Summer 2024: Land-Cover Mapping with Deep Learning in ArcGIS #GISMapping

The article discusses the combination of big data, satellite imagery, and AI to create high-quality land-cover models available in ArcGIS Living Atlas of the World. These models can be used for environmental monitoring, resource management, urban planning, and more without requiring extensive training or AI expertise. The article highlights different resolution models available, such as Landsat 8 for lower resolution and Sentinel-2 for medium resolution, which can be used for various environmental monitoring and analysis purposes.

New models like Text SAM and Prithvi – Crop Classification have been added to ArcGIS Living Atlas, allowing users to classify surface features and crops using satellite imagery. The article encourages users to explore pretrained deep learning models in ArcGIS Living Atlas and learn how to use them in ArcGIS.

Overall, the article emphasizes the importance of utilizing these advanced models for land-cover mapping and environmental analysis. It also encourages users to join the conversation on Esri Community to ask questions, gain insights, and contribute ideas for additional AI-powered feature extraction tasks.

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Source link: https://www.esri.com/about/newsroom/arcnews/land-cover-mapping-with-deep-learning-in-arcgis-living-atlas-of-the-world/