Agromonitoring (Agro API)

Agriculture · Weather & Environment

The Agromonitoring Agro API is a satellite-based crop monitoring and agricultural weather API developed by the OpenWeather team, providing farm field monitoring through satellite imagery analysis and integrated meteorological data. The platform is specifically designed for agritech developers and precision agriculture application builders who need to combine satellite vegetation health monitoring with weather intelligence in a single API integration, covering registered farm field polygons across Nigeria and globally.

paid

API Key

Configurable based on plan

✗ Not Available

Best For

Precision agriculture with integrated weather and satellite

Pricing

Part of the OpenWeatherMap ecosystem — the same API key can be used across OpenWeatherMap and Agro Monitoring products. Free tier allows a limited number of field polygons. Nigeria farmland is within global satellite coverage.

Key Highlights

  • Part of the OpenWeatherMap platform — combines historical and forecast weather data with satellite NDVI and EVI indices in one API
  • Polygon-based field management lets you define farm boundaries and receive satellite imagery and indices specific to those areas
  • Soil moisture data derived from satellite measurements provides field-level irrigation decision support for precision farming
  • NDVI and EVI time series show vegetation trends over a growing season — useful for tracking crop development and anomaly detection
  • Historical satellite imagery archive enables retrospective analysis of crop performance across previous growing seasons

Required Access Documents

  • API KeyRequired
    Sign up for a developer account to obtain an API key/credentials.

Use Cases

  • Weather-Satellite Integration:Combine weather forecasts with satellite data for comprehensive intelligence.
  • Vegetation Monitoring:Monitor crop vegetation using NDVI and EVI from satellites.
  • Soil Moisture Tracking:Track soil moisture from satellite data for irrigation optimization.
  • Disease Risk Prediction:Predict disease pressure combining weather and crop health data.
  • Yield Forecasting:Forecast yields using integrated weather and satellite information.

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