Welcome to geemap¶
A Python package for interactive geospatial analysis and visualization with Google Earth Engine
- GitHub repo: https://github.com/gee-community/geemap
- Documentation: https://geemap.org
- PyPI: https://pypi.org/project/geemap
- Conda-forge: https://anaconda.org/conda-forge/geemap
- 360+ GEE notebook examples: https://github.com/giswqs/earthengine-py-notebooks
- GEE Tutorials on YouTube: https://youtube.com/@giswqs
- Free software: MIT license
Acknowledgment: The geemap project is supported by the National Aeronautics and Space Administration (NASA) under Grant No. 80NSSC22K1742 issued through the Open Source Tools, Frameworks, and Libraries 2020 Program.
The book Earth Engine and Geemap: Geospatial Data Science with Python, written by Qiusheng Wu, has been published by Locate Press in July 2023. If you're interested in purchasing the book, please visit this URL: https://locatepress.com/book/gee.
If you find geemap useful in your research, please consider citing the following papers to support my work. Thank you for your support.
- Wu, Q., (2020). geemap: A Python package for interactive mapping with Google Earth Engine. The Journal of Open Source Software, 5(51), 2305. https://doi.org/10.21105/joss.02305
- Wu, Q., Lane, C. R., Li, X., Zhao, K., Zhou, Y., Clinton, N., DeVries, B., Golden, H. E., & Lang, M. W. (2019). Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine. Remote Sensing of Environment, 228, 1-13. https://doi.org/10.1016/j.rse.2019.04.015 (pdf | source code)
Check out the geemap workshop presented at the GeoPython Conference 2021. This workshop gives a comprehensive introduction to the key features of geemap.
Below is a partial list of features available for the geemap package. Please check the examples page for notebook examples, GIF animations, and video tutorials.
- Display Earth Engine data layers for interactive mapping.
- Create split-panel maps with Earth Engine data.
- Retrieve Earth Engine data interactively using the Inspector Tool.
- Interactive plotting of Earth Engine data by simply clicking on the map.
- Convert data format between GeoJSON and Earth Engine.
- Use drawing tools to interact with Earth Engine data.
- Use shapefiles with Earth Engine without having to upload data to one's GEE account.
- Export Earth Engine FeatureCollection to other formats (i.e., shp, csv, json, kml, kmz).
- Export Earth Engine Image and ImageCollection as GeoTIFF.
- Extract pixels from an Earth Engine Image into a 3D numpy array.
- Calculate zonal statistics by group.
- Add a customized legend for Earth Engine data.
- Add animated text to GIF images generated from Earth Engine data.
- Add colorbar and images to GIF animations generated from Earth Engine data.
- Create Landsat timelapse animations with animated text using Earth Engine.
- Search places and datasets from Earth Engine Data Catalog.
- Use timeseries inspector to visualize landscape changes over time.
- Export Earth Engine maps as HTML files and PNG images.
- Search Earth Engine API documentation within Jupyter notebooks.
- Import Earth Engine assets from personal account.
- Publish interactive GEE maps directly within Jupyter notebook.
- Add local raster datasets (e.g., GeoTIFF) to the map.
- Perform image classification and accuracy assessment.
- Extract pixel values interactively and export as shapefile and csv.
I have created a YouTube Channel for sharing geemap tutorials. You can subscribe to my channel for regular updates. If there is any specific tutorial you would like to see, please submit a feature request here.