One of the key challenges in monitoring wildfires lies in distinguishing burn scars from non-burnt and assessing the extent of damage. This differentiation is crucial to assist emergency responders in their decision-making ability. Satellite imagery enriched with high temporal and spectral information, coupled with advancements in machine learning methods, present an avenue for automated monitoring and management of post-wildfire landscapes on a large scale. The burn scar deep learning model can emerge as an indispensable tool to tackle the task of accurately identifying and mapping the aftermath of wildfires from satellite imagery.
The Prithvi-100M-burn-scar pretrained model has been developed by NASA and IBM by fine-tuning their foundation model for earth observation—the Prithvi-100m, HLS Burn Scar Scenes dataset. Use this model to automate the process of classifying burn scars in multispectral satellite imagery.
License requirements
To complete this workflow, the following are the license requirements:
- ArcGIS Desktop—ArcGIS Image Analyst extension for ArcGIS Pro
- ArcGIS Enterprise—ArcGIS Image Server with raster analytics configured
- ArcGIS Online—ArcGIS Pro or Professional Plus user type.
Model details
This model has the following characteristics:
- Input—Raster, mosaic dataset, or image service of 6-band composite.
- Output—Classified raster with two classes (no burn and burn scar).
- 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 across the globe.
- Architecture—This model packages the IBM and NASA Prithvi-100M-burn-scar 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 HLS Burn Scar Scenes dataset .
- Accuracy metrics—This model has an IoU of 0.73 on the burn scar class and 96 percent overall accuracy.
Access and download the model
Download the Prithvi - Burn Scars Segmentation 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.
- Browse to ArcGIS Living Atlas of the World.
- Sign in with your ArcGIS Online credentials.
- Search for Prithvi - Burn Scars Segmentation and open the item page from the search results.
- 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:
| Date | Description |
|---|---|
| January 2024 | First release of Prithvi - Burn Scars Segmentation |