geemap

What it is and what it does

Geemap bridges the gap between Google Earth Engine's Python API and interactive Jupyter-based workflows. It wraps Earth Engine's computational backend with ipyleaflet and ipywidgets to enable live map visualization, data inspection, and export—tasks that are cumbersome in the raw Earth Engine Python API. The package is built for students, researchers, and GEE JavaScript users transitioning to Python, and includes tools to convert existing GEE JavaScripts to Python automatically.

The package handles satellite imagery, geospatial datasets, and raster and vector operations through Earth Engine's catalog. It supports interactive drawing, split-panel maps, timeseries inspection, image classification, zonal statistics, and export to formats like GeoTIFF, shapefile, and GeoJSON. All visualization and interaction happen within Jupyter cells, making it suitable for exploratory analysis and reproducible research workflows.

Use it for:

• Explore and visualize satellite imagery and geospatial datasets interactively in Jupyter notebooks.
• Convert existing GEE JavaScript code to Python scripts and notebooks automatically.
• Perform zonal statistics, image classification, and accuracy assessment on Earth Engine data.
• Create animated timelapse visualizations of landscape changes over time.
• Export Earth Engine results as GeoTIFF, shapefile, or CSV for downstream analysis.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Geemap provides interactive geospatial analysis and visualization of Google Earth Engine datasets within Jupyter notebooks, with tools for mapping, data inspection, and export.

Yes, if you work with Google Earth Engine and want interactive Jupyter-based analysis. The package is actively maintained, has no known vulnerabilities, and low install friction. Requires a GEE account and Python 3.12 or later, and the 19 dependencies add bulk but are all standard geospatial tools. Ideal for research, education, and exploratory geospatial work; less suitable if you need a standalone command-line tool or non-Jupyter environment.

Install

geemap on PyPI

pip install geemap

uv add geemap

poetry add geemap

Installing geemap

Before you install

Low install friction with a pure Python wheel and active maintenance—last release 49 days ago with 4013 GitHub stars. Requires Python 3.12 or later and pulls in 19 runtime dependencies including ipyleaflet, folium, and earthengine-api, all standard geospatial libraries.

License in practice

MIT license (permissive) places no restrictions on use, modification, or distribution in commercial or private projects.

Quickstart

pip install geemap

import geemap
m = geemap.Map()
m

Requires a Google Earth Engine account and authentication; geemap will prompt for credentials on first use within a Jupyter environment.

Verify before relying

• Whether the 19 runtime dependencies are all required or some are optional for specific features.
• Performance characteristics when working with large Earth Engine datasets or high-resolution imagery.
• Compatibility with non-Jupyter environments (e.g., standard Python scripts or other IDEs).
• Specific coordinate systems and zoom levels supported by the Map constructor.

Package facts

Evidence: geemap-0.38.3-py3-none-any.whl

Keywords: geemap

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