National Urban Information System (NUIS)Data Model

at Indian Institute of Surveying & Mapping

Hyderabad8th June 2010

byRabindranath Nanda

Superintending SurveyorGIS & RS Directorate

Survey of India

What is NUIS ?

• The Ministry of Urban Development has launched the National Urban Information System (NUIS) Scheme in March, 2006. to implement 74th constitutional ammendment.

• Components are:• Urban Spatial Information System (USIS) to meet

the spatial requirements of urban planning.• National Urban Databank and Indicators (NUDB&I)

to develop town level urban database. • Developed Databases will be used for preparation of

• Master/ Development plans.• Detailed town planning schemes.• Serve as decision support for e-governance.

Scales of GIS Data Creation (153 Towns)

1:10000 - Preparation of Zonal/Master Plan 1:2000 - Detailed Town Planning

1:1000 - Utility Planning

Source of Data Creation

1:10000 - Thematic Mapping from imageries 1:2000 - Large Scale Mapping using 1:10K scale aerial photographs

1:1000 - Under ground utility mapping using Ground Penetrating Radar

National Map Policy

• National Map Policy was published during June 2005.

• The policies announced has given rise to two series of maps OSM and DSM.

• Mapping scale of 1:2k and 1:10k was introduced in addition to 1:25k, 1:50k and 1:250k.

Everest/Polyconic

WGS84/LCC

WGS 84 /UTM

Polyconic SeriesDSM Series

OSM Series

Need to Standardized the Data Capture

• Ensure Interoperability among different software and hardware platforms.

• Uniformity of various datasets.

• Integrated decision support system for different agencies could be developed.

• Automation in some stages of data capturing/generation could be implemented.

What is Data Modelling ?

Data modeling • It is a method used to define and analyze data requirements needed.• The data requirements are recorded as a conceptual data model with associated data definitions. • Data modeling defines not just data elements, but their structures and relationships between them. • Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. • Use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g. using data modeling:

• to manage data as a resource; • for the integration of information systems; • for designing databases/data warehouses.

Data Model

• The foundation to a database.

• Blue prints for data.

• Building plans for storing data.

• Instructions for building a database.

Types of data modelsFlat model

This may not strictly qualify as a data model. The flat (or table) model consists of a single, two-dimensional array of data elements, where all members of a given column are assumed to be similar values, and all members of a row are assumed to be related to one another.

Hierarchical model

In this model data is organized into a tree-like structure, implying a single upward link in each record to describe the nesting, and a sort field to keep the records in a particular order in each same-level list.

Network model

This model organizes data using two fundamental constructs, called records and sets. Records contain fields, and sets define one-to-many relationships between records: one owner, many members.

Relational model

It is a database model based on first-order predicate logic. Its core idea is to describe a database as a collection of predicates over a finite set of predicate variables, describing constraints on the possible values and combinations of values.

Looking Ahead

• Things to consider before constructing or updating a data model

• Selecting a data model that best fits your situation.

• Already have a Data Model

• Basic steps to help create and maintain your data model

How to do ?

• Match Data to Spatial Elements• Determine geometry type of discrete

features• Specify relationships between features• Implement attribute types for objects• Select Geographic Representation• Represent data with discreet features–

Points, Lines and Polygons

Objectives of Design

• Results in a Well-Constructed Database :• Satisfies objectives and supports organizational

requirements• Contains all necessary data but no redundant data• Organizes data so that different users can access

the same data.• Accommodates different views of the data.• Distinguishes which applications maintain the

data. from which applications access the data.• Appropriately represents, codes and organizes

graphical features.

Benefits From Good Design

• Data retrieval and analysis are used more frequently.

• Decrease time in attributing data.

• Data that supports different users and uses.

• Minimized data redundancy.

• Increased likelihood of users developing applications.

Different Data Models in Use• Survey of India

– Small Scale like guide maps on 1:50k/25k– Large Scale like DDA project 1:10k and

DSSDI on 1:2k

• National Informatics Centre (NIC) project completed by SOI on 1:1K for cities.

• NRSC Data model for 1:10k planning area survey under NUIS project.

• National Urban Information System 1:2k core area survey undertaken by SOI.

Basic Data Structures

• Vector ModelA vector model builds a complex representation from primitive objects from the dimensions such as points, lines and polygons. Examples could be road, building, tree etc.

• Raster ModelThe raster data model serves to quantize or divide space as a series of packets or units, each of which represents a limited, but defined, amount of the earth’s surface. Examples could be DEM, Ortho photos and Scanned Photographs.

Vector data model

• Location referenced by x, y coordinates, which can be linked to form lines and polygons.

• Attributes referenced through unique feature ID linked to the specific row/rows of the tables.

Raster Model

• Location is referenced by a grid cell in a rectangular array (matrix)

• Attribute is represented as a single value for that cell.

• More data comes in this form– Images from remote sensing– Scanned maps– Elevation data

Vector Model

Salient features• Data is to be disassociated from Visualization

and to be maintained in databases.• Visualization is to be planned/developed for

each and every product.• Visualization is to be again decided product wise

and developed in style sheet form.• Where ever desired objects to be filtered and

generalized as per requirement and should be automatic as far as practicable.

Data filtering and Generalization

1: 2000

1: 10000

1: 25000

Village Block

Village Block orOblong Hut

HUT

Filtering/ Generalisation

Data Creation on different scales

Database1:2k

Database1:10k

Filtering/ Generalisation

Database1:25k

Style Layer Description for NUIS Core map

Cartographic Output

Database1:2k

Database1:10k

Database1:25k

Style Layer Description for Utility map

Style Layer Description for Guide map

Style Layer Description for NUIS Planning map

Style Layer Description for Topomap

Style Layer Description for Project map

Feature Organisation

Major Categories1. Settlements & Cultural Details2. Hydrography3. Ocean & Coast lines4. Transportation5. Land Cover & Land Use6. Utilities7. Government/Administrative Boundaries8. Land Surface Elevation: Topographic /

Hypsography9. Geodetic10.Vital Installations

01. Settlements & Cultural Details

• Residential

• Commercial

• Government Offices

• Religious

• Antiquities

• Utility Centre

• Educational

• Institutions/Welfare/Relief

02. Hydrography• Stream

• Stream features

• River

• River Features

• Lake

• Lake Features

• Canal

• Canal features

• Other Water Features

03. Ocean & Coast Lines

• Coast Line

• Coastal natural features

• Coastal artificial features

• Tidal

• Elevation data

04. Transportation

• Carriageway• Carriageway Infrastructure• Tracks• Transport Utilities• Railway• Railway Infrastructure• Railway Embankment & Cuttings• Airport

05. Land Cover & Land Use

• Built up

• Agricultural

• Forest

• West Land

• Water bodies

• Wet Lands

• Grass Land/Grazing Land

• Snow Cover

06. Utilities

• Transmission Lines

• Pipe Lines

• Water Utilities

• Conveyor Belt

• Rope Way

• Filling Stations

• Solid Waste Management

07. Government & Administrative boundaries

• International Boundaries• State Boundaries• District Boundaries• Subdivision / Tehsil / Taluk / Mandal Boundaries• Pragana Boundaries in UP• Village Boundaries• Cantonment Boundaries• Municipal/ Corporation Boundaries• Ward Boundaries• Panchayat Boundaries• Block Boundaries• Constituency Boundaries• Police Station Boundaries• Park/Lawn Boundaries• Boundary Infrastructure

08. Land surface elevation & Hypsography

• Contours

• Mountain Features

• Mud Volcanoes

• Sand Features

• High Mountain Features

09. Geodetic Control Points

• Primary

• Secondary

• Topographic

• Other Sources

10.Vital Installation

• Civil Vital Installations

• Military Vital Installations

Code Level 1 Level 2 Level 3 Level 4 2k 10k 25k Remarks

01-01-00-00 Residential

01-01-01-00 Huts

01-01-01-01 Temporary A P P

01-01-01-02 Permanent A P P

01-01-02-00 Village Block

01-01-02-01 In ruin A A p/A

01-01-02-02 Existing A A P/A

01-01-03-00 Buildings

01-01-03-01 Single floor A p/A -

01-01-03-02 Multi Floor A p/A -

01-02-00-00 Commercial

01-02-01-00 Finance/Banks

01-02-01-01 Nationalized Bank A P -

01-02-01-02 Private Bank A P -

01-02-01-03 Chit Funds A P -

01-02-02-00 Farms

01-02-02-01 Poultry Farm A P/A P

01-02-02-02 Diary Farm A P/A P

Geometry of the object => Feature(NUIS)

Data Model 1:2K• Urban Layer (Point Feature) Table 2.1

– Topographical Features– Land Marks (Religious)– Land Marks (Infrastructure)– Land Marks (Others)

• Urban Network Layer (Line Feature) Table 2.2

– Transport– Infrastructure– Topographical Features– Drainage

Data Model 1:2K• Urban Layer (Polygon Feature) Table 2.3

– Built-up (Residential)– Built-up (Non-Residential)– Religious– Transport– Recreational– Administrative– Water Bodies– Public/Semi-public– Other Land Uses

Data Collection (Digital Photogrammetric)

Attribute Data Collection (Field Work)

00030102 00030103 00030104

Attribute Data Addition

Thank You !!!