Biomass

Forage grass biomass modeling is designed to estimate the total mass of forage grass in a given area, including both the water and dry matter fractions. Biomass is a key indicator of rangeland productivity and can provide valuable information for understanding the amount of forage available to grazing animals. The model integrates Sentinel-2 satellite imagery with field measurements and applies machine learning algorithms to accurately estimate biomass at high spatial resolution. By analyzing the spectral reflectance of satellite imagery and relating it to ground truth biomass samples, the model generates reliable biomass predictions across a vast and diverse terrain.

Accurate biomass estimates are critical for optimizing pasture management and supporting sustainable livestock production. With timely and detailed spatial biomass information, farmers and land managers can assess forage availability, plan grazing schedules, and avoid overgrazing. The model also supports fertilization and harvesting decisions, helping to improve pasture health and productivity. By leveraging remote sensing and artificial intelligence, this approach reduces the need for labor-intensive field surveys while providing actionable insights for agricultural planning.

Usage

The processBioMass() mutation and retrieveBioMass() query are used to generate and retrieve bio mass analyses. They each require three arguments:

• polygonId
• startDate
• endDate

mutation {
  processBioMass(
    polygonId: "[YOUR POLYGON ID GOES HERE]"
    startDate: "2023-01-01"
    endDate:   "2023-07-31"
  )
  {
    IsSuccess
    Message
    Status
    Result {
      requestId
    }
  }
}

query {
  retrieveBioMass(
    polygonId: "[YOUR POLYGON ID GOES HERE]"
    startDate: "2023-01-01"
    endDate:   "2023-07-31"
  )
  {
    IsSuccess
    Message
    Status
    Result {
      tif
      png
      json
      colorlegend
    }
  }
}

Please refer to the Schema Documentation in the API Playground for more information.