geemap
A Python package for interactive mapping using Google Earth Engine and ipyleaflet
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Google Earth Engine account and authentication; geemap will prompt for credentials on first use within a Jupyter environment.
- 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 · maintenance · safety
MIT (permissive) — MIT license (permissive) places no restrictions on use, modification, or distribution in commercial or private projects.
last release 2026-06-26 (49 days) · last repo commit 2026-08-12 · 4,013 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 166,131 downloads/mo, #10,508 on PyPI
Alternatives
Verify before relying
pip install geemap
import geemap
m = geemap.Map()
m- 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.
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 on it.
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
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.
Requires a Google Earth Engine account and authentication; geemap will prompt for credentials on first use within a Jupyter environment.
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()
mVerify 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
| License | MIT permissive |
| Python support | Supports the current Python release >=3.12 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 19 packagesanywidgetbqplotearthengine-apieereprfoliumgeocoderipyeventsipyfilechooseripyleafletmatplotlibnumpypandasplotlypyperclippyshppython-boxrequestsscoobyxarray |
| Maintenance | Actively maintained 49 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 166,131 / month, #10,508 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: geemap-0.38.3-py3-none-any.whl
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See also earthengine-api · eerepr · leafmap · whiteboxgui · jupyter-leaflet · whitebox · xee · torchgeo · sentinelhub · datacube