points’ total RMS
(as average per scene) as obtained from the Geometric Correction, in meters [m].
Optionally, also RMSx and RMSy may be given. Distribution of CP's should be
attached as a snapshot, or described in the Comments section.
Resampling Method (20) Specify, if / which resampling algorithm has been used (e.g. NN=Nearest Neighbour,
BIL=Bilinear Interpolation, CC=Cubic Convolution).
Sampling unit (21) Specify sampling unit of Accuracy Assessment as POINT, FRAME, POLYGON and how
it is treated (e.g. pixel center, polygon centre, etc.).
Sampling Design (22) SYST=Systematic, RAND=Random, STRAT=Stratified, SBCLASS=Stratified by class,
SBAREA=Stratified by area
Sample exclusion criteria (23)
Describe which criteria you apply for sampling point selection resp. exclusion of
certain points. For example, if the point is too close to a class boundary (less than 1
pixel), it is excluded. If the selected sample point is not representative of the class ,
it is excluded. For these reasons, it is recommended to oversample by 10% to
compensate for sample point exclusion.
Thematic Accuracy (24)
Provide a detailed description of the Accuracy Assessment results in the form of
error matrices showing commission and omission errors, user’s , producer’s and
overall accuracies and other measures of Thematic Accuracy, as the confidence
level (usually fixed at 95%) and the respective confidence interval, at least for the
overall accuracy. If classification is done in a phased approach, e.g. if Forest Area
and subsequently Forest Type are mapped, independent reports have to be
produced.
Completeness of Coverage (25) State whether the coverage is limited to a subset, or portion of the final product.
Completeness of
Classification (26)
State whether classification was constrained to a subset, or portion of the final
product.
Completeness of Verification (27)
State whether verification applied to lineage, positional, or thematic accuracy is
constrained to a subset, or portion of the final product.
Product (28) Please delete / add additional product sections as necessary.
Lineage (29)
Definition (INSPIRE 2015): Lineage is “a statement on process history and/or overall
quality of the spatial data set. Where appropriate it may include a statement
whether the data set has been validated or quality assured, whether it is the official
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Page 36
version (if multiple versions exist), and whether it has legal validity. The value
domain of this element is free text.”
Source(30)
Definition (INSPIRE, 2015): “This is the description of the organisation responsible
for the establishment, management, maintenance or distribution of the resource.
This description shall include: name of the organisation and contact email address.”
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
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Page 1
Earth Observation for Sustainable Development - Urban
Quality Assurance and Quality Control Sheets These QA/QC Templates were prepared by GAF AG compliant with ISO 9001:2008 Quality Management System
standards and can only be used by Partners in the current EO4SD-Urban Project.
Project Title: EO4SD-Urban
Project Leader: GAF AG
Service Provider: JR Editor: H. Proske
Client: ADB Date: 14.09.2017
Product: Flood Risk Assessment
Overview of QC-Sheets and Processing Steps Sheet
used
Sheet filled
in
Requirements
0.1 Requirements Yes Yes
Specifications of Input Data
1.1 List of EO Data Yes Yes
1.2 List of In-situ Data No No
1.3 List of Ancillary Data Yes Yes
Data Quality Checks
2.1 EO Data Quality Yes Yes
2.2 In-situ Data Quality No No
2.3 Ancillary Data Quality Yes Yes
Pre-Processing of EO Data
3.1 Geometric Correction Yes Yes
3.1.1 Data Fusion Yes No
3.2 Data Processing Yes Yes
Thematic Processing
4.1 Classification Yes Yes
Accuracy Assessment
5.1 Thematic Accuracy Yes Yes
5.2 Error Matrices Yes Yes
Delivery Checks / Delivery
6.1 Completeness Yes Yes
6.2 Compliancy Yes Yes
Glossary (index numbers in the QA/QC tables refer to the glossary at the end of this document)
Further QC-relevant Documents:
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
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Page 2
Comments / Characteristics:
In-situ data for thematic accuracy assessment is not available
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reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
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Page 3
0.1 Requirements
Product 1 (28) Water Extent Denpasar (Water_Extent_RS_Denpasar)
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
No relevant increase of permanent and seasonal water cover can be observed for the period from 1984
to 2015 according to the Global Surface Water Explorer Product (Joint Research Centre), based on
Landsat Imagery.
For demonstration purposes, water extents of recent dates as derived from HR EO data are included in
the present Geodatabase.
Service / Product Specifications
Area Coverage
Country: Indonesia
City: Denpasar Wall-to-wall
Area km² Core Urban: 141,51 km²
Peri-Urban: 540,94 km²
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
2015 N/A
Comments: Update Frequency depends on flooding events
Geographic Reference System
UTM 50S
Mapping Classes and Definitions
Water Extent of recent dates
Cloud and Cloud Shadow Detection and Removal
Data selection is aiming at low cloud coverage in flood exposed areas
Relevant clouds manually digitized and replaced using additional EO data
Spatial Resolution
Vector files
Input raster resolution: 10 m (S2), 30 m (LS8)
Minimum Mapping Unit (MMU)
1.000 m²
Data Type & Format
Vector, shapefile format
Bit Depth
N/A
Class Coding
Class Code Class Name RGB Code
0 No Water Cover
1 Water Cover
Metadata
ISO compliant
Service / Product Quality
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
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Page 4
Thematic Accuracy
Overall Accuracy: not specified
Positional Accuracy
RMSE < 30 m
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
End of May 2017
Product 2 (28) Flood History River Floods (Flood History Rivers_Den)
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
To overcome this shortcoming, point data of reported and localized urban floods (2008 – 2017) are
included in this product.
Service / Product Specifications
Area Coverage
Country: Indonesia
City: Denpasar Core urban
Area km² Core Urban: 141,51 km²²
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
not specified depends on frequency of flooding events
Comments: data analysis of short-term river floods (hours to days) depends on availability of datasets to be
analysed
Geographic Reference System
UTM 50S
Mapping Classes and Definitions
Localization and date of flooding from river floods (point data)
Cloud and Cloud Shadow Detection and Removal
N/A
Spatial Resolution
Vector files
Minimum Mapping Unit (MMU)
N/A
Data Type & Format
Vector, shapefile format
Bit Depth
N/A
Class Coding
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
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Page 5
Class Code Class Name RGB Code
1 Localization of flood reports
Metadata
ISO compliant
Service / Product Quality
Thematic Accuracy
Overall Accuracy: not specified
Positional Accuracy
Not specified – depends on available input data
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
End of May 2017
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Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 6
Product 3 (28) Flood Hazard Short-term River Floods
(Flood_Hazard_Denpasar.gdb)
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical.
The present Geodatabase includes two shp-files for rough estimation of potential flooding zones:
a. Denpasar_Flood_Hazard_Rivers
Waterways are taken from OSM Layer and complemented by hydrologic modelling of potential
catchment areas and flow routes based on SRTM and visual interpretation of VHR data. After
classification in two classes based on Stream Order the lines were buffered with 50 m and 100 m
respectively to roughly estimate potential flooding zones.
b. Denpasar_Flood_Reports_buff200
Point data of reported and localized urban floods (2008 – 2017) are buffered with 200 m to roughly
estimate potential flooding hot-spots
Service / Product Specifications
Area Coverage
Country: Indonesia
City: Denpasar Wall-to-wall
Area km² Core Urban: 141,51 km²
Peri-Urban: 540,94 km²
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
not specified depends on frequency of flooding events
Comments: data analysis of short-term river floods (hours to days) depends on availability of datasets to be
analysed
Geographic Reference System
UTM 50S
Mapping Classes and Definitions
potential flooding zones close to rivers and waterways
potential flooding hot-spots
Cloud and Cloud Shadow Detection and Removal
N/A
Spatial Resolution
Point Shape file
Minimum Mapping Unit (MMU)
N/A
Data Type & Format
Vector, shapefile format
Bit Depth
N/A
Class Coding
Class Code Class Name RGB Code
1 potential flooding zones close to rivers and waterways
1 potential flooding hot-spots
Metadata
ISO compliant
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
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Service / Product Quality
Thematic Accuracy
Overall Accuracy: not specified
Positional Accuracy
Not specified – depends on available input data
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
End of May 2017
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Development – Urban Project QA/QC Sheets developed by GAF AG
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 8
Product 4 (28) Flood Hazard Denpasar Combined
(Flood_Hazard_Denpasar_Combined.shp)
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
No relevant increase of permanent and seasonal water cover can be observed for the period from 1984
to 2015 according to the Global Surface Water Explorer Product (Joint Research Centre), based on
Landsat Imagery.
As land subsidence is expected in Denpasar due to observed decrease in groundwater level coastal
lowlands are classified as flood prone at a distance of 200 m. This does not include Tsunami flooding.
The flood hazard map is taking into account all available data sources (EO based flood extents, reports
and press releases, results of modelling of potential flooding along rivers and waterways, ancillary data)
aiming at covering all types of floods and thus all areas which are potentially endangered by flooding.
The classification in three qualitative hazard levels is expert-based under consideration of observed and
reported frequencies of floods.
Service / Product Specifications
Area Coverage
Country: Indonesia
City: Denpasar
Area km² Core Urban: 141,51 km²
Peri-Urban: 540,94 km²
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
not specified depends on frequency of flooding events
Comments: data analysis of short-term river floods (hours to days) depends on availability of datasets to be
analysed
Geographic Reference System
UTM 50S
Mapping Classes and Definitions
1 low hazard
2 medium hazard
3 high hazard
Cloud and Cloud Shadow Detection and Removal
N/A
Spatial Resolution
Vector file
Minimum Mapping Unit (MMU)
N/A
Data Type & Format
Vector, shapefile format
Bit Depth
N/A
Class Coding
Class
Code Class Name RGB Code
1 low hazard 255-255-115
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2 medium hazard 255-211-127
3 high hazard 255-127-127
Metadata
ISO compliant
Service / Product Quality
Thematic Accuracy
Overall Accuracy: not specified
Positional Accuracy
Not specified – depends on available input data
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
September 2017
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Development – Urban Project QA/QC Sheets developed by GAF AG
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part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 10
Product 5 (28) Flood Risk Classification Denpasar
(Flood_Risk_Classification_Denpasar.shp)
Abstract
Risk is defined as a combination of probability and consequences. A detailed and uniform land-use map
is an important prerequisite to perform flood risk calculations, since it determines what is damaged in
case of flooding. The land-use map was provided by GAF AG and recoded to pre-defined categories to
ensure consistent results.
The exposition is classified integrating economic costs, social damage, physical damage and flood
duration. Four land use damage levels (A, B, C, D) are defined based on this estimation.
The Flood Risk matrix is generated based on these results code and on flood hazard classified into three
hazard levels. The flood risk level is classified in four qualitative classes based on the combination of
flood hazard and land use damage.
Service / Product Specifications
Area Coverage
Country: Indonesia
City: Denpasar
Area km² Core
Urban: 141,51 km²
Peri-
Urban: 540,94 km²
Time Period - Update Frequency
A) Baseline Year(s): B) Update Frequency
not specified depends on frequency of flooding events and on availability of land-use classification
(5 to 7 years)
Geographic Reference System
UTM 50S
Mapping Classes and Definitions
1 low risk
2 medium risk
3 high risk
4 very high risk
Cloud and Cloud Shadow Detection and Removal
N/A
Spatial Resolution
Vector file
Minimum Mapping Unit (MMU)
0.25 ha for the urban area, 0.5 ha for the peri-urban area.
Data Type & Format
Vector, shapefile format
Bit Depth
N/A
Class Coding
Class
Code Class Name RGB Code
1 low risk 255-255-190
2 medium risk 255-211-127
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Page 11
3 high risk 255-170-0
4 very high risk 255-0-0
Metadata
Not specified
Service / Product Quality
Thematic Accuracy
Overall Accuracy: not specified
Positional Accuracy
Not specified – depends on available input data
Delivery Procedure
Service Provision
Online via FTP
Delivery Date
September 2017
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Development – Urban Project QA/QC Sheets developed by GAF AG
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Page 12
1.1 List of EO Data
Sensor 1 (8)
Landsat 5
Incoming
Date
Acquisition
Date
Proc.
Level
Path /
Row
AOI - City /
Region /
Country
Spatia
l Res.
No. of
Band
s
Cloud
Cover
(Data
Provider
)
Projectio
n /
Spheroid (16)
Data
Forma
t (3)
Bit
Depth (5)
Header /
Metadata (2) File Name
1. LT51160661997151DKI00 20170509 19970531 L1TP 116/66 Denpasar 30,
30 7 3
UTM50S/
WGS84 *.tif 8 Bit u *.mtl
2. LT51160661999317DKI00 20170509 19991113 L1TP 116/66 Denpasar 30,
30 7 42
UTM50S/
WGS84 *.tif 8 Bit u *.mtl
3. LT51160662000064DKI00 20170509 20000304 L1TP 116/66 Denpasar 30,
30 7 68
UTM50S/
WGS84 *.tif 8 Bit u *.mtl
Lineage: USGS Earth Explorer Collection 1 Level-1/L4-5 TM C1 Level 1
Sensor 2 (8)
Landsat 8
Incoming
Date
Acquisition
Date
Proc.
Level
Path /
Row
AOI - City /
Region /
Country
Spatia
l Res.
No. of
Band
s
Cloud
Cover
(Data
Provider
)
Projectio
n /
Spheroid (16)
Data
Forma
t (3)
Bit
Depth (5)
Header /
Metadata (2) File Name
1. LC81160662013115LGN0
2 20170504 20130425 L1TP 116/66 Denpasar
30,
30 11 6.97
UTM50S/
WGS84 *.tif
12 Bit
u *.mtl
2. LC81160662013307LGN0
1 20170504 20131103 L1TP 116/66 Denpasar
30,
30 11 14.59
UTM50S/
WGS84 *.tif
12 Bit
u *.mtl
3. LC81160662014006LGN0
1 20170504 20140106 L1TP 116/66 Denpasar
30,
30 11 47.52
UTM50S/
WGS84 *.tif
12 Bit
u *.mtl
4 LC81160662015105LGN0
1 20170504 20150415 L1TP 116/66 Denpasar
30,
30 11 1.91
UTM50S/
WGS84 *.tif
12 Bit
u *.mtl
5. LC81160662016012LGN0
2 20170504 20160112 L1TP 116/66 Denpasar
30,
30 11 6.32
UTM50S/
WGS84 *.tif
12 Bit
u *.mtl
Lineage: USGS Earth Explorer Collection 1 Level-1/L8 OLI/TIRS C1 Level 1
Sensor 3 (8)
Sentinel 2
Incoming
Date
Acquisition
Date
Proc.
Level
Path /
Row
AOI - City /
Region /
Country
Spatia
l Res.
No. of
Band
s
Cloud
Cover
(Data
Provider
)
Projectio
n /
Spheroid (16)
Data
Forma
t (3)
Bit
Depth (5)
Header /
Metadata (2) File Name
1.
S2A_OPER_MSI_L1C_TL_EP
A__20161213T095422_A0
01716_T50LKR_N02.04
20170512 20151021 L1C 3/n/a Denpasar 10,
10 13
13.281
7
UTM50S/
WGS84 *jp2
12 Bit
u *.safe
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Page 13
2.
S2A_OPER_MSI_L1C_TL_S
GS__20151230T091952_A
002717_T50LKR_N02.01
20170512 20151230 L1C 3/n/a Denpasar 10,
10 13 5
UTM50S/
WGS84 *jp2
12 Bit
u *.safe
3.
S2A_OPER_MSI_L1C_TL_S
GS__20160806T092156_A
005863_T50LKR_N02.04
20170512 20160806 L1C 3/n/a Denpasar 10,
10 13 5.9869
UTM50S/
WGS84 *jp2
12 Bit
u *.safe
4.
S2A_OPER_PRD_MSIL1C_P
DMC_20161025T230615_
R003_V20161025T02175
2_20161025T021752
20170512 20161025 L1C 3/n/a Denpasar 10,
10 13
69.808
2
UTM50S/
WGS84 *jp2
12 Bit
u *.safe
Lineage: ESA Copernicus Open Access Hub
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
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Page 14
1.2 List of In-situ Data N/A
1.3 List of Ancillary Data
Dataset 1 (14)
DEM Incoming
Date
Acquisition
Date
AOI - City / Region /
Country
Data
Type (4)
Data
Format (3)
Projection
/
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Area
Coverage Header / Metadata (2)
SRTM 1arcsec 20170426 11.02.2000 Denpasar Raster *.tif UTM50S
/ WGS84
Horizontal:
CE90 <20m
Vertical:
CE90 <16m
N/A 100% *.mta
Lineage:
The Shuttle Radar Topography Mission (SRTM) was flown aboard the space shuttle Endeavour on February 11 - 22, 2000. The National Aeronautics and
Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA) participated in an international project to acquire radar data which
were used to create detailed topographic maps. SRTM data are intended for scientific use with a Geographic Information System (GIS) or other special
application software. Endeavour orbited Earth 16 times each day during the 11-day mission completing 176 orbits. SRTM successfully collected radar
data over 80% of the Earth's land surface between 60° north and 56° south latitude with data points posted every 1 arc-second (approximately 30
meters).
Source: USGS Earth Explorer https://earthexplorer.usgs.gov/
Dataset 1 (14)
Water Cover Incoming
Date
Acquisition
Date
AOI - City / Region /
Country
Data
Type (4)
Data
Format (3)
Projection
/
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Area
Coverage Header / Metadata (2)
Global Surface Water
Explorer Product 20170502
1984 -
2015 Denpasar / Indonesia Raster *.tif
UTM50S
/ WGS84
RMSE < 30
m.
depending
on
dataset
100% *.xml
Lineage:
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 15
The European Commission’s Joint Research Centre developed this new water dataset in the framework of the Copernicus Programme. This maps the
location and temporal distribution of water surfaces at the global scale over the past 32 years (1984 – 2015) and provides statistics on the extent and
change of those water surfaces. The dataset, produced from Landsat imagery, will support applications including water resource management, climate
modelling, biodiversity conservation and food security. The following six datasets are downloadable: Occurrence, Occurrence change intensity,
Seasonality, Recurrence, Transitions, Maximum water extent. Each of the downloadable files contains a colormap which will display the files in desktop
GIS tools using the symbology that has been used in the Global Surface Water Explorer website.
Source: Joint Research Centre; https://global-surface-water.appspot.com
Dataset 1 (14)
OSM Incoming
Date
Acquisition
Date
AOI - City / Region /
Country
Data
Type (4)
Data
Format (3)
Projection
/
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Area
Coverage Header / Metadata (2)
OSM Street Layer 20170502 N/A Denpasar Vector *.shp UTM50S
/ WGS84 N/A 1 100% N/A
Dataset 1 (14)
OSM Incoming
Date
Acquisition
Date
AOI - City / Region /
Country
Data
Type (4)
Data
Format (3)
Projection
/
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Area
Coverage Header / Metadata (2)
OSM Waterways Layer 20170502 N/A Denpasar Vector *.shp UTM50S
/ WGS84 N/A 1 100% N/A
Lineage: Up-to-date data extracts from the OpenStreetMap project
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 16
Dataset 4 (14)
LULC map Incoming
Date
Acquisition
Date
AOI - City /
Region / Country
Data
Type (4)
Data
Format (3)
Projection
/
Spheroid (16)
Positional
Accuracy (11)
No. of
Classes
Area
Coverage Header / Metadata (2)
Land Use Map 28.08.2017 +/- 2016 Denpasar Shapefile *.shp UTM50S
/ WGS84 85% 27 100% *.mta
Lineage:
Land Use/Land Cover Information was derived from Very High Resolution (VHR) and High Resolution (HR) satellite imagery. The Land Use/Land Cover
(LU/LC) product contains spatial explicit information on the different occurring land use and land cover in both the Core and Peri-Urban areas of the City of
Denpasar for the years 2006 and 2016. The Core area has detailed LU/LC nomenclature whereas the Peri-Urban area LU/LC nomenclature is at an
aggregated Level. The input data for the Core area was Very High Resolution data (Worldview, Quickbird) and the input data for the Peri-Urban area was
HR Sentinel and Landsat data. The LU/LC product is the Baseline Product from which various derived products are produced.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 17
2.1 EO Data Quality
Sensor 1 (8) Landsat 5
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2
)
Band Specifications
Pro
jecti
on
/ S
ph
ero
id (
16
)
Sce
ne
Lo
ca
tio
n
Co
mp
lete
ne
ss o
f
Ad
dit
ion
al D
ata
Da
ta F
orm
at
(3)
Bit
De
pth
(5
)
Clo
ud
Co
ve
r (i
nte
rna
l
ch
eck
)
Ra
dio
me
try
To
po
gra
ph
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7
)
Acce
pta
nce
Sta
tus
Comments File Name
No
. o
f B
an
ds
Ba
nd
Re
gis
tra
tio
n
Sp
ectr
al/
Sp
ati
al
Re
so
luti
on
1. LT51160661997151DKI00 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
2. LT51160661999317DKI00 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
3. LT51160662000064DKI00 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
Sensor 2 (8) Landsat 8 B
ack
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2)
Band Specifications
Pro
jecti
on
/ S
ph
ero
id (
16
)
Sce
ne
Lo
ca
tio
n
Co
mp
lete
ne
ss o
f
Ad
dit
ion
al D
ata
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Clo
ud
Co
ve
r (i
nte
rna
l
ch
eck
)
Ra
dio
me
try
To
po
gra
ph
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7)
Acce
pta
nce
Sta
tus
Comments File Name
No
. o
f B
an
ds
Ba
nd
Re
gis
tra
tio
n
Sp
ectr
al/
Sp
ati
al
Re
so
luti
on
1. LC81160662013115LGN02 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
2. LC81160662013307LGN01 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
3. LC81160662014006LGN01 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
4. LC81160662015105LGN01 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
5. LC81160662016012LGN02 Y - Q Y - V Y- V Y - V Q Y – V Q Y - Q Y - V Y - V Y - V Q Y - Q Y - Q Y - V Q Y - V Q Y - V N - V Q Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 18
Sensor 3 (8)
Sentinel 2
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/ M
eta
da
ta
(2)
Band Specifications
Pro
jecti
on
/ S
ph
ero
id (
16
)
Sce
ne
Lo
ca
tio
n
Co
mp
lete
ne
ss o
f
Ad
dit
ion
al D
ata
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Clo
ud
Co
ve
r (i
nte
rna
l
ch
eck
)
Ra
dio
me
try
To
po
gra
ph
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7
)
Acce
pta
nce
Sta
tus
Commen
ts File Name
No
. o
f B
an
ds
Ba
nd
Re
gis
tra
tio
n
Sp
ectr
al/
Sp
ati
al
Re
so
luti
on
1. S2A_OPER_MSI_L1C_TL_EPA__
20161213T095422_A001716_
T50LKR_N02.04
Y -
Q
Y -
V
Y-
V
Y - V
Q Y – V
Q
Y -
Q
Y -
V
Y -
V
Y - V
Q Y -
Q Y -
Q Y - V
Q Y - V
Q Y -
V N - V
Q Ye
s none
2. S2A_OPER_MSI_L1C_TL_SGS__
20151230T091952_A002717_
T50LKR_N02.01
Y -
Q
Y -
V
Y-
V
Y - V
Q Y – V
Q
Y -
Q
Y -
V
Y -
V
Y - V
Q Y -
Q Y -
Q Y - V
Q Y - V
Q Y -
V N - V
Q Ye
s none
3. S2A_OPER_MSI_L1C_TL_SGS__
20160806T092156_A005863_
T50LKR_N02.04
Y -
Q
Y -
V
Y-
V
Y - V
Q Y – V
Q
Y -
Q
Y -
V
Y -
V
Y - V
Q Y -
Q Y -
Q Y - V
Q Y - V
Q Y -
V N - V
Q Ye
s none
4.
S2A_OPER_PRD_MSIL1C_PDMC_
20161025T230615_R003_V20161025T02
1752_
20161025T021752
Y -
Q
Y -
V
Y-
V
Y - V
Q Y – V
Q
Y -
Q
Y -
V
Y -
V
Y - V
Q Y -
Q Y -
Q Y - V
Q Y - V
Q Y -
V N - V
Q Ye
s none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 19
2.3 Ancillary Data Quality
Dataset 1 (14) DEM
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2)
Ext
en
t
Pro
jecti
on
/ S
ph
ero
id
(16
)
Sp
ati
al R
eso
luti
on
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Lo
ca
tio
n
Co
mp
lete
ne
ss
Ge
om
. M
isa
lign
me
nt
Pla
usib
ilit
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7)
Acce
pta
nce
Sta
tus
Comments File Name
SRTM1S09E115V3 Y - Q Y - Q Y - Q Y - V Y - Q Y - Q Y - Q Y - Q Y - V Q Y - V N - V Y - V N - V Yes none
Dataset 2 (14)
Global Surface
Water Explorer
Product
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2
)
Ext
en
t
Pro
jecti
on
/ S
ph
ero
id (
16
)
Sp
ati
al R
eso
luti
on
Da
ta F
orm
at
(3)
Bit
De
pth
(5
)
Lo
ca
tio
n
Co
mp
lete
ne
ss
Ge
om
. M
isa
lign
me
nt
Pla
usib
ilit
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7
)
Acce
pta
nce
Sta
tus
Comments
File Name
change.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
extent.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
occurrence.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
recurrence.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
seasonality.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
transitions.tif Y - Q Y - V Y - V Q Y - V Y - V Y - Q Y - Q Y - Q Y - V Y - V Q N - V Q Y - V N - V Q Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 20
Dataset 3 (14) OSM
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2)
Ext
en
t
Pro
jecti
on
/ S
ph
ero
id
(16
)
Sp
ati
al R
eso
luti
on
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Lo
ca
tio
n
Co
mp
lete
ne
ss
Ge
om
. M
isa
lign
me
nt
Pla
usib
ilit
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7)
Acce
pta
nce
Sta
tus
Comments File Name
gis.osm_roads_free_1.shp Y - Q Y - Q N/A Y – V Q Y - Q N/A Y - Q N/A Y - V Q Y - V N - V Y - V N - V Yes none
gis.osm_waterways_free_1 Y - Q Y - Q N/A Y – V Q Y - Q N/A Y - Q N/A Y - V Q Y - V N - V Y - V N - V Yes none
Dataset 4 (14) Land Use
Ba
ck
up
Re
ad
ab
ilit
y (1
)
Ch
eck
He
ad
er
/
Me
tad
ata
(2)
Ext
en
t
Pro
jecti
on
/ S
ph
ero
id
(16
)
Sp
ati
al R
eso
luti
on
Da
ta F
orm
at
(3)
Bit
De
pth
(5)
Lo
ca
tio
n
Co
mp
lete
ne
ss
Ge
om
. M
isa
lign
me
nt
Pla
usib
ilit
y
Dro
pp
ed
Lin
es /
Art
efa
cts
(7)
Acce
pta
nce
Sta
tus
Comments Land Use/Land Cover Information
Denpasar_WB_LULC_2006_2016_Total_2_2.shp Y - Q Y - Q Y - Q Y - V Y - Q NA Y - Q NA Y - V Q Y - V N - V Y - V N - V Yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 21
3.1 Geometric Correction
Sensor 1 (8) Landsat 5
Pro
ce
ssin
g D
ate
AO
I
Cit
y / R
egio
n /
Co
un
try
Pro
jecti
on
/ S
ph
ero
id (
16
)
No
. &
RM
S (
m)
of
GC
Ps (
17
)
No
. &
RM
S (
m)
of
TP
s (
18
)
No
. &
RM
S (
m)
of
CP
s (
19
)
Dig
ita
l E
leva
tio
n M
od
el
(DE
M)
Mo
de
l / A
lgo
rith
m (
13
)
Re
sa
mp
lin
g
Me
tho
d (
20
)
Va
lid
ati
on
Re
po
rts
Acce
pta
nce
Sta
tus
Output File Name No. File Name
1. LT51160661997151DKI00 Landsat 5 Imagery was downloaded as Level 1 TP Products
(radiometrically calibrated and orthorectified),
refer to https://landsat.usgs.gov/geometry
2. LT51160661999317DKI00
3. LT51160662000064DKI00
Sensor 2 (8) Landsat 8
Pro
ce
ssin
g D
ate
AO
I
Cit
y / R
egio
n /
Co
un
try
Pro
jecti
on
/ S
ph
ero
id (
16
)
No
. &
RM
S (
m)
of
GC
Ps (
17
)
No
. &
RM
S (
m)
of
TP
s (
18
)
No
. &
RM
S (
m)
of
CP
s (
19
)
Dig
ita
l E
leva
tio
n M
od
el
(DE
M)
Mo
de
l / A
lgo
rith
m (
13
)
Re
sa
mp
lin
g
Me
tho
d (2
0)
Va
lid
ati
on
Re
po
rts
Acce
pta
nce
Sta
tus
Output File Name No. File Name
1. LC81160662013115LGN02
Landsat 8 Imagery was downloaded as Level 1 TP Products
(radiometrically calibrated and orthorectified),
refer to https://landsat.usgs.gov/geometry
2. LC81160662013307LGN01
3. LC81160662014006LGN01
4. LC81160662015105LGN01
5. LC81160662016012LGN02
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 22
Sensor 3 (8) Sentinel 2
Pro
ce
ssin
g D
ate
AO
I
Cit
y / R
egio
n /
Co
un
try
Pro
jecti
on
/ S
ph
ero
id (
16
)
No
. &
RM
S (
m)
of
GC
Ps (
17
)
No
. &
RM
S (
m)
of
TP
s (
18
)
No
. &
RM
S (
m)
of
CP
s (
19
)
Dig
ita
l E
leva
tio
n M
od
el
(DE
M)
Mo
de
l / A
lgo
rith
m (
13
)
Re
sa
mp
lin
g
Me
tho
d (2
0)
Va
lid
ati
on
Re
po
rts
Acce
pta
nce
Sta
tus
Output File Name No. File Name
1.
S2A_OPER_MSI_L1C_TL_EPA__
20161213T095422_A001716_
T50LKR_N02.04
Sentinel 2 Imagery was downloaded as Level 1C Products.
Level-1C processing includes radiometric and geometric corrections including ortho-rectification
and spatial registration on a global reference system with sub-pixel accuracy.
(refer to https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/processing-levels/level-1)
2.
S2A_OPER_MSI_L1C_TL_SGS__
20151230T091952_A002717_
T50LKR_N02.01
3.
S2A_OPER_MSI_L1C_TL_SGS__
20160806T092156_A005863_
T50LKR_N02.04
4.
S2A_OPER_PRD_MSIL1C_PDMC_
20161025T230615_R003_V20161025T021752_
20161025T021752
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 23
3.1.1 Data Fusion
Natural colour and false colour composites were produced from all EO data listed in Section 1.1., merging visible bands (R, G, B) and NIR band
3.2 Data Processing
Sensor 1 (8) Landsat 5 Atmospheric
Correction
Radiometric
Processing (15)
Topographic
Normalisation
OTHER
Calculation:
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment
No. File Name Processing
Date
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
1. LT51160661997151DKI00 20170518 Yes QGIS/DOS1 No downloaded
Level 1 TP
Products
radiometrically
calibrated
No topographic
effects in
flood-prone
areas
negligible
No N/A Yes Yes none
2. LT51160661999317DKI00 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
3. LT51160662000064DKI00 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
Sensor 2 (8) Landsat 8 Atmospheric
Correction
Radiometric
Processing (15)
Topographic
Normalisation
OTHER
Calculation:
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment
No. File Name Processing
Date
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
1. LC81160662013115LGN02 20170518 Yes QGIS/DOS1 No downloaded
Level 1 TP
Products
radiometrically
calibrated
No topographic
effects in
flood-prone
areas
negligible
No N/A Yes Yes none
2. LC81160662013307LGN01 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
3. LC81160662014006LGN01 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
4. LC81160662015105LGN01 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
5. LC81160662016012LGN02 20170518 Yes QGIS/DOS1 No No No N/A Yes Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 24
Sensor 3 (8)
Sentinel 2 Atmospheric
Correction
Radiometric
Processing (15)
Topographic
Normalisation
OTHER
Calculation:
Acce
pta
nce
Sta
tus
Ba
ck
up
Commen
t No. File Name
Processing
Date
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Softwar
e /
Method
1.
S2A_OPER_MSI_L1C_TL_EPA__
20161213T095422_A001716_
T50LKR_N02.04
2017051
9
Ye
s
QGIS/DOS
1
N
o
downloaded
Level 1C
Products
radiometricall
y calibrated
N
o
topographi
c effects in
flood-prone
areas
negligible
N
o N/A
Ye
s
Ye
s none
2.
S2A_OPER_MSI_L1C_TL_SGS__
20151230T091952_A002717_
T50LKR_N02.01
2017051
9
Ye
s
QGIS/DOS
1
N
o
N
o
N
o N/A
Ye
s
Ye
s none
3.
S2A_OPER_MSI_L1C_TL_SGS__
20160806T092156_A005863_
T50LKR_N02.04
2017051
9
Ye
s
QGIS/DOS
1
N
o
N
o
N
o N/A
Ye
s
Ye
s none
4.
S2A_OPER_PRD_MSIL1C_PDMC_
20161025T230615_R003_V20161025T021752
_
20161025T021752
2017051
9
Ye
s
QGIS/DOS
1
N
o
N
o
N
o N/A
Ye
s
Ye
s none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 25
4.1 Classification
Sensor 1 (8) Landsat 5
Processing
Date
Cloud Masking Thematic
Classification
Manual
Enhancement Mosaicking
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment
No. File Name
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
1. LT51160661997151DKI00 20170520 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
2. LT51160661999317DKI00 20170520 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
3. LT51160662000064DKI00 20170520 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
Sensor 2 (8) Landsat 8
Processing
Date
Cloud Masking Thematic
Classification
Manual
Enhancement Mosaicking
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment
No. File Name
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
1. LC81160662013115LGN02 20170520 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
2. LC81160662013307LGN01 20170520 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
3. LC81160662014006LGN01 20170520 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
4. LC81160662015105LGN01 20170520 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
5. LC81160662016012LGN02 20170520 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 26
Sensor 3 (8) Sentinel 2
Processing
Date
Cloud Masking Thematic
Classification
Manual
Enhancement Mosaicking
Acce
pta
nce
Sta
tus
Ba
ck
up
Comment
No. File Name
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
pro
ce
sse
d
Software /
Method
1.
S2A_OPER_MSI_L1C_TL_EPA__
20161213T095422_A001716_
T50LKR_N02.04
20170522 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
2.
S2A_OPER_MSI_L1C_TL_SGS__
20151230T091952_A002717_
T50LKR_N02.01
20170522 No N/A Yes
ArcGIS 10 /
AWEI-
calculation
No N/A No N/A Yes Yes none
3.
S2A_OPER_MSI_L1C_TL_SGS__
20160806T092156_A005863_
T50LKR_N02.04
20170522 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
4.
S2A_OPER_PRD_MSIL1C_PDMC_
20161025T230615_R003_V20161025T021752_
20161025T021752
20170522 Yes ArcGIS 10 /
manual Yes
ArcGIS 10 /
AWEI-
calculation
No N/A Yes
ArcGIS 10 /
Mosaic
Dataset
Yes Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 27
5.1 Thematic Accuracy
Qualitative (visual) Comparison of Water Extents based on Automated Water Extraction Index (AWEI) with Source Imagery
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 28
5.2 Error Matrices
Class No Reference Data
Totals
1 2
Water Extent
20150415
No water
cover
water
cover
1 No
water
cover
35 1
36
2 water
cover 2 34 36
Totals 37 35 72
Accuracy Statistics z= 1,96
Overall
Accuracy: 95,83%
95%
Confidence
Interval:
N/A N/A
Kappa
(Cohen): 0,91667
Class Name Producer
Accuracy
95% Confidence
Interval
User
Accuracy 95% Confidence Interval
Class 1 94,59% N/A N/A 97,22% N/A N/A
Class 2 97,14% N/A N/A 94,44% N/A N/A
Class No Reference Data
Totals
1 2
Water Extent
20151024
No water
cover
water
cover
1 No
water
cover
34 2
36
2 water
cover 5 31 36
Totals 39 33 72
Accuracy Statistics z= 1,96
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 29
Overall
Accuracy: 90,28%
95%
Confidence
Interval:
N/A N/A
Kappa
(Cohen): 0,80556
Class Name Producer
Accuracy
95% Confidence
Interval
User
Accuracy 95% Confidence Interval
Class 1 87,18% N/A N/A 94,44% N/A N/A
Class 2 93,94% N/A N/A 86,11% N/A N/A
Class No Reference Data
Totals
1 2
Water Extent
20161025
No water
cover
water
cover
1 No
water
cover
36 0
36
2 water
cover 2 34 36
Totals 38 34 72
Accuracy Statistics z= 1,96
Overall
Accuracy: 97,22%
95%
Confidence
Interval:
N/A N/A
Kappa
(Cohen): 0,94444
Class Name Producer
Accuracy
95% Confidence
Interval
User
Accuracy 95% Confidence Interval
Class 1 94,74% N/A N/A 100,00% N/A N/A
Class 2 100,00% N/A N/A 94,44% N/A N/A
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No part of these pages, either text or image may be used for any purpose other than
use in the EO4SD-Urban Project. Therefore, reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or otherwise, for reasons other than
personal use, is strictly prohibited without prior written permission
Page 30
6.1 Completeness
INPUT DATA
No. Item AOI Coverage
[km²]
Area Coverage
[km²]
Completeness of
Coverage (25) No. of Scenes
Scenes used in
Production
Completeness of
Verification (27) Metadata Comments
1. HR EO Data
Denpasar
peri-urban
(540,94 km²)
540,94 km² 100% 12 3 100% Yes none
2. VHR EO Data 141,51 km² 26,2 % 3 0 N/A Yes none
3. In-situ Data N/A N/A N/A N/A N/A N/A none
4. Ancillary Data 540,94 km² 100 % N/A N/A N/A Yes none
PRODUCTS
No. Product (28) AOI Coverage
[km²]
Product
Coverage
[km²]
Completeness of
Coverage (25)
Completeness of
Classification (26)
Unclassifiable
Area [%]
Completeness of
Verification (27) Metadata Comments
1. Water Extent
Denpasar
Denpasar
peri-urban
(540,94 km²)
540,94 km² 100% 100% N/A 100% Yes none
2. Flood History
River Floods
Denpasar urban
(141,51 km²) 141,51 km² 100% 100% N/A N/A Yes none
3. Flood Hazard
River Floods
Denpasar
peri-urban
(540,94 km²)
540,94 km² 100% 100% N/A N/A Yes none
4.
Flood Hazard
Denpasar
Combined
Denpasar
peri-urban
(540,94 km²)
540,94 km 100% 100% N/A N/A Yes none
5.
Flood Risk
Classification
Denpasar
Denpasar
peri-urban
(540,94 km²)
540,94 km 100% 100% N/A N/A Yes none
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 31
6.2 Compliancy
Product 1 (28) Water Extent Denpasar
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
No relevant increase of permanent and seasonal water cover can be observed for the period from 1984
to 2015 according to the Global Surface Water Explorer Product (Joint Research Centre), based on
Landsat Imagery.
For demonstration purposes, water extents of recent dates as derived from HR EO data are included in
the present Geodatabase.
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia/Denpasar Country 1: Indonesia/Denpasar yes
A) Wall-to-wall: A) Wall-to-wall: yes
Urban and peri-urban area Urban and peri-urban area
Test area of approx. 540,94 km², defined by the national user.
B) Sampling based: B) Sampling based: N/A
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s): yes
2000 2000
B) Update Frequency B) Update Frequency
Update Frequency depending on frequency of flooding events
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
WGS84 / UTM 50S WGS84 / UTM 50S yes
Mapping Classes and Definitions
Requirements Achieved Specifications Compliancy
Class 1: Extent of flooding Class 1: Extent of flooding yes
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
Cloud covered areas shall be
removed.
Data selection was aiming at low cloud
coverage in flood exposed areas.
Relevant clouds manually digitized and
replaced using additional EO data.
yes
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
10m – 30 m 10 m – 30 m yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 32
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
0.5 ha 0.1 ha yes
Data Type
Requirements Achieved Specifications Compliancy Comments
Thematic Vector or Raster File Thematic Vector File yes
Bit Depth
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile yes
Class Coding
Requirements Achieved Specifications Compliancy
0 = No Water Cover 0 = No Water Cover yes
1 = Water Cover 1 = Water Cover yes
Metadata
Requirements Achieved Specifications Compliancy Comments
not specified not specified N/A
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
Overall Accuracy: > 80% Overall Accuracy: > 80% yes
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
RMSE < 30 m RMSE < 30 m yes
Delivery Procedure
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP online via FTP yes
Delivery Date
Requirements Achieved Specifications Compliancy Comments
End of May 2017 31.05.2017 yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 33
Product 2 (28) Flood History River Floods
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
To overcome this shortcoming, point data of reported and localized urban floods (2008 – 2017) are
included in this product.
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia/Denpasar Country 1: Indonesia/Denpasar yes
A) Wall-to-wall: A) Wall-to-wall: yes
Urban area Urban area
Test area of approx. 141,51 km², defined by the national user.
B) Sampling based: B) Sampling based: N/A
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s): N/A
not specified 2008 - 2017
B) Update Frequency B) Update Frequency
Update Frequency depending on frequency of flooding events
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
WGS84 / UTM 50S WGS84 / UTM 50S yes
Mapping Classes and Definitions
Requirements Achieved Specifications Compliancy
Class 1: Localization and date of flooding Class 1: Localization and date of flooding yes
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 34
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Type
Requirements Achieved Specifications Compliancy Comments
Thematic Vector or Raster File Thematic Vector File yes
Bit Depth
Requirements Achieved Specifications Compliancy Comments
N/A N/A
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile yes
Class Coding
Requirements Achieved Specifications Compliancy
1 = Localization and date of flooding 1 = Localization and date of flooding yes
Metadata
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Delivery Procedure
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP online via FTP yes
Delivery Date
Requirements Achieved Specifications Compliancy Comments
End of May 2017 31.05.2017 yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 35
Product 3 (28) Flood Hazard River Floods
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical.
The present Geodatabase includes two shp-files for rough estimation of potential flooding zones:
a. Denpasar_Flood_Hazard_Rivers
Waterways were taken from OSM Layer and complemented by hydrologic modelling of potential
catchment areas and flow routes based on SRTM and visual interpretation of VHR data. After
classification in two classes based on Stream Order the lines were buffered with 50 m and 100 m
respectively to roughly estimate potential flooding zones.
b. Denpasar_Flood_Reports_buff200
Point data of reported and localized urban floods (2008 – 2017) were buffered with 200 m to roughly
estimate potential flooding hot-spots
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia/Denpasar Country 1: Indonesia/Denpasar yes
A) Wall-to-wall: A) Wall-to-wall: yes
Peri-urban area Peri-urban area
Test area of approx. 540,94 km², defined by the national user.
B) Sampling based: B) Sampling based: N/A
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s): N/A
not specified 2008 - 2017
B) Update Frequency B) Update Frequency
Update Frequency depending on frequency of flooding events
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
WGS84 / UTM 50S WGS84 / UTM 50S yes
Mapping Classes and Definitions
Requirements Achieved Specifications Compliancy
1: Potential flooding zones close to
rivers and waterways 1:
Potential flooding zones close to rivers
and waterways yes
2 Potential flooding hot-spots 2 Potential flooding hot-spots yes
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 36
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Type
Requirements Achieved Specifications Compliancy Comments
Thematic Vector or Raster File Thematic Vector File yes
Bit Depth
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile yes
Class Coding
Requirements Achieved Specifications Compliancy
Potential flooding zones close to rivers and waterways Potential flooding zones close to rivers and
waterways yes
Potential flooding hot-spots Potential flooding hot-spots yes
Metadata
Requirements Achieved Specifications Compliancy Comments
not specified not specified N/A
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Delivery Procedure
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP online via FTP yes
Delivery Date
Requirements Achieved Specifications Compliancy Comments
End of May 2017 31.05.2017 yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 37
Product 4 (28) Flood Hazard Denpasar Combined
Abstract
For the Denpasar area short-term flooding close to rivers and waterways in the rainy season (November
– March) is typical. Even though Denpasar is prone to flooding according to available local sources, this
cannot be confirmed by the analysis of EO data.
No relevant increase of permanent and seasonal water cover can be observed for the period from 1984
to 2015 according to the Global Surface Water Explorer Product (Joint Research Centre), based on
Landsat Imagery.
As land subsidence is expected in Denpasar due to observed decrease in groundwater level coastal
lowlands are classified as flood prone at a distance of 200 m. This does not include Tsunami flooding.
The flood hazard map is taking into account all available data sources (EO based flood extents, reports
and press releases, results of modelling of potential flooding along rivers and waterways, ancillary data)
aiming at covering all types of floods and thus all areas which are potentially endangered by flooding.
The classification in three qualitative hazard levels is expert-based under consideration of observed and
reported frequencies of floods.
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia/Denpasar Country 1: Indonesia/Denpasar yes
A) Wall-to-wall: A) Wall-to-wall: yes
Peri-urban area Peri-urban area
Test area of approx. 540,94 km², defined by the national user.
B) Sampling based: B) Sampling based: N/A
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s): N/A
not specified 2008 - 2017
B) Update Frequency B) Update Frequency N/A
N/A N/A
Update Frequency depending on frequency of flooding events
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
WGS84 / UTM 50S WGS84 / UTM 50S yes
Mapping Classes and Definitions
Requirements Achieved Specifications Compliancy
1 low hazard 1 low hazard yes
2 medium hazard 2 medium hazard yes
3 high hazard 3 high hazard yes
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
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Page 38
Vector file Vector file yes
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Type
Requirements Achieved Specifications Compliancy Comments
Thematic Vector or Raster File Thematic Vector File yes
Bit Depth
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile yes
Class Coding
Requirements Achieved Specifications Compliancy
low hazard: RGB Code 255-255-115 low hazard: RGB Code 255-255-115 yes
medium hazard: RGB Code 255-211-127 medium hazard: RGB Code 255-211-127 yes
high hazard: RGB Code 255-127-127 high hazard: RGB Code 255-127-127 yes
Metadata
Requirements Achieved Specifications Compliancy Comments
ISO compliant ISO compliant yes
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
Not specified – depends on
available input data N/A N/A
Delivery Procedure
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP online via FTP yes
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 39
Delivery Date
Requirements Achieved Specifications Compliancy Comments
End of May 2017 15.09.2017 no
Product 5 (28) Flood Risk Classification Denpasar
Abstract
Risk is defined as a combination of probability and consequences. A detailed and uniform land-use map
is an important prerequisite to perform flood risk calculations, since it determines what is damaged in
case of flooding. The land-use map was provided by GAF AG and recoded to pre-defined categories to
ensure consistent results.
The exposition is classified integrating economic costs, social damage, physical damage and flood
duration. Four land use damage levels (A, B, C, D) are defined based on this estimation.
The Flood Risk matrix is generated based on these results code and on flood hazard classified into three
hazard levels. The flood risk level is classified in four qualitative classes based on the combination of
flood hazard and land use damage.
Service / Product Specifications
Area Coverage
Requirements Achieved Specifications Compliancy Comments
Country 1: Indonesia/Denpasar Country 1: Indonesia/Denpasar yes
A) Wall-to-wall: A) Wall-to-wall: yes
Peri-urban area Peri-urban area
Test area of approx. 540,94 km², defined by the national user.
B) Sampling based: B) Sampling based: N/A
N/A N/A
Time Period - Update Frequency
Requirements Achieved Specifications Compliancy Comments
Baseline Year(s): Baseline Year(s): N/A
not specified 2008 - 2017
B) Update Frequency B) Update Frequency N/A
not specified N/A
depends on frequency of flooding events and on availability of land-use classification (5 to 7 years)
Geographic Reference System
Requirements Achieved Specifications Compliancy Comments
WGS84 / UTM 50S WGS84 / UTM 50S yes
Mapping Classes and Definitions
Requirements Achieved Specifications Compliancy
1 low risk 1 low risk yes
2 medium risk 2 medium risk yes
3 high risk 3 high risk yes
4 very high risk 4 very high risk yes
Cloud and Shadow Detection and Removal
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 40
Spatial Resolution
Requirements Achieved Specifications Compliancy Comments
Vector file Vector file yes
Minimum Mapping Unit (MMU)
Requirements Achieved Specifications Compliancy Comments
0.25 ha for the urban area, 0.5 ha
for the peri-urban area.
0.25 ha for the urban area, 0.5 ha for
the peri-urban area. yes
same as landuse / landcover classification
Data Type
Requirements Achieved Specifications Compliancy Comments
Thematic Vector or Raster File Thematic Vector File yes
Bit Depth
Requirements Achieved Specifications Compliancy Comments
N/A N/A N/A
Data Format
Requirements Achieved Specifications Compliancy Comments
*.shp Shapefile Shapefile yes
Class Coding
Requirements Achieved Specifications Compliancy
low risk: RGB Code 255-255-190 low risk: RGB Code 255-255-190 yes
medium risk: RGB Code 255-211-127 medium risk: RGB Code 255-211-127 yes
high risk: RGB Code 255-170-0 high risk: RGB Code 255-170-0 yes
very high risk: RGB Code 255-0-0 very high risk: RGB Code 255-0-0 yes
Metadata
Requirements Achieved Specifications Compliancy Comments
ISO compliant ISO compliant yes
Service / Product Quality
Thematic Accuracy
Requirements Achieved Specifications Compliancy Comments
not specified depends on available input data N/A
Positional Accuracy
Requirements Achieved Specifications Compliancy Comments
depends on available input data N/A
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 41
Not specified – depends on
available input data
Delivery Procedure
Service Provision
Requirements Achieved Specifications Compliancy Comments
online via FTP online via FTP yes
Delivery Date
Requirements Achieved Specifications Compliancy Comments
End of May 2017 15.09.2017 no
Glossary
Quality Checks
Prefix Suffix Explanation
Y (Yes) - V Visually checked
N (No) - Q Quantitatively/qualitatively checked
N/A - V Q Visually and quantitatively/qualitatively checked
- N/A Not applicable
Readability (1) Check readability of all required input data. Can the data be stored again?
Header / Metadata (2) Check Image Header Information and/or Metadata for completeness / distinctive
features.
Data Format (3) For digital data, please give file format (e.g. *.tiff, *.shp).
Data Type (4) Please specify the type of the data (e.g. raster, vector or analogue).
Bit Depth (5) Please give pixel depth and sign of raster data (e.g. 8 bit unsigned integer).
Dynamic Range (6) Check dynamic range of all image bands. Visual check of dynamic range should be
accompanied by histograms and statistics.
Dropped Lines & Artefacts (7) Check Image for dropped lines and other artefacts. If such occurs, please give
description of extent and influence in the Comments section.
Sensor 1, 2, … (8) Please delete / add additional sensor sections as necessary.
Purpose (9)
The purpose and use of the given auxiliary or reference data should be stated:
ORHTOrectification, GEOmetric correction, REFerence, VERification source,
POSitional ACCuracy assessment, THEmatic ACCuracy assessment.
Sampling Methodology (10)
Methodology of in situ or reference/auxiliary data sampling scheme should be
outlined. In case of sample plots, also state how the plot positions have been
determined (e.g. from GPS measurements, topographic maps, terrestrial
triangulation, EO data, etc.) and how the sampling grid was established.
Positional Accuracy (11)
Positional accuracy of collected in situ data should be given. For reference/auxiliary
data it MUST be given. If unknown, the data’s use must be explained. For DEM or
other data with 3D information please specify both vertical and horizontal Positional
Accuracy. For analogue data (e.g. maps) try to give approximate accuracy related to
mapping scale.
Completeness (12) Data should be checked for spatial/temporal/content gaps.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 42
Model / Algorithm (13)
Give the name of the software and its version. Specify the software
module/algorithm used for: a) geometric correction, e.g., Polynomial and its degree,
Rational Functions, Thin Plate Spline, etc.
b) classification, e.g., ISODATA, Maximum Likelihood, Neural Networks, etc.
Dataset 1, 2, … (14) Please delete / add additional dataset sections as necessary.
Radiometric Processing (15)
State whether (and which) radiometric processing was applied (e.g., contrast
enhancement, histogram matching, bundle block adjustment, radiometric
normalisation, filtering, etc.).
Projection; Spheroid /
Ellipsoid (16)
Always specify completely, i.e. at minimum the Projection (+Zone, if applicable),
Spheroid / Ellipsoid, Map Datum. Give additional information if necessary to
unambiguously define the reference system.
Ground Control Points (GCPs) (17)
Give the number, distribution and RMS of used Ground Control Points (as average
per scene) as obtained from the Geometric Correction, in meters [m]. Optionally, also
RMSx and RMSy may be given. Distribution of GCPs should be attached as a
snapshot, or described in the Comments section.
Tie Points (TPs) (18)
In case of mosaicking, give the number of used Tie Points and their total RMS (as
average per scene) as obtained from the Geometric Correction, in meters [m].
Optionally, also RMSx and RMSy may be given. Distribution of TPs should be
attached as a snapshot, or described in the Comments section.
Check Points (CPs) (19)
The real measure of positional accuracy and the only measure which should be
examined as to its Acceptable Range. Give the independent Check Points’ total RMS
(as average per scene) as obtained from the Geometric Correction, in meters [m].
Optionally, also RMSx and RMSy may be given. Distribution of CP's should be
attached as a snapshot, or described in the Comments section.
Resampling Method (20) Specify, if / which resampling algorithm has been used (e.g. NN=Nearest Neighbour,
BIL=Bilinear Interpolation, CC=Cubic Convolution).
Sampling unit (21) Specify sampling unit of Accuracy Assessment as POINT, FRAME, POLYGON and how
it is treated (e.g. pixel center, polygon centre, etc.).
Sampling Design (22) SYST=Systematic, RAND=Random, STRAT=Stratified, SBCLASS=Stratified by class,
SBAREA=Stratified by area
Sample exclusion criteria (23)
Describe which criteria you apply for sampling point selection resp. exclusion of
certain points. For example, if the point is too close to a class boundary (less than 1
pixel), it is excluded. If the selected sample point is not representative of the class , it
is excluded. For these reasons, it is recommended to oversample by 10% to
compensate for sample point exclusion.
Thematic Accuracy (24)
Provide a detailed description of the Accuracy Assessment results in the form of
error matrices showing commission and omission errors, user’s , producer’s and
overall accuracies and other measures of Thematic Accuracy, as the confidence
level (usually fixed at 95%) and the respective confidence interval, at least for the
overall accuracy. If classification is done in a phased approach, e.g. if Forest Area
and subsequently Forest Type are mapped, independent reports have to be
produced.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 43
Completeness of Coverage (25) State whether the coverage is limited to a subset, or portion of the final product.
Completeness of
Classification (26)
State whether classification was constrained to a subset, or portion of the final
product.
Completeness of Verification (27)
State whether verification applied to lineage, positional, or thematic accuracy is
constrained to a subset, or portion of the final product.
Product (28) Please delete / add additional product sections as necessary.
Earth Observation for Sustainable
Development – Urban Project QA/QC Sheets developed by GAF AG
© 2017 GAF AG All Rights Reserved. Unless otherwise indicated, the templates of these QA/QC pages are copyrighted by GAF AG. No
part of these pages, either text or image may be used for any purpose other than use in the EO4SD-Urban Project. Therefore,
reproduction, modification, storage in a retrieval system or retransmission, in any form or by any means, electronic, mechanical or
otherwise, for reasons other than personal use, is strictly prohibited without prior written permission
Page 44