We are happy to inform our user community that ArcGIS Living Atlas of the World not only provides a collection pretrained deep learning models, but also provides World Imagery as a high-resolution imagery source for automated feature extraction.
Acquiring high-resolution aerial and satellite imagery may not be feasible for some organizations. Visually inspecting or hand digitizing features from imagery can be time consuming, tedious, and expensive. AI and deep learning can help save time and money by automating manual processes, but not everyone has the expertise or resources to train a deep learning model. If you are experiencing any of these limitations, we just might have a solution for you.
This learning tutorial will walk you through a step-by-step workflow using a pretrained deep learning model from Living Atlas to detect building footprints from the World Imagery basemap in ArcGIS Pro. While this tutorial focuses specifically on building footprint extraction, you will find a number of pretrained deep learning models in Living Atlas that you can leverage to extract a variety of information.

Find the full tutorial by @RobertWaterman here.
Visit the ArcGIS Living Atlas home page to learn about what's new and how to use content. See the ArcGIS Living Atlas blog for more blog articles that help you get the most out of Living Atlas.
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