Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
microsoft cntk geospatial-data neural-networks image-classification image-segmentation azure-storage land-cover land-use geospatial-analysis microsoft-azure microsoft-machine-learning cntk-model azure-batchai
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Updated
Jul 25, 2019 - Jupyter Notebook