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🚀 Quick Setup Guide

Initial Setup (First Time)

1. Google Earth Engine Setup

# Follow the detailed guide
cat docs/GEE_SETUP.md

# Summary:
# - Create GCP project
# - Enable Earth Engine API
# - Create service account
# - Download JSON credentials
# - Save to backend/credentials/gee-service-account.json

2. Backend Setup

cd backend

# Create virtual environment
python -m venv venv

# Activate (Windows PowerShell)
.\venv\Scripts\Activate.ps1

# Activate (Windows CMD)
venv\Scripts\activate.bat

# Install dependencies
pip install -r requirements.txt

# Create .env file
copy .env.example .env

# Edit .env and set GEE_SERVICE_ACCOUNT_PATH
notepad .env

3. Frontend Setup

cd frontend

# Install dependencies
npm install

# Update .env.development if needed (default is localhost:8000)

Running Locally

Terminal 1 - Backend

cd backend
.\venv\Scripts\Activate.ps1  # or appropriate activation command
python run_local.py

# Should see:
# ✅ GEE credentials found
# 🚀 Starting SAR Flood Detection API...
#    Local: http://localhost:8000
#    Docs:  http://localhost:8000/docs

Terminal 2 - Frontend

cd frontend
npm start

# Should open browser at http://localhost:3000

Testing the Application

  1. Open http://localhost:3000
  2. Select a test location from dropdown (e.g., "Venice Lagoon, Italy")
  3. Click "🛰️ Detect Water"
  4. Wait 30-60 seconds for processing
  5. View results - blue polygons show detected water
  6. Download results as GeoJSON if desired

Troubleshooting

Backend Issues

"GEE credentials not found"

  • Check backend/credentials/gee-service-account.json exists
  • Verify .env file has correct path

"Earth Engine access not configured"

Import errors

  • Ensure virtual environment is activated
  • Run pip install -r requirements.txt again

Frontend Issues

"Cannot connect to backend"

  • Verify backend is running on port 8000
  • Check .env.development has correct API URL

Map not loading

  • Check console for errors
  • Ensure leaflet CSS is imported

"Module not found" errors

  • Run npm install in frontend directory
  • Delete node_modules and package-lock.json, run npm install again

Deployment

Backend to Cloud Run

# Set your GCP project ID
export GCP_PROJECT_ID=your-project-id

# Run deployment script
bash deploy.sh

# Or deploy manually:
cd backend
gcloud run deploy sar-flood-api \
  --source . \
  --region us-central1 \
  --timeout 300s \
  --memory 1Gi \
  --allow-unauthenticated \
  --set-secrets GEE_SERVICE_ACCOUNT=gee-service-account:latest

Frontend to GitHub Pages

cd frontend

# Update .env.production with Cloud Run URL
echo "REACT_APP_API_URL=https://your-cloud-run-url" > .env.production

# Deploy
npm run deploy

# Or use GitHub Actions:
# 1. Go to repo Settings > Secrets
# 2. Add REACT_APP_API_URL secret with Cloud Run URL
# 3. Push to main branch

Project Structure

sar/
├── backend/                    # FastAPI backend
│   ├── main.py                # API endpoints
│   ├── gee_processing.py      # GEE SAR processing
│   ├── water_detection.py     # Water detection algorithm
│   ├── utils.py               # Helper functions
│   ├── requirements.txt       # Python dependencies
│   ├── Dockerfile             # Cloud Run deployment
│   └── run_local.py           # Local development server
├── frontend/                   # React frontend
│   ├── src/
│   │   ├── components/        # React components
│   │   ├── services/          # API integration
│   │   ├── utils/             # Validators
│   │   └── data/              # Test AOIs
│   ├── package.json           # Node dependencies
│   └── public/                # Static assets
├── docs/                       # Documentation
│   └── GEE_SETUP.md           # GEE setup guide
├── .github/                    # GitHub Actions
│   └── workflows/
│       └── deploy-frontend.yml
├── deploy.sh                   # Backend deployment script
└── README.md                   # Main documentation

Key Features Implemented

✅ FastAPI backend with Google Earth Engine integration ✅ Sentinel-1 SAR imagery processing ✅ Adaptive Otsu thresholding for water detection ✅ Manual parameter overrides for advanced users ✅ React frontend with Leaflet maps ✅ Dual basemap support (OSM + Satellite) ✅ Test AOI selector with 4 pre-loaded locations ✅ Collapsible advanced parameters panel ✅ Multi-stage progress indicators ✅ GeoJSON download functionality ✅ Cloud Run deployment configuration ✅ GitHub Pages deployment workflow ✅ Comprehensive documentation

Next Steps

  1. ✅ Complete GEE service account setup
  2. ✅ Test locally with all 4 test AOIs
  3. ✅ Deploy backend to Cloud Run
  4. ✅ Deploy frontend to GitHub Pages
  5. 📸 Add screenshots to README
  6. 🎨 Customize styling/branding
  7. 📊 Add usage analytics (optional)
  8. 🔒 Add API key authentication (optional)

Support

Happy flood detecting! 🛰️💧