Earth Engine and Geemap: Geospatial Data Science with Python

Get started, quickly, with Google Earth Engine and the powerful geemap Python package. Apply geemap to interactively analyze and visualize big geospatial data in a Jupyter environment.

Google Earth Engine (GEE) is a cloud computing platform that offers access to a vast data catalog of satellite imagery and geospatial datasets. The platform has gained immense popularity in the geospatial community in recent years and has played a significant role in empowering numerous environmental applications at local, regional, and global scales.

This book takes a hands-on approach to help users get started with the GEE Python API and geemap. It begins with the basics of geemap, including creating and customizing interactive maps. Then, users learn to load cloud-based Earth Engine datasets and local geospatial datasets onto the interactive maps.

As readers progress through the chapters, they will explore practical examples of using geemap to visualize and analyze Earth Engine datasets and learn how to export data from Earth Engine. Additionally, the book covers more advanced topics, such as building and deploying interactive web apps with Earth Engine and geemap.

Who this book is for

This book is designed for students, researchers, and data scientists who want to explore Google Earth Engine using the Python ecosystem of diverse libraries and tools. Regardless of whether you are a new or experienced user of the Earth Engine JavaScript API, this book is suitable for you.

Dr. Qiusheng Wu is an Associate Professor in the Department of Geography & Sustainability at the University of Tennessee, Knoxville. He is also an Amazon Visiting Academic and a Google Developer Expert (GDE) for Earth Engine. His research interests include geospatial data science, remote sensing, and environmental modeling. Dr. Wu is particularly interested in utilizing big geospatial data and cloud computing (e.g., Google Earth Engine, Microsoft Planetary Computer, Amazon Web Services) to study environmental change, especially surface water and wetland inundation dynamics. His research has been funded by NASA, USDA, and the Department of Defense. Dr. Wu is an advocate of open science and reproducible research, having developed and published various open-source packages for advanced geospatial analysis and data visualization, such as geemap, leafmap, lidar, and segment-geospatial. Check out his open-source projects at opengeos.