Skip To Content

Introduction to the model

Banner page for the model

In modern agriculture, crop classification plays a crucial role. It provides essential information that can assist in tasks such as early crop monitoring and water irrigation management. However, classifying crops poses a significant challenge for policymakers due to the complexity involved in differentiating between crop types. The growing accessibility to satellite imagery with high temporal and spectral information and advancement in machine learning methods have paved the way for automated monitoring and management of agricultural production and land use on a large scale.

The Prithvi-100M-multi-temporal-crop-classification pretrained model has been developed by NASA and IBM by fine-tuning their foundation model for earth observation—the Prithvi -100m, multitemporal crop classification dataset. Use this model to automate the process of identifying and classifying different crops in multispectral satellite imagery.

License requirements

To complete this workflow, the following are the license requirements:

  • ArcGIS DesktopArcGIS Image Analyst extension for ArcGIS Pro
  • ArcGIS EnterpriseArcGIS Image Server with raster analytics configured
  • ArcGIS OnlineArcGIS Image for ArcGIS Online

Model details

This model has the following characteristics:

  • Input—Raster (18 bands composite raster), mosaic dataset, or image service.
  • Output—Classified raster with 13 classes from cropland data layer.
  • Compute—This workflow is compute intensive and a GPU with compute capability of 6.0 or higher is recommended.
  • Applicable geographies—This model is expected to work well in the United States.
  • Architecture—This model packages the IBM and NASA Prithvi-100M-multitemporal crop classification model and uses a self-supervised encoder developed with a ViT architecture and Masked AutoEncoder (MAE) learning strategy.
  • Training Data—This model fine-tunes the pretrained Prithvi-100m model using the multitemporal crop classification dataset.
  • Accuracy metrics—This model has a mean intersection over union of 0.43 and mean accuracy of 64.06 percent.

Access and download the model

Download the Prithvi - Crop Classification pretrained model from ArcGIS Living Atlas of the World. Alternatively, access the model directly from ArcGIS Pro, or consume it in ArcGIS Image for ArcGIS Online.

  1. Browse to ArcGIS Living Atlas of the World.
  2. Sign in with your ArcGIS Online credentials.
  3. Search for Prithvi - Crop Classification and open the item page from the search results.
  4. Click the Download button to download the model.

    You can use the downloaded .dlpk file directly in ArcGIS Pro, or upload and use it in ArcGIS Enterprise. Additionally, you can fine-tune the pretrained model if necessary.

Release notes

The following are the release notes:

DateDescription

January 2024

First release of Prithvi - Crop Classification