DemeterEye

🌍 Live App: https://demetereye-web-1060536779509.us-central1.run.app/

🪐 Project presentation: canva.com

🚀 Developed as part of NASA's International Space Apps Challenge 2025 – a global hackathon empowering teams to solve real-world problems using NASA's open data and satellite imagery.

DemeterEye is an end-to-end field intelligence platform that combines NASA Harmonized Landsat Sentinel (HLS) imagery, agronomic models, and farmer-supplied data to surface vegetation trends, anomalies, and yield projections. This repository brings together the cloud-native API, the geospatial processing service, the map-driven web dashboard, and the iOS mobile application that make up the DemeterEye experience.

Web UI Demo

iOS UI Demo

Highlights

• Full-stack reference implementation for remote sensing-driven crop monitoring
• Chipnik Monitor service ingests HLS tiles, detects anomalies, and publishes daily/forecast time series
• Go REST API provides authenticated access to fields, reports, and operations backed by MongoDB
• React + Leaflet web app for drawing fields, reviewing NDVI/EVI histories, and requesting new analyses
• Native iOS app for mobile field monitoring with seasonal summaries and anomaly notifications
• Dockerfiles and GitHub Actions for deploying each component to Google Cloud Run

Repository Layout

• api/ - Go 1.24 service that fronts MongoDB, wraps JWT auth, and brokers report generation requests
• chipnik_monitor/ - Python 3.10+ analytics stack with FastAPI endpoints, Streamlit dashboard, and Prophet forecasting
• web/ - React client with Leaflet tooling for field management and report visualisation
• ios/ - Native iOS application for mobile field monitoring with seasonal tracking and notifications
• media/ - Shared branding assets referenced by documentation and the web client
• .github/workflows/ - CI/CD pipelines for deploying the API, web client, and on-premise monitor images

Prerequisites

• Python 3.10 or newer with GDAL/rasterio system libraries
• Go 1.24 toolchain
• Node.js 20+ and npm 10+
• MongoDB instance (local or cloud)
• NASA Earthdata credentials with access to HLS collections
• Google Cloud SDK (optional, for Cloud Run deployments)
• Xcode 26 (for iOS development)

Quick Start (Local Development)

1. Set up shared infrastructure
   • Start a MongoDB instance and note the connection string.
   • Obtain an Earthdata bearer token and keep it handy for the monitor service.
2. Run the Chipnik Monitor processor

   cd chipnik_monitor
   python -m venv .venv
   # Windows: .venv\Scripts\Activate
   # macOS/Linux: source .venv/bin/activate
   pip install -r requirements.txt
   cp .env_example .env  # fill EARTHDATA_BEARER_TOKEN, MONGO_URI, MONGO_DB, DAYS_BACK_LIMIT
   uvicorn api:app --reload --host 0.0.0.0 --port 8000

   The FastAPI docs become available at http://127.0.0.1:8000/docs. Optional: launch the Streamlit UI with streamlit run chipnik_monitor.py in a separate terminal for manual explorations.
3. Start the DemeterEye API

   cd api
   export MONGO_URI="mongodb://127.0.0.1:27017"
   export MONGO_DB="demetereye"
   export PROCESSOR_URL="http://127.0.0.1:8000"
   export JWT_SECRET="change_me"
   go run ./...

   The API exposes Swagger docs at http://127.0.0.1:8080/swagger/index.html.
4. Launch the web client

   cd web
   npm install
   VITE_API_BASE="http://127.0.0.1:8080" npm run dev

   Visit http://127.0.0.1:5173 to draw fields, request reports, and visualise Chipnik outputs.
5. Build the iOS app (optional)

   cd ios
   open DemeterEye.xcodeproj

   Configure the API endpoint in the app settings and build to a simulator or device through Xcode.

Environment Variables

Chipnik Monitor (chipnik_monitor/.env)

Key	Purpose
EARTHDATA_BEARER_TOKEN	Token used to fetch HLS imagery from NASA services
MONGO_URI	MongoDB connection string (shared with the API)
MONGO_DB	Database name for reports and job metadata
DAYS_BACK_LIMIT	Optional lookback window for historical imagery (defaults to 2000 days)

DemeterEye API

Key	Purpose
MONGO_URI	MongoDB connection string
MONGO_DB	Database name (must match the monitor service)
PROCESSOR_URL	Base URL of the Chipnik Monitor FastAPI service
JWT_SECRET	Symmetric secret for signing/verifying user tokens
PORT	HTTP port (defaults to 8080)

Web Client

Key	Purpose
VITE_API_BASE	Base URL for the DemeterEye API (e.g. http://127.0.0.1:8080)

Deployment & Automation

• deploy-chipnik-monitor.yml and deploy-chipnik-monitor-self-hosted.yml publish the monitor service to Cloud Run or self-hosted runners.
• deploy-chipnik-monitor.yml uses the on-premise Dockerfile in chipnik_monitor/on-premise/ for GPU-friendly builds.
• API and web subdirectories include reference gcloud run deploy commands in their READMEs and Dockerfiles for container builds.
• build.ps1 and build.sh under chipnik_monitor/on-premise/ package air-gapped artifacts for environments without Cloud Run.

Additional Resources

• Processor docs: chipnik_monitor/README.md
• API reference & OpenAPI spec: api/openapi.yaml
• Front-end notes and deployment snippet: web/README.md
• iOS app documentation: ios/README.md

iOS App Features

The mobile application helps farmers monitor field health using NASA Earth observation data:

• Login and management of multiple fields
• Map view with field boundaries
• Track field greenness and seasonal growth history
• Seasonal summaries with start, and peak of season dates
• Summaries and predictions for crop flowering

Contributions and feedback are welcome. Please open an issue or discussion if you plan to add new data sources, crop profiles, or deployment targets.

🏷️ Tags

NASA • Space Apps Challenge • AgriTech • Remote Sensing • Climate Intelligence • AI for Agriculture • Geospatial • Sustainability