BlueDocs

Spatial Intelligence for the Blue Economy

Bluedocs is an interactive ocean planning tool that lets users propose offshore projects—wind farms, aquaculture sites, subsea cables—and instantly analyze spatial conflicts against real federal datasets. Drop a pin, set a radius, and get a risk score with actionable relocation recommendations.

Demo Flow

1. Explore — Full-screen dark ocean map with toggleable federal data layers (wind leases, MPAs, shipping lanes, submarine cables)
2. Propose — Click anywhere to drop a project pin, choose a type, and set a radius
3. Analyze — Conflict engine scores risk 0–100, flags overlapping protected zones and shipping corridors
4. Optimize — AI recommender suggests lower-risk locations and flies the map to the new site

Architecture

Layer	Stack	Role
Frontend	Next.js · React · Mapbox GL JS · Tailwind	Dark-themed map dashboard with glassmorphism panels, real-time layer rendering, and animated conflict visualization
Accounts	Convex	Email/password account auth and per-user persisted project lists
Backend	FastAPI · Shapely · Python	GeoJSON ingestion, spatial overlap/buffer analysis, risk scoring, and grid-search relocation engine
Data	BOEM · NOAA · MarineCadastre · TeleGeography	Real federal GeoJSON datasets for wind leases, marine protected areas, shipping lanes, and submarine cables

flowchart TD
    subgraph Frontend["Frontend · Next.js + Mapbox GL"]
        Map[Map Dashboard]
        Layers[Layer Panel]
        Modal[Project Modal]
        Panel[Conflict Panel]
    end

    subgraph Backend["Backend · FastAPI + Shapely"]
        API[API Router]
        Geo[GeoDataService]
        Engine[ConflictEngine]
        Rec[Recommender]
    end

    subgraph Data["Federal GeoJSON"]
        D1[(BOEM\nWind Leases)]
        D2[(NOAA\nMPAs)]
        D3[(MarineCadastre\nShipping)]
        D4[(TeleGeography\nCables)]
    end

    Map -- GET /api/layers --> API
    Modal -- POST /api/conflict-check --> API
    API --> Geo --> D1 & D2 & D3 & D4
    API --> Engine --> Geo
    API --> Rec --> Engine

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How Project Shapes Work

When a user drops a pin and configures a project, the frontend generates a GeoJSON polygon on the map representing the project's footprint. Four shape types are supported:

Shape	How It's Drawn	Math
Circle	64-sided regular polygon	Vertices at equal angles around center, radius converted from km to degrees via radiusKm / 6371 (Earth's radius)
Square	4-sided regular polygon rotated 45°	Same algorithm as circle but with 4 vertices and a π/4 rotation so edges align N/S/E/W
Hexagon	6-sided regular polygon	Same algorithm with 6 vertices, no rotation
Drawn	Freehand polygon from user clicks	User clicks points on the map; centroid and bounding radius are computed via haversine distance

All shapes ultimately call createRegularPolygonGeoJSON(lng, lat, radiusKm, sides, properties, rotation):

for i in 0..sides:
    angle = (i / sides) × 2π + rotation
    dLat  = (radiusKm / 6371) × cos(angle)
    dLng  = (radiusKm / 6371) × sin(angle) / cos(lat)
    → [lng + dLng, lat + dLat]  (converted to degrees)

The resulting polygon is rendered on the Mapbox map as a semi-transparent fill with a dashed border. It's also sent to the backend's ConflictEngine, which uses Shapely to:

1. Overlap check — project_polygon.intersects(layer_geometry) → flags direct spatial conflicts
2. Buffer check — Expands the project polygon by each layer's buffer distance (2–10 km) and checks for nearby features
3. Scoring — Overlap area (km²) and proximity (km) feed into the 0–100 risk score

Key Endpoints

GET  /health              → service status + loaded layer counts
GET  /api/layers           → all GeoJSON layers for map rendering
POST /api/conflict-check   → spatial analysis with risk score + recommendation

Quickstart

# Backend
cd backend
uv sync
uv run uvicorn app.main:app --port 8000

# Frontend
cd frontend
bun install
bun run convex:dev  # in another terminal (first run will set up your Convex deployment)
bun run dev

Required frontend env vars:

• NEXT_PUBLIC_MAPBOX_TOKEN
• NEXT_PUBLIC_CONVEX_URL (from Convex dashboard / convex dev)

Team

Built by Krish (backend + AI) and Partner (frontend + UX).