Madhya Pradesh has become the first state in India to implement an AI-based real-time forest alert system on a pilot basis for active forest management. The system uses satellite images, mobile feedback, and machine learning to detect land encroachment, land use change, and forest degradation.
About Forest Alert System
- First-time integration of satellite, AI, and field feedback in a continuous learning cycle.
- Developed by: Guna DFO Akshaya Rathore (IIT Roorkee alumnus) with help from ChatGPT.
- Implemented as a pilot project in 5 sensitive divisions: Guna, Burhanpur, Shivpuri, Khandwa, Vidisha
- Aims for statewide implementation later.
Features of AI Alert System
- Built on Google Earth Engine.
- Analyzes multi-temporal satellite data using a custom AI model to detect land use changes.
- Sends alerts to field staff via a mobile app for site verification.
- Dashboard monitoring at Divisional Forest Officer (DFO) level: Real-time alerts categorized by beat and field posts.
- Monitoring Filters: date, density, area.
- Each alert includes:
- Polygon alerts (pixel changes mapped)
- 20+ data features per alert
- Mobile app-based verification (field staff upload GPS-tagged photos, voice notes, comments).
- Indexes used for analysis:
- NDVI (Normalized Difference Vegetation Index)
- SAVI (Soil Adjusted Vegetation Index)
- EVI (Enhanced Vegetation Index)
- SAR (Synthetic Aperture Radar)
- Alerts cover areas as small as 10×10 meters, enabling detection of: Crop cultivation; Construction and Other land use changes.
- Instant instructions sent to beat guards for on-ground verification to curb illegal activities.
- Innovative Aspects: Generates alerts every 2–3 days (vs. Karnataka’s 21-day alert frequency).
Future Application
- Phase 1: Staff must upload photo proofs from alert zones (ensures accountability).
- Phase 2 goal: Move toward full automation to reduce human dependency.
- Once system achieves 99% accuracy, it will evolve into a predictive tool for:
- Identifying illegal activities (felling, encroachment)
- Managing grass and water resources
- Optimizing budget allocation and manpower.
Need of Such System
- MP has largest forest and tree cover in India (85,724 sq km) (Forest Survey of India 2023).
- But also reported highest forest loss: 612.41 sq km.
- Traditional monitoring relied on manual methods with delayed alerts.
- AI system improves detection, response, and forest protection capacity.
Other National Sustainable Forest Management Initiatives
| Initiative | Objective |
| Green India Mission (GIM) | Increased India’s forest cover by 0.56% (2017-2021) |
| National Agroforestry Policy (2014) | Promotes tree planting on private farmland to ease pressure on forests. |
| Trees Outside Forests in India (TOFI) | Encourages afforestation on non-forest lands with private participation. |
| Compensatory Afforestation Fund (CAMPA) | Funds reforestation where forests diverted for projects |
| CSR-driven Plantations | Companies (automobile, cement, energy) plant trees to offset emissions |
| Agroforestry for Livelihoods | Farmers combine timber, fruit, medicinal trees with crops for extra income |
| Carbon Credit Afforestation | Industries plant forests to earn carbon credits |