Development of AI-powered FRA Atlas and WebGIS-based Decision Support System (DSS) for Integrated Monitoring of Forest Rights Act (FRA) Implementation. (States to be concentrated: Madhya Pradesh Tripura Odisha Telangana)
Organization: Ministry of Tribal Affairs(MoTA)
Category: Software | Theme: Miscellaneous

Problem Background :
The Forest Rights Act (FRA), 2006 recognizes the rights of forest-dwelling communities over land and forest resources. However, significant challenges persist:
• Legacy records of Individual Forest Rights (IFR), Community Rights (CR), and Community Forest Resource Rights (CFR) are scattered, non-digitized, and difficult to verify.
• There is no centralized, real-time visual repository (e.g., an FRA Atlas) of FRA claims and granted titles.
• Integration of satellite-based asset mapping (land, water bodies, farms, etc.) with FRA data is missing.
• Integration of legacy data with FRA Atlas is missing.
• Decision-makers lack a Decision Support System (DSS) to layer Central Sector Schemes (CSS) benefits (e.g., PM-KISAN, Jal Jeevan Mission, MGNREGA, DAJGUA (3 ministries)) for FRA patta holders.

Project Objectives
1. Digitize and standardize legacy data of FRA claims, verifications, and pattas, and integrate with FRA Atlas. FRA patta holders’ shapefiles to be integrated.
2. Create an FRA Atlas showing potential and granted FRA areas using AI and satellite data.
3. Integrate a WebGIS portal to visualize and manage spatial and socio-economic data.
4. Use Remote Sensing and AI/ML to map capital and social assets (ponds, farms, forest resources) of FRA-holding villages.
5. Build a Decision Support System (DSS) to recommend and layer CSS schemes based on mapped data, enhancing targeted development.

AI & Tech Components
1. Data Digitization
• Use suitable models to extract and standardize text from scanned FRA documents.
• Apply Named Entity Recognition (NER) to identify village names, patta holders, coordinates, and claim status.

2. AI-based Asset Mapping
• Employ Computer Vision on high-resolution satellite imagery to detect:
  • Agricultural land
  • Forest cover
  • Water bodies (ponds, streams)
  • Homesteads
• Classify land-use using supervised ML models (e.g., Random Forest, CNN).
• Add layers of information with respect to forest data, groundwater data, and infrastructure data (e.g., PM Gati Shakti).

3. WebGIS Integration
• Interactive layers (IFR/CR, village boundaries, land-use, assets)
• Filters by state/district/village/tribal group
• FRA progress tracking (village/block/district/state level)

4. Decision Support System (DSS)
• Build a rule-based + AI-enhanced DSS engine that:
  • Cross-links FRA holders with eligibility for CSS schemes such as DAJGUA and others.
  • Prioritizes interventions (e.g., borewells under Jal Shakti for villages with low water index).

Deliverables
1. AI-processed digital archive of FRA claims & decisions.
2. An interactive FRA Atlas on a WebGIS platform.
3. AI-generated asset maps for all FRA villages.
4. A DSS engine for scheme layering and policy formulation.

Target Users
• Ministry of Tribal Affairs
• District-level Tribal Welfare Departments & Line Departments of DAJGUA
• Forest and Revenue Departments
• Planning & Development Authorities
• NGOs working with tribal communities

Future Scope
• Incorporate real-time satellite feeds for monitoring CFR forests.
• Integrate IoT sensors for soil health, water quality, etc., in FRA lands (if feasible).
• Enable mobile-based feedback and updates from patta holders themselves.