
The NASA EarthRISE Applied Artificial Intelligence and Deep Learning Book provides practitioners with applied examples of Remote Sensing AI and Deep Learning across NASA Earth Action thematic areas. Each chapter focuses on a specific problem domain — semantic segmentation, time series analysis, ecological process simulation, and foundation model evaluation — combining theoretical background with practical hands-on Jupyter notebooks. The book spans multiple frameworks (TensorFlow, PyTorch) and thematic areas including agriculture, forestry, fire ecology, and geospatial AI foundation model evaluation.
remote sensing, foundation models, EarthRISE, GeoAI, deep learning, earth observation, applied AI, time series, NASA, Jupyter notebooks, semantic segmentation
remote sensing, foundation models, EarthRISE, GeoAI, deep learning, earth observation, applied AI, time series, NASA, Jupyter notebooks, semantic segmentation
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