A comprehensive predictive flood risk assessment system for NYC subway stations that combines real-time weather data, FEMA flood zones, stormwater modeling, and crowdsourced reports to predict flooding and suggest proactive mitigation strategies.

• Predictive Risk Assessment: Machine learning model that calculates flood probability for each station
• Interactive Risk Map: Color-coded subway stations by flood risk (green=safe, red=critical)
• Time-based Forecasting: Slider to see risk predictions for T+1h, T+6h, T+12h, T+24h
• Station Detail Panels: Comprehensive risk analysis with mitigation suggestions
• Crowdsourced Reporting: Real-time flood reports from riders
• Mitigation Planning: Cost-effective solutions with implementation timelines

1. Subway Entrances/Exits: NYS/MTA entrances dataset with coordinates & metadata

   • Source: Data.gov - NY State

2. Stormwater Flood Polygons: NYC Stormwater Flood Maps (rainfall-based flooding)

   • Source: NYC Open Data

3. MTA Real-time Alerts: Live service disruptions and alerts

   • Source: MTA Developer Portal

4. Basemap & Visualization: Mapbox for interactive mapping

   • Source: Mapbox

• Node.js 18+
• npm or yarn
• Mapbox account (free tier available)

1. Install dependencies

   npm install

2. Set up environment variables

   cp .env.example .env.local

   Add your Mapbox token to .env.local:

   NEXT_PUBLIC_MAPBOX_TOKEN=your_mapbox_token_here
   

   Get a free token at: https://account.mapbox.com/access-tokens/

3. Run the development server

   npm run dev

4. Open your browser Navigate to http://localhost:3000

• Rainfall Intensity: Real-time and forecasted precipitation (inches/hour)
• Station Elevation: Height above sea level for each entrance
• Distance to Water: Proximity to nearest water body or storm drain
• Land Cover: Impervious surface ratio in surrounding area
• FEMA Flood Zone: Official flood risk classification
• Drainage Capacity: Local stormwater infrastructure capacity
• Historical Floods: Past flooding events at each station

• Flood Probability: 0-100% likelihood of flooding
• Severity Score: 0-10 scale for flood impact
• Time to Flood: Estimated minutes until flooding begins

• Weighted Risk Calculation: Combines multiple factors with learned weights
• Real-time Updates: Adjusts predictions based on current weather
• Historical Learning: Incorporates past flood events for accuracy
• Geospatial Analysis: Uses Turf.js for distance and intersection calculations

• Frontend: Next.js 15, React 19, TypeScript
• Mapping: Mapbox GL JS with custom risk visualization
• Styling: Tailwind CSS with responsive design
• Data Processing: Turf.js for geospatial calculations
• Icons: Lucide React
• Date Handling: date-fns
• Predictive Modeling: Custom risk assessment algorithms

• Color-coded subway entrances by flood risk (red = high, orange = medium, green = low)
• Flood zone overlays showing stormwater accumulation areas
• Real-time alert markers for active flooding incidents
• Clickable entrances for detailed information

• Flood risk assessment with exposure percentage
• Active alerts (both MTA official and crowdsourced)
• Suggested mitigation strategies with cost estimates
• Crowdsourced flood reporting form

• Key statistics: total entrances, high-risk count, active alerts
• Real-time refresh capability
• Last updated timestamp

The flood risk calculation considers:

• Proximity to stormwater flood zones
• Historical flood depth data
• Real-time weather and alert data
• Entrance elevation and drainage characteristics

src/
├── app/                    # Next.js app router
├── components/            # React components
│   ├── Dashboard.tsx      # Main dashboard component
│   ├── FloodMap.tsx      # Mapbox map component
│   ├── EntrancePanel.tsx # Side panel for entrance details
│   └── StatusHeader.tsx  # Header with statistics
├── lib/                   # Utilities and services
│   ├── dataService.ts    # Data fetching and processing
│   └── constants.ts      # Configuration constants
├── types/                 # TypeScript type definitions
├── data/                  # Mock data for development
└── app/api/              # API routes

• DataService: Centralized data fetching from NYC APIs
• FloodMap: Mapbox integration with custom layers
• EntrancePanel: Detailed view with mitigation suggestions
• Risk Calculator: Geospatial analysis for flood exposure

1. Define types in src/types/index.ts
2. Add API endpoints to src/lib/constants.ts
3. Implement fetch logic in src/lib/dataService.ts
4. Update visualization in src/components/FloodMap.tsx

Edit the calculateFloodRisk method in src/lib/dataService.ts to adjust:

• Distance thresholds for flood zones
• Weight factors for different risk types
• Risk level boundaries

Update MITIGATION_OPTIONS in src/lib/constants.ts with new suggestions including:

• Cost estimates
• Implementation timeframes
• Effectiveness ratings

The application is responsive and works on mobile devices with:

• Touch-friendly map interactions
• Responsive panel layouts
• Optimized performance for mobile networks

1. Connect your GitHub repository to Vercel
2. Add environment variables in Vercel dashboard
3. Deploy automatically on push to main branch

# Build image
docker build -t transit-flood-monitor .

# Run container
docker run -p 3000:3000 transit-flood-monitor

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

This project is open source and available under the MIT License.

For questions or issues:

1. Check existing GitHub issues
2. Create a new issue with detailed description
3. Include steps to reproduce any bugs

Built with ❤️ for NYC transit riders and flood resilience.