EarthRISE Applied Artificial Intelligence and Deep Learning Book

The NASA EarthRISE program harnesses NASA Earth Action capabilities to deliver trusted solutions for sustained benefits to society. This book provides practitioners with a wide variety of applied examples of Remote Sensing Artificial Intelligence and Deep Learning approaches, with each chapter focusing on a specific problem set and spanning NASA Earth Action thematic areas.

📖 Read the book: nasa-earthrise.github.io/EarthRISE-Applied-Artificial-Intelligence-and-Deep-Learning-Book

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Book Outline

• Introduction
• Data Preparation (coming soon)
• Semantic Segmentation
  • Crop Mapping — Rice Mapping in Bhutan with U-Net
  • Selective Logging Detection with Very-High Resolution Imagery
  • Clay Deforestation Segmentation Model
• Object Detection (coming soon)
• Time Series
  • Soybean Yield Prediction
• Ecological Processes Simulation
  • Active Fire Detection with Bayesian Neural Networks
• Transfer Learning (coming soon)
• Fusion (coming soon)
• Downscaling (coming soon)
• Future of Deep Learning and Foundational Models
  • Evaluating Foundation Models Trained with Earth Observation Data
• Ethics and Artificial Intelligence (coming soon)
• Conclusions (coming soon)

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Building Locally

The book is built with Quarto. To render locally:

# Render both HTML and PDF
quarto render

# Preview with live reload
quarto preview

# Render a single chapter
quarto render 03_Semantic_Segmentation/01__Crop_Mapping/notebooks/Rice_Mapping_Bhutan_2021.ipynb

For PDF rendering you will also need TinyTeX:

quarto install tinytex

Notebook execution is disabled — chapters render from pre-computed outputs, so no Python environment is required to build the book.

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Contributing

See CONTRIBUTING.md for folder naming conventions, notebook structure, and how to add a new chapter.

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License and Distribution

This book is distributed under the terms of the CC BY 4.0 License. You are free to share and adapt the material with appropriate attribution.

Privacy & Terms of Use

This book abides by NASA's privacy and terms of use, available at nasa.gov/privacy.

Citation

Mayer, T., Bhandari, B., & Saah, D. (2026). EarthRISE Applied Artificial Intelligence and Deep Learning Book. Zenodo. https://doi.org/10.5281/zenodo.20547797

For individual chapter DOIs and BibTeX, see the How to Cite page.