CanopySense

Canopy Sense 🌳

Intelligent Geo-Spatial Afforestation Planning

An MVP for Smart India Hackathon 2026 (Internal Qualifying Round). Given any location on a map + a carbon offset target, returns:

• Ranked native tree species suited to that location
• Number of trees required to hit the target
• Projected carbon sequestration over 5/10/20 years
• Suitability visualization on the map

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Stack

Layer	Tech
Frontend	Next.js 14, React-Leaflet, Recharts
Backend	FastAPI, SQLAlchemy, Pydantic v2
Database	PostgreSQL (Neon/Supabase for prod)
Geo Data	Google Earth Engine (NDVI, CHIRPS, SoilGrids, ESA WorldCover)
ML	Scikit-learn / XGBoost (species suitability scoring)
Deploy	Vercel (frontend) + Render (backend) + Docker

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Project Structure

canopy-sense/
├── backend/              # FastAPI backend
│   ├── app/
│   │   ├── api/          # Route handlers
│   │   ├── core/         # Config, settings
│   │   ├── db/           # SQLAlchemy models, session, init
│   │   ├── models/       # Pydantic schemas
│   │   └── services/     # GEE, species scoring, carbon calc
│   ├── Dockerfile
│   └── requirements.txt
├── frontend/             # Next.js frontend
├── data/                 # Species dataset (CSV + seed script)
├── ml/                   # Model training scripts
└── docker-compose.yml

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Quick Start

1. Clone & setup

git clone <repo-url>
cd canopysense

2. Configure environment

cp backend/.env.example backend/.env
# Edit backend/.env with your DB URL and GEE credentials

3. Run with Docker

docker-compose up --build

4. Initialize the database

docker exec canopy_sense_backend python -m app.db.init_db

5. Seed species data

docker exec canopy_sense_backend python data/seed_species.py

6. Access

• Backend API: http://localhost:8000
• API Docs: http://localhost:8000/docs
• Frontend: http://localhost:3000

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API Endpoints

Method	Endpoint	Description
POST	/api/v1/analyze-location	Main analysis endpoint
GET	/api/v1/species	List all species in dataset
GET	/api/v1/demo-locations	Pre-cached demo locations
GET	/health	Health check

Example Request

POST /api/v1/analyze-location
{
  "lat": 28.6139,
  "lon": 77.2090,
  "carbon_target_tonnes": 100.0
}

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Demo Locations (pre-cached for judging)

City	Lat	Lon	Zone
Delhi	28.6139	77.2090	Semi-arid, BSh
Bangalore	12.9716	77.5946	Tropical savanna, Aw
Chennai	13.0827	80.2707	Tropical wet/dry, Aw

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Team

Built for SIH 2026 Internal Hackathon — Smart Automation theme.