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Leafmap

Python package for interactive geospatial mapping and analysis inside Jupyter notebooks

As of 1 September 2026, Leafmap is free to use. An academic open source library, not a product. Softwr lists it under Libraries. Leafmap is made by Leafmap contributors, led by Qiusheng Wu, available on Linux, Windows, macOS.

Overview

What Leafmap does

Leafmap is a Python package for interactive mapping and geospatial analysis in Jupyter notebooks. It provides a consistent API over several plotting backends including ipyleaflet, folium, MapLibre, pydeck and KeplerGL, and bundles helpers for loading vector and raster data, cloud-optimised GeoTIFFs, STAC catalogues, Earth Engine assets, basemaps and simple analysis, plus interactive widgets for drawing and inspecting layers. It exists for a specific reason. Doing interactive geospatial work in a notebook previously meant learning several unrelated libraries and writing a lot of boilerplate, and most of those libraries assume a JavaScript front end. Leafmap collapses that into a few function calls, which is why it spread quickly through university teaching, remote sensing coursework and research notebooks. It is MIT licensed with no licence fee and nothing to purchase. The project is maintained principally by Qiusheng Wu, an academic at the University of Tennessee, with contributions from the open source geospatial community and funding largely from research grants and institutional support rather than commercial revenue. That is the fact a team should weigh: Leafmap is excellent for analysis and teaching, but a single-maintainer academic package with a fast-moving API and a dependency on several third-party backends is a risky foundation for a production application with a five-year support horizon.

What people use it for

  • A remote sensing course where students need interactive maps without learning JavaScript or a desktop GIS
  • A researcher exploring STAC-hosted satellite imagery inside a notebook before committing to a processing pipeline
  • An analyst producing a shareable interactive map from a GeoDataFrame in a handful of lines
  • A team prototyping a geospatial visualisation before deciding whether to build it properly in a web framework

The honest half

Where it falls short

Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Leafmap.

  • It is a Python library rather than an application, so there is nothing to buy, nothing to install for a non-technical colleague and no interface outside a notebook environment.
  • Maintenance rests largely on one academic maintainer with grant funding, which makes long-term continuity a real consideration for anything beyond research use.
  • The API has moved quickly across releases, so notebooks written against an older version can break on upgrade, which undermines reproducibility in exactly the research settings where it is popular.
  • It abstracts over several third-party backends, so a bug or a rendering limitation is often in ipyleaflet, folium or MapLibre rather than in Leafmap, and diagnosing it means understanding the layer underneath anyway.
  • Large datasets rendered through notebook widgets become slow or unresponsive, so it does not scale to the data volumes a dedicated tiling service or desktop GIS handles comfortably.

Cross-shopped

What people choose instead of Leafmap

Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.

  • Leafmap logo
    Leafmap
    vs
    Kepler.gl logo
    Kepler.gl

    Kepler.gl: If the goal is a shareable interactive visualisation rather than notebook-driven analysis

  • Leafmap logo
    Leafmap
    vs
    Q
    QGIS

    QGIS: A full desktop GIS for people who do not work in Python

  • Leafmap logo
    Leafmap
    vs
    deck.gl logo
    deck.gl

    deck.gl: For building a production web visualisation rather than a notebook prototype

Pricing

What Leafmap costs

Taken from the vendor's own pricing page. Prices move, so check before you buy.

Leafmap

Free

  • MIT licence
  • Installed from PyPI or conda-forge
  • No usage limits
  • Community support through GitHub issues and discussions
  • No commercial support available

Capabilities

Features

  • Multiple mapping backends

    One API across ipyleaflet, folium, MapLibre, pydeck and KeplerGL

  • Notebook interactivity

    Draw, inspect and query layers directly in Jupyter

  • Raster and COG support

    Loads local rasters and cloud-optimised GeoTIFFs from URLs

  • STAC catalogue access

    Searches and displays SpatioTemporal Asset Catalog items

  • Earth Engine integration

    Displays Google Earth Engine layers where a user has access

  • Basemap library

    Hundreds of preconfigured basemaps

  • Vector data handling

    Reads GeoJSON, shapefiles and GeoPackage with sensible defaults

  • Split map comparison

    Side-by-side comparison of two layers in one view

Answered, with sources

Questions people ask

Each answer names the page it came from, so you can check it rather than take our word for it.

Is Leafmap a product?

No. It is an MIT-licensed Python package installed from PyPI or conda-forge. There is nothing to purchase.

Who maintains it?

Primarily Qiusheng Wu at the University of Tennessee, with community contributors, funded through research grants rather than sales.

Can I buy support?

No commercial support offering exists. Help comes from GitHub issues and the community.

Is it suitable for a production web application?

It is not designed for that. Use it for analysis and prototyping, then build production maps on MapLibre, deck.gl or a hosted service.

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Softwr does not host reviews and shows no star rating for Leafmap, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.

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