Formulating Standards related to Land Parcels as per the national Geospatial Policy 2022

P L N Raju

Special Secretary STCCD & Director, ASSAC 9411768991

Land Parcel

• A "land parcel" means a specific, defined area of land that is considered a single unit of ownership, essentially a plot of land with clear boundaries that can be bought, sold, or developed for a particular purpose like building or farming; it's a distinct piece of real estate with its own legal description. 

Key points of the policy:

• Open data access:
• Aims to liberalize the geospatial sector by allowing wider access to geospatial data, with the exception of sensitive security information, enabling citizens and businesses to utilize this data freely. 
• Private sector participation:
• Encourages private companies to actively participate in the geospatial industry by generating and utilizing their own geospatial data, fostering innovation and competition. 
• High-resolution mapping:
• Aims to develop high-resolution topographical surveys and a high-accuracy Digital Elevation Model (DEM) for the entire country by 2030. 
• Innovation ecosystem:
• Plans to establish incubation centers and technology parks to promote start-ups and technology development in the geospatial sector. 
• Citizen-centric approach:
• Focuses on empowering citizens and local communities by providing easy access to geospatial data and services. 

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�Core Principles (Aligned with NGP 2022)�

• Open Data and Data Sharing: Standards should facilitate easy data sharing and access, promoting open data principles while respecting privacy and security concerns.
• Interoperability: Standards must ensure seamless data exchange between different systems and stakeholders. This includes defining common data formats, schemas, and metadata.
• Accuracy and Reliability: Standards should specify requirements for data accuracy, completeness, and consistency, ensuring reliable land parcel information.
• Discoverability: Metadata standards are crucial for easy discovery of land parcel data. This includes keywords, spatial and temporal extent, data quality information, and access conditions.
• Usability: Standards should promote ease of use for various applications, including land administration, planning, and disaster management.
• Sustainability: Standards should be designed for long-term maintenance and evolution, adapting to technological advancements and changing user needs.

Key Technical Components

• Unique Parcel Identifier (UPI): A persistent and unique identifier is essential for each land parcel. This should be a nationally consistent system, potentially incorporating existing identifiers (e.g., survey numbers) but designed for digital representation and automated processing. Consider:
• Structure: Hierarchical, alphanumeric, or a combination. Consider incorporating state, district, tehsil, and village codes.
• Generation: Centralized or decentralized, but with clear rules and validation procedures.
• Persistence: Ensuring the UPI remains valid even after parcel boundary changes (e.g., subdivision).

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Geometry Representation

• Geometry Representation: Land parcel boundaries should be represented using well-defined geometric primitives:
• Coordinate Reference System (CRS): A standard CRS (e.g., a projected system like UTM or a geographic system like WGS 84) must be specified. Consider the implications of using different CRSs for different applications.
• Geometry Type: Polygons are the most common representation. Standards should address how to handle complex parcel shapes and shared boundaries.
• Data Format: Standard formats like GeoJSON, Well-known Text (WKT), and Shapefiles can be used, but newer formats like GeoParquet offer advantages in terms of performance and efficiency.

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Attribute Data

• Attribute Data: Standards should define a core set of attributes associated with each land parcel:
• Ownership Information: Clear guidelines on representing ownership details, including individual, joint, and government ownership. Consider privacy regulations and data security.
• Land Use Classification: Standardized categories for land use (e.g., residential, commercial, agricultural). Consider using existing classification systems (e.g., National Land Use/Land Cover data).
• Legal Status: Information on encumbrances, mortgages, and other legal restrictions.
• Area: Calculated accurately based on the geometry.
• Parcel History: Tracking changes in parcel boundaries and ownership over time.

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Metadata

• Metadata: Comprehensive metadata is crucial for data discoverability and understanding:
• Data Provider: Organization responsible for creating and maintaining the data.
• Data Quality: Information on accuracy, completeness, and consistency.
• Spatial and Temporal Extent: Geographic area and time period covered by the data.
• Data Dictionary: Definitions of all attributes and their data types.
• Access Constraints: Conditions for accessing and using the data. Adherence to ISO 19115 and other relevant metadata standards is recommended.

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Data Quality & Data Exchange Formats

• Data Quality Assurance: Standards should define procedures for ensuring data quality:
• Validation Rules: Automated checks for geometric and attribute consistency.
• Data Cleaning: Processes for correcting errors and inconsistencies.
• Accuracy Assessment: Methods for evaluating the accuracy of the data.
• Data Exchange Formats: Standards should specify preferred data exchange formats:
• GeoJSON: Lightweight and widely supported for web applications.
• GeoParquet: Efficient columnar storage for large datasets.
• OGC Standards: Consider adopting relevant OGC standards like WFS and WMS for data access and visualization.

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Data Security and Privacy

• Data Security and Privacy: Standards should address data security and privacy concerns:
• Access Control: Restricting access to sensitive data based on user roles and permissions.
• Data Encryption: Protecting data during storage and transmission.
• Privacy Regulations: Complying with relevant privacy laws and regulations.

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Alignment with NGP 2022

• The above technical considerations directly support the NGP 2022's objectives by:
• Enabling easy access to geospatial data: Standardized data formats and metadata facilitate data discovery and sharing.
• Promoting the use of geospatial technologies: Clear standards encourage the development of geospatial applications and services.
• Strengthening the geospatial ecosystem: Interoperable data and well-defined standards contribute to a more robust and integrated geospatial ecosystem.

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Implementation Considerations:

• Collaboration: Involve all relevant stakeholders (e.g., land record agencies, survey departments, urban planning authorities) in the development and implementation of standards.
• Pilot Projects: Implement the standards in pilot projects to test their effectiveness and identify any issues.
• Capacity Building: Provide training and support to users on how to implement the standards.
• Continuous Improvement: Regularly review and update the standards based on feedback and technological advancements.

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�National Natural Resources Management System (NNRMS) Standards�

• Pioneering Efforts: ISRO, through the NNRMS, has been instrumental in establishing the first geospatial data standards in India. These standards, initially developed in 1998 and updated in 2005, provide a framework for data generation, processing, and dissemination related to natural resources.
• Key Components: The NNRMS standards cover various aspects, including:
• Data formats: Defining standard formats for spatial data (vector and raster) and attribute data.
• Spatial reference systems: Specifying coordinate systems and projections for accurate georeferencing.
• Thematic classifications: Establishing standardized categories for land use, soil types, forest cover, and other natural resource themes.
• Metadata: Defining metadata elements for describing data characteristics, quality, and lineage.
• Data quality assurance: Outlining procedures for data validation, accuracy assessment, and quality control.

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Bhuvan Geo-platform:

• Data Harmonization: ISRO's Bhuvan geoportal serves as a platform for hosting and disseminating geospatial data related to natural resources. To ensure data interoperability and usability, Bhuvan adheres to specific geospatial content standards.
• Bhuvan Standards: These standards encompass:
• Remote sensing data standards: Specifying parameters for satellite imagery, including spatial and spectral resolution, processing levels, and accuracy.
• GIS data standards: Aligning with NNRMS standards for thematic data layers, ensuring consistency in content and format.
• Spatial reference standards: Adhering to national map policies for coordinate systems and projections.
• Metadata standards: Following ISO 19115 and other relevant standards for metadata creation and management.

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Contributions to National Geospatial Policy, 2022�

• Alignment with NGP: ISRO's efforts in developing geospatial standards for natural resource information systems align with the objectives of the National Geospatial Policy, 2022.
• Data Accessibility and Sharing: ISRO's initiatives promote open data principles and facilitate data sharing among stakeholders, supporting the policy's goals of wider data availability and utilization.
• Interoperability and Standardization: ISRO's focus on standards ensures data interoperability, enabling seamless integration of natural resource information with other geospatial datasets.

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Applications and Benefits:

• Natural Resource Management: ISRO's geospatial standards support various applications in natural resource management, including:
• Land use and land cover mapping: Monitoring changes in land use patterns and assessing environmental impacts.
• Forest monitoring: Tracking deforestation, forest degradation, and biodiversity.
• Water resource management: Mapping water bodies, assessing water availability, and monitoring water quality.
• Agriculture: Crop monitoring, yield estimation, and precision farming.
• Disaster management: Providing critical information for disaster preparedness, response, and recovery.
• Informed Decision-making: By providing standardized and reliable geospatial information, ISRO contributes to informed decision-making for sustainable development and resource management.

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Challenges and Future Directions:

• Evolving Technologies: Keeping pace with rapid technological advancements in remote sensing, GIS, and data analytics.
• Data Integration: Integrating diverse data sources, including satellite imagery, ground-based observations, and socio-economic data.
• Capacity Building: Enhancing the capacity of users and stakeholders to effectively utilize geospatial standards and tools.
• Data Accessibility: Ensuring wider accessibility of geospatial data while addressing privacy and security concerns.
• ISRO's ongoing efforts in developing and promoting geospatial standards for natural resource information systems are crucial for effective resource management, sustainable development, and informed decision-making in India.

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Geographic Information Technologies

• Global Positioning Systems (GPS)
• a system of earth-orbiting satellites which can provide precise (100 meter to sub-cm.) location on the earth’s surface (in lat/long coordinates or equiv.)
• Remote Sensing (RS)
• use of satellites or aircraft to capture information about the earth’s surface
• Digital ortho images a key product (map accurate digital photos)
• Geographic Information Systems (GIS)
• Software systems with capability for input, storage, manipulation/analysis and output/display of geographic (spatial) information.

GPS and RS are sources of input data for a GIS.

A GISy provides for storing and manipulating GPS and RS data.

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

• Integrating technology consisting of:
• Remote Sensing
• Cartography and Mapping
• GPS
• Computers
• RDMS
• Information Technology
• Communication technology
• Survey and field data collection

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General Understanding of GIS

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

Sensor

Object to be sensed

Electro Magnetic Radiation

• "Remote sensing is the science of acquiring information

about the Earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted Electromagnetic Energy and processing, analyzing, and applying that information."

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Three Essential Things for Remote

Sensing

What is Remote Sensing ?

Remote Sensing Area

• Sun synchronous satellites
• Optical RS data
• MW RS data
• HSRS data
• Geostationary satellites
• XS RS
• HSRS
• Weather satellites
• UAV RS data

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Optical Remote Sensing satellites

• Indian Remote Sensing Program
• LANDSAT / NASA Programs
• ESA RS Programs
• SPOT /French RS Programs
• China RS Programs
• JEXA RS Programs
• Commercial satellite programs

Hyper-spectral imaging and its applications

Spectral range: 400nm – 2500nm, spectral bands: 300 – 400, Applications: Precision

agriculture, geology , mineral exploration, environmental monitoring and archaeology

Active Vs Passive Remote Sensing

Passive remote sensors measure radiant energy reflected or emitted by the Earth’s atmosphere system or changes in gravity from the Earth.

Active remote sensors have their own source of light or illumination. In particular, it actively sends a pulse and measures the backscatter reflected to the sensor.

(Passive )Optical Remote Sensing Basics

• The sun radiates the earth with nearly equal amounts of blue, green, and red wavelength light.
• Because of its physical properties, the tree reflects and absorbs differing amounts of the incoming light...
• The tree absorbs much of the red and blue wavelengths and reflects much of the green.

Review of Spectral Signatures

Optical RS Satellite constellations

• Large number of satellites in sun synchronous orbit
• Operated by States and individuals on commercial mode
• There are around 791 Earth-observation and Earth-science satellites in orbit out of 2800 active satellites (Sept. 2021) which are used for communication, navigation and scientific research.
• ~ Approximately 481  are optical/multi-spectral/hyper spectral imaging satellites
• To be used for natural resources management, infrastructure development, rural / urban planning, utility services
• Availability of large number of satellites helping in near real time applications
• PLANETSCOPE is one of the largest optical RS satellite constellations. It operates more than 200 satellites (180+ planetscope, 5 Rapideye and 21 Skysat satellites)
• World View, Geoeye, Cartosat, Komsat are the other HR satellites may be referred for more details

What makes data spatial?

Place name

Grid co-ordinate

Postcode

Distance & bearing

Description

Latitude / Longitude

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Questions that can answered by GIS

• LOCATION (Question: What is at ...?)
• CONDITION (Question: Where is it....?)
• TRENDS (Question: What has changed since....?)
• PATTERN (Question: What spatial pattern exist...?)
• MODELING (Question: What if....?)

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Types of data

• Two types of data are stored for each item in the database
• Attribute data:
• Says what a feature is
• Eg. statistics, text, images, sound, etc.
• Spatial data:
• Says where the feature is
• Co-ordinate based
• Vector data – discrete features:
• Points
• Lines
• Polygons (zones or areas)
• Raster data:
• A continuous surface

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Modelling the real world

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Geo-referencing data

• Capturing data
• Scanning: all of map converted into raster data
• Digitising: individual features selected from map as points, lines or polygons
• Geo-referencing
• Initial scanning digitising gives co-ordinates in inches from bottom left corner of digitiser/scanner
• Real-world co-ordinates are found for four registration points on the captured data
• These are used to convert the entire map onto a real-world co-ordinate system

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Layers

• Data on different themes are stored in separate “layers”.

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• As each layer is geo-referenced layers from different sources can easily be integrated using location

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• This can be used to build up complex models of the real world from widely disparate sources

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Line and Polygon feature

Buildings: polygons

Raster (image) Layer

Digital Ortho Photograph Layer:

Digital Ortho photo: combines the visual properties of a photograph with the positional accuracy of a map, in computer readable form.

Vector

Layers

Layers

SRS: UTM, WGS 84

Resolution: 0.5 meters

Accuracy: 1.0 meters

Scale: 1:500 Scale

Location: Gandhinagar Slum Hyderabad, Andhra Pradesh

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

Spatial data storage

• Vector model

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• Raster model

As geometric objects: points, lines, polygons

As image files composed of grid-cells (pixels)

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Vector data model

• Advantage of the vector data format: allows precise representation of points, boundaries, and linear features.

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• useful for analysis tasks that require accurate positioning,
• for defining spatial relationship (i.e. the connectivity and adjacency) between coverage features (topology), important for such purposes as network analysis (for example to find an optimal path between two nodes in a complex transport network)

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• Main disadvantage of vector data is that the boundaries of the resulting map polygons are discrete (enclosed by well-defined boundary lines), whereas in reality the map polygons may represent continuous gradation or gradual change, as in soil maps.

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

Raster data model

• Good for representing indistinct boundaries thematic information on soil types, soil moisture, vegetation, ground temperatures

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• As reconnaissance satellites and aerial surveys use raster-based scanners, the information (i.e. scanned images) can be directly incorporated into GIS

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• The higher the grid resolution, the larger the data file is going to be

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

INDIAN INSTITUTE OF REMOTE SENSING, DEHRADUN

Projection, Scale, Accuracy and Resolution�the key properties of spatial data

• Projection: the method by which the curved 3-D surface of the earth is represented by X,Y coordinates on a 2-D flat map/screen
• distortion is inevitable

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• Scale: the ratio of distance on a map to the equivalent distance on the ground
• in theory GIS is scale independent but in practice there is an implicit range of scales for data output in any project

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• Accuracy: how well does the database info match the real world
• Positional: how close are features to their real world location?
• Consistency: do feature characteristics in database match those in real world
• is a road in the database a road in the real world?
• Completeness: are all real world instances of features present in the database?
• Are all roads included.

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• Resolution: the size of the smallest feature able to be recognized
• for raster data, it is the pixel size

The tighter the specification, the higher the cost.

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The GIS Data Model: Implementation�Geographic Integration of Information

• Data is organized by layers, coverages or themes (synonymous concepts), with each layer representing a common feature.
• Layers are integrated using explicit location on the earth’s surface, thus geographic location is the organizing principal.

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GIS Data Open Formats

• Raster:
• TIFF/GEO TIF
• JPEG 2000
• GML
• WCS and WMS
• Vector
• Shape File
• POSTGIS
• GML
• KML
• WFS and WMS

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Overshoot

Undershoot

Duplicate line

Sliver

Digitising errors

iirs

Snap Tolerance

iirs

Identifying & Interpreting errors

• Overshoots
• Undershoots
• Missing labels
• Multiple labels

Pseudo node

Label points

Dangling node

Missing labels

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*

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+213

+214

+212

+211

+216

+215

+217

iirs

Some clean-up operations for vector data

Source: ITC

iirs

UAV Applications

• Playing major role in Remote Sensing applications, mainly very high resolution data products, improved area coverage with higher endurance, terrain /DTM applications, disaster management studies etc.
• Used for surveillance
• Delivery of emergency products / medicine etc
• Local area WiFi internet services
• Transportation etc.

In GNSS area

• GNSS technology is changing rapidly with multiple new applications.
• Multiple GNSS constellations (i.e. GPS (USA), GLONASS (Russia), Galileo (EU), NAVIC (India), Beidou (China), QZSS (Japan) etc.
• SBAS with improved positional accuracy (WAAS/EGNOS/MSAS/GAGAN/…..) systems
• Other augmentation systems are LAAS, LADGPS/GBAS/NDGPS/CORS etc.
• Use of GNSS is positioning, direction, kids/elderly tracking. Drones, autonomous vehicles, IOT based applications, LBS, Precision farming etc.

In Communication area

• Internet evolution in India
• 1995 is the beginning year through VSNL at 9.6 kbps
• 2004 broadband policy of 256 kbps, 2010 Govt auctioned 3G, followed by 4G – accelerated wireless BB market
• 450 m internet users in India , second to China (700 m users), 72% are below 35 years and 80% from mobile use

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Revolution in internet

• Dedicated HTC satellites for Northeast (GSAT 29) for DTH based Internet services
• In Northeast there are more than 50,000 villages which can be connected effectively through GSAT 29 with high bandwidth.
• Future will be very bright with availability of STARLINK (SPACEX), KUIPER (Amazon) and ONEWEB satellite internet connection without the terrestrial support.
• Starlink – 3000 launched, to go 12,000 + 42,000 satellites, Oneweb launched 464 out of 648 & Kuiper plans with 3236 in ten years

Role of Social media

• World over many geo-portals offering services for social media through Google Earth, MS Virtual Earth/Bing Maps/NASA’s World Wind/Open street maps
• Indian Geo-portals are NRSC Bhuvan/NDEM/NESAC NESDR/NEDRP etc. enables social media to respond with geospatial information
• Social Media networks such as SMS feeds, Web Forms, Email, Facebook, Twitter, wikis etc. Example: Social media in Haitian earthquake in 2020

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Web platform

Geo-Portals and their services

Way Forward …….

• NSP 2022 is a mission towards Digital India for planning, development, governance and economic progression
• Data Democratization
• Ease of transactions and up dation periodically
• Efficient handling
• Safe and secure handing
• Many more…

United Nations Integrated Geospatial Information Framework (UN-IGIF)