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Get Started

This Get Started guide is intended as a quick way to start programming with leafmap. You can try out leafmap by using Goolge Colab (image) or Binder (image) without having to install anything on your computer.

Important Note

Leafmap has six plotting backends, including folium, ipyleaflet, plotly, pydeck,, and heremap. An interactive map created using one of the plotting backends can be displayed in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. By default, import leafmap will use the ipyleaflet plotting backend.

The six plotting backends do not offer equal functionality. The ipyleaflet plotting backend provides the richest interactive functionality, including the custom toolset for loading, analyzing, and visualizing geospatial data interactively without coding. For example, users can add vector data (e.g., GeoJSON, Shapefile, KML, GeoDataFrame) and raster data (e.g., GeoTIFF, Cloud Optimized GeoTIFF [COG]) to the map with a few clicks (see Figure 1). Users can also perform geospatial analysis using the WhiteboxTools GUI with 468 geoprocessing tools directly within the map interface (see Figure 2). Other interactive functionality (e.g., split-panel map, linked map, time slider, time-series inspector) can also be useful for visualizing geospatial data. The ipyleaflet package is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input (source). In contrast, folium has relatively limited interactive functionality. It is meant for displaying static data only. Note that the aforementioned custom toolset and interactive functionality are not available for other plotting backends. Compared with ipyleaflet and folium, the pydeck,, and heremap plotting backend provides some unique 3D mapping functionality. An API key from the Here Developer Portal is required to use heremap.

To choose a specific plotting backend, use one of the following:

  • import leafmap.leafmap as leafmap
  • import leafmap.foliumap as leafmap
  • import leafmap.deck as leafmap
  • import leafmap.kepler as leafmap
  • import leafmap.plotlymap as leafmap
  • import leafmap.heremap as leafmap

Figure 1. The leafmap user interface built upon ipyleaflet and ipywidgets.

Figure 2. The WhiteboxTools graphical user interface integrated into leafmap.

Leafmap Modules

The key functionality of the leafmap Python package is organized into nine modules as shown in the table below.

Module Description
basemaps A collection of XYZ and WMS tile layers to be used as basemaps
colormaps Commonly used colormaps and palettes for visualizing geospatial data
common Functions being used by multiple plotting backends to process geospatial data
foliumap A plotting backend built upon the folium Python package
heremap A plotting backend built upon the here-map-widget-for-jupyter
kepler A plotting backend built upon keplergl Python package
leafmap The default plotting backend built upon the ipyleaflet Python package
legends Built-in legends for commonly used geospatial datasets
osm Functions for extracting and downloading OpenStreetMap data
pc Functions for working with Microsoft Planetary Computer
plotlymap A plotting backend built upon plotly Python package
pydeck A plotting backend built upon pydeck Python package
toolbar A custom toolset with interactive tools built upon ipywidgets and ipyleaflet

Launch Jupyter notebook

conda activate env_name
jupyter notebook

Use ipyleaflet plotting backend

import leafmap
m = leafmap.Map(center=(40, -100), zoom=4)

Use folium plotting backend

import leafmap.foliumap as leafmap
m = leafmap.Map(center=(40, -100), zoom=4)

Use heremap plotting backend



Create an interactive map

import os
import leafmap.heremap as leafmap
api_key = os.environ.get("HEREMAPS_API_KEY") # read api_key from environment variable.
m = leafmap.Map(api_key=api_key, center=(40, -100), zoom=4)

Leafmap demo with ipyleaflet backend