Multi-Layer Analytics

Precision agriculture is capable of generating vast amounts of data in the form of yield data, satellite imagery, and soil fertility, among others. The lack of easy-to-use cloud precision software toolkits that assist crop producers in converting field data layers into useful knowledge and actionable recommendations limits the application of precision agricultural technologies. In precision agriculture, management zones are areas within a field that have similar yield potential based on soil type, slope position, soil chemistry, microclimate, and/or other factors that influence crop production. The producer’s knowledge of a field is a very important piece of the process. Management zones are thought of as a mechanism to optimize crop inputs and yield potential.

The big challenge is to build management zones that perfectly reflect field variability. A combination of different layers like satellite imagery, soil fertility, topography derivatives, and yield monitor data is the next logical step to generate more responsive management zones.

Multi-layer analytics (also known as integrated analysis) is becoming a part of the GeoPard geospatial analytics engine.

Classic combinations of integrated analysis parameters include one or more yield data, NDVI map, elevation, and soil sensor physicochemical characteristics. GeoPard supports these parameters and in addition, allows the inclusion of other field data layers either already available in the system or uploaded directly by the user (soil sampling, yield datasets, etc.). As a result, you are free to operate with the complete set of parameters doing integrated analytics:

Yield data Remote sensing data:

  • Potential productivity map (single-year and multi-year)

  • Stability/variation map

  • Vegetation indices NDVI, EVI2, WDRVI, LAI, SAVI, OSAVI, GCI, GNDVI


  • Digital elevation

  • Slope

  • Curvature

  • Wetness index

  • Hillshades

Soil data:

  • pH

  • CEC (cation exchange capacity)

  • SOM (soil organic matter)

  • K (potassium)

  • Thin topsoil depth, lower available water holding capacity (drought-prone soil)

  • EC (electrical conductivity)

  • and other chemical attributes available in the uploaded dataset

It’s important to emphasize that custom factors are configured on top of every data layer to assign the desired layer weight. You are very welcome to share your integrated analytics use cases, and build management zones maps based on your knowledge of the field while selecting data sources and their weights in GeoPard.

Pictures contain a sample field with data layers (like a productivity map covering 18 years, digital elevation model, slope, hillshade, 2019 yield data) and various combinations of integration analytics maps. You can follow the steps of the evolution of management zones while extending integration analytics with an additional data layer.

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