part a: introduction to the use case · • burn scar mapping shapefiles ¾deied fom hr and vhr...
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Use Case IIUse Case IIReal-time fire monitoring
Part A: Introduction to the Use Case
2nd User workshopDarmstadt, 10-11 May 2012Darmstadt, 10 11 May 2012
P t H i K t & I i P t i (NOA)Presenters: Haris Kontoes & Ioannis Papoutsis (NOA)
GMES: Global Monitoring for Environment and SecurityBackground - GMES
The objective is to provide Earth Observation = satellite i f ti i t li d d i i kinformation services to policy and decision-makers
EARTH OBSERVATION PUBLIC
Satellite ImagesInformationOBSERVATION
SYSTEMS(satellite images,
PUBLICPOLICIES
(Environment & aerial photographs,
in-situ data)
(Security)Needs
(user driven)
Space AgenciesIn-situ Observing systems Scientific
National Governments and AgenciesEuropean Union Institutions
CommunityEO Value Adding Industry
Inter-Governmental Organisations (IGOs) Non Governmental Organisations (NGOs)
5/10/2012
Background - GMES
Space SystemsSpace SystemsSpace SystemsSpace Systems
Obser ational Net orksObser ational Net orksObser ational Net orksObser ational Net orks
Mission OperationsMission OperationsMission OperationsMission Operations
Observational NetworksObservational NetworksObservational NetworksObservational NetworksData CentersData CentersData CentersData Centers
GMESCore Services es
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Land
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Urban AtlasUrban AtlasE
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Downstream ServicesDownstream ServicesDownstream ServicesDownstream Services5/10/2012
SAFER - LinkER ERS projects rationale
The projects SAFER - LinkER aims to implement and validate a preoperationalp j p p pversion of the GMES Emergency Response Service, reinforcing the Europeancapacity to respond to such challenges
First priority: Validate an information i f i id i
SHORT-TERMUPGRADES
MID AND LONGER-TERMUPGRADES
SHORT-TERMUPGRADES
MID AND LONGER-TERMUPGRADES
service focusing on rapid mappingduring the response phase
Second priority: Enrich this service
UPGRADES
MID AND
UPGRADES
MID AND Second priority: Enrich this service with a wider set of thematic products
LONGER-TERM
UPGRADES
LONGER-TERM
UPGRADES
In the long term, ERCS provide tangible benefits for all citizens, in Europe andworldwide, in terms of better quality of life, better health, and increased safety.
5/10/2012
Fire monitoring applicationAvailable datasets
NOA hotspot service
• Raw data
Available datasets
Raw data
• Intermediate products
• Hotspots
MSG2 (15 minutes) & MSG1_RSS (5 minutes)
Ready products
• FMM-1 hotspot shapefiles & kml
Derived from MSG/SEVIRI on a 15 minutes basis Available in the Derived from MSG/SEVIRI, on a 15 minutes basis
Derived from MODIS, 2-3 times per day
• FMM-2 burnt area shapefiles & kml
Available in the framework of SAFER
Derived from MODIS, on a daily basis
• Burn Scar Mapping shapefiles
De i ed f om HR and VHR senso s on a seasonal basisDerived from HR and VHR sensors, on a seasonal basis
Auxiliary datasets
• GIS layers: administrative boundaries, road network, places of interest & toponymsy , , p p y
• Digital Elevation Model (DEM)
• CORINE Land Cover raster and vector layers
• Background mosaic, derived from LANDSAT 5 TM images
5/10/2012 5
Dataset examplesFMM-1 MODIS derived hotspotsFMM 1, MODIS derived hotspots
Shapefile & kmlShapefile & kml
Delivered 2-3 times per day
Summer seasons of 2009 2010 Summer seasons of 2009, 2010 & 2011
Spatial resolution 1×1km
5/10/2012 6
Dataset examplesFMM-2 MODIS derived burnt areasFMM 2, MODIS derived burnt areas
Shapefile & kml
A l t d b t Accumulated burnt areas
Daily burnt areas
Summer seasons of 2009 2010 & Summer seasons of 2009, 2010 & 2011
Spatial resolution 250×250m
5/10/2012 7Zip files of the form:
Dataset examplesBSM example in Greece
Rapid Fire Mapping – Greece 2007
BSM example in Greece
5/10/2012
Dataset examplesBSM derived from HR and VHR satellite imagesBSM, derived from HR and VHR satellite images
Shapefile
Delivered seasonally
2007, 2008, 2009, 2010 & 2012
5/10/2012 9High and Very High resolution satellite imagery (2m – 30m)
Dataset examplesBSM example in IoanninaBSM example in Ioannina
Dataset examplesBSM example in CorsicaBSM example in Corsica
Dataset examplesAuxiliary informationAuxiliary information
Contour lineAirfield
Background images
and mosaics from Place of interest
CLC 2000various sensors
GIS layers
(administrative (administrative,
places of interest,
toponyms, etc.)
Background image
Contour lines
derived from DEM
C i L d C Corine Land Cover,
in raster and vector
format, in 3 layers
f d t ilHospital
Administrative
of detail
5/10/2012 12
Administrative boundaries
Fire monitoringThe 2007 wildfiresThe 2007 wildfires
WP7 in TELEIOSRole with respect to the general architectureRole with respect to the general architecture
5/10/2012
Use Case IIObjectiveObjective
D i i l t d lid t f llDesign, implement, and validate a fullyautomatic fire monitoring processing chain, forreal time fire monitoring and rapid mapping,that combines in real-time:
i) Volumes of EO image acquisitions.
ii) Volumes of GMES fire monitoring productsii) Volumes of GMES fire monitoring products.
iii) Models/Algorithms for data exchange and processing
iv) Auxiliary geo-information.
v) Human evidence, in order to draw reliable decisionsand generate highly accurate fire products.
5/10/2012
1st User WorkshopRequirements gatheringRequirements gathering
5/10/2012 16
Use Case IIUse Case IIReal-time fire monitoring
Part B: An insight at the various components
2nd User workshopDarmstadt, 10-11 May 2012Darmstadt, 10 11 May 2012
P t H i K t & I i P t i (NOA)Presenters: Haris Kontoes & Ioannis Papoutsis (NOA)
Real-time Fire Monitoring
Refinement of hotspot serviceRefinement of hotspot service
• Automation of the processing and storage
Processing chain triggering
Systematic archiving of raw data and storage of hotspot products
• Geo-referencing with increased geometric accuracy
• Increased thematic accuracy using a dynamic threshold approach
Product refinement using semantics
Generation of thematic maps using Linked dataGeneration of thematic maps using Linked data
Easy integration of new processing modules using SciQL
TELEIOS system infrastructure - DEMO
5/10/2012 18
Fire monitoring applicationAdvancements – integration of the TELEIOS technologiesAdvancements integration of the TELEIOS technologies
EumetsatEumetsat @ @ 9.59.5°°EastEastFront End: GUIFront End: GUI Map ElementMap Element
Back End: MonetDB / Strabon
•• CorineCorine LandcoverLandcover•• Admin BoundariesAdmin Boundaries•• POIsPOIs
External Sources GeospatialGeospatial
OntologyOntologyWeb accessWeb access
based on Semanticsbased on Semantics
Cataloguing ServiceCataloguing Service& Metadata Creation& Metadata Creation
OntologyOntology based on Semanticsbased on Semantics
LinkedLinked
Data Vault
Linked Linked Geospatial DataGeospatial Data
SSemanticemantictechnologiestechnologies
HotSpotsHotSpots
Raw DataRaw Data• Search & Display• Search for raw & Processing
Processing ChainProcessing Chain((SciQLSciQL based)based)
• Real-time Fire Monitoring• Refinement (Post-Processing) • Linked Data
5/10/2012 19
Fire monitoring service Processing chainProcessing chain
Data Import
• Band Separation• Band Separation• Transformation of raw
imagery to appropriate internal format for
Raw data
processing Product generation
• Exports final products to raster and vector formats
Cropping
• Crops image to the area of interestof interest
Georeferencing ClassificationGeoreferencing
• Georeference input image bands
• Each pixel can be
Classification
• Derive physical indexes through band operations
• Assign each pixel a fire non-• Each pixel can be geographically identified
• Assign each pixel a fire nonfire flag with an associated level of confidence, via index thresholding
Fire monitoring serviceProcessing chain – intermediate productsProcessing chain intermediate products
Data Import
Cropping Georeferencing
Classification
Fire monitoring service ProductsProducts
Rasteraste
Vector
Fire monitoring serviceAlgorithmic improvementsAlgorithmic improvements
Classification approach #1: Fire detection is based on fixed thresholding applied on two spectral bands using simple band thresholding, applied on two spectral bands using simple band algebra.
Classification approach #2: The thresholds are dynamically pp y ycalculated for each new image and for every pixel of the raw imagery.
Step 1: Calculation of latitude and longitude for each pixel using bilinear interpolation.Step 2: Estimation of Solar Zenith Angle per image, per pixel.
Step 3: Definition of new thresholds depending on this angle, with a linear interpolation.
Fire monitoring serviceAlgorithmic improvements – an exampleAlgorithmic improvements an example
Discussion on TELEIOS technologies Benefits from using MonetDBBenefits from using MonetDB
Hide completely the details/complexity of the raw data Hide completely the details/complexity of the raw data format, using the Data Vault
Use higher-level languages stop worrying about how to Use higher-level languages, stop worrying about how to store and manage data, just focus on the actual processing
Express common earth observation operations easily using Express common earth observation operations easily using the purpose-build SciQL instead of using a lengthy C programg
Easily handle massive loads due to advanced processing capabilities of column-store MonetDB p
Allow algorithm execution to be optimized by the DBMS’s query optimizer.query optimizer.
5/10/2012
Discussion on TELEIOS technologies Benefits from using Semantic technologiesBenefits from using Semantic technologies
Refine products by using spatio-temporal queries expressed in tSPARQLstSPARQL:
o Identify and eliminate hotspots occurring in the sea
o Decide for hotspots that are partly located in non-consistent underlying land use
Attribute a variable confidence level according the the spatioo Attribute a variable confidence level according the the spatio-temporal persistence of a hotspot
Express semantic queriesExpress semantic queries
o “Find hotspots within 2 km from a major archeological site”
Use other Linked Data together with fire products to further enhance our products’ value:
G eek go e nment data (geodata go g ) Administ ati e o Greek government data (geodata.gov.gr), Administrative Geography of Greece, Open Street Map, Wikipedia, Gazeteers (e.g. Geonames)
5/10/2012
Discussion on TELEIOS technologies Benefits from using Semantic technologiesBenefits from using Semantic technologies
5/10/2012
Burn Scar Mapping serviceProcessing chain
Geo-
Processing chain
Pre-processing
Input dataHigh & Very high spatial resolution
referencingIdentification of reference control
Cloud maskingspatial resolution reference control
points
Core processingClassification
NBR, ALBEDO, Near-Noise removalRaster to t
Core processing
, O, eaInfrared and NDVI difference indexes
are used
Application of two spatial filters
vector conversion
Attributes Post-processing
Visual refinement
Use of auxiliary GIS
Attributes enrichmentInvolves spatial
Map productionand delivery to Use of auxiliary GIS
layers
poperations with geo-information layers
and delivery to end users
LT51840342011218MOR00
LT5 S t llit
The LEDAPS preprocessing software performs • calibration & atmospheric
The Automated Precise Orthorectification Package (AROP) provides generalLT5 : Satellite
184 : Row034 : Path2011 : Year
pcorrection and additionally
• computes water-land and cloud mask products
Procedure 1
(AROP) provides general image georegistration and orthorectification for Landsat-like data sources.
Procedure 2218 : Day of the YearProcedure 1Procedure 2
Base Images DTM
7 TIF BANDS & *MTF ASCII7 TIF BANDS Base = BAND 5
B1 B2 B3 B4 B5 B6 B7
Metadata File
For each LANDSAT Image
400+LANDSAT-4 & LANDSAT-5Satellite Image Archive
Temporal Coverage:1984-1991 & 1998-2011
1. Orthorectified Landsat Image (*.IMG)2. Water-Land-Cloud (0-1-2) Mask (*.TIF)
Burn Scar Mapping serviceCore processingCore processing
Classification based on trained thresholdsClassification based on trained thresholds
o NBR, ALBEDO, Near-Infrared, NDVI difference indexes
Filtering of the classified pixels
o Spatial filtering for gap filling through a 3×3 (variable) p g g p g g ( )window
o Grouping to pixel clusters
o Elimination of clusters where area < 1ha (variable)
C t i hb i l t ith di t h t th o Connect neighboring clusters with distance shorter than 2 pixels (variable)
Raster to vector conversionRaster to vector conversion
Burn Scar Mapping servicePost-processingPost-processing
Application of refinement queries:Application of refinement queries:
o False alarms near the coastline
o Burnt crops during the summer
Attribute enrichment with the use of Linked data
Ability to produce rapid mapping products in rush Ability to produce rapid mapping products in rush mode
l h bl lProcess large archives enabling a time-series analysis
Pose queries on historical products for long-term ose que es o sto ca p oducts o o g teanalysis
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