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Key Features

You can try out leafmap by using the cloud-computing platforms below without having to install anything on your computer:

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Install leafmap

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# !pip install leafmap geopandas pycrs osmnx

Use ipyleaflet plotting backend

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import os
import leafmap

Create an interactive map

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

Customize map height

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m = leafmap.Map(height="400px", width="800px")
m

Set control visibility

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m = leafmap.Map(
    draw_control=False,
    measure_control=False,
    fullscreen_control=False,
    attribution_control=True,
)
m

Change basemaps

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m = leafmap.Map()
m.add_basemap("OpenTopoMap")
m

Add XYZ tile layer

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m = leafmap.Map()
m.add_tile_layer(
    url="https://mt1.google.com/vt/lyrs=y&x={x}&y={y}&z={z}",
    name="Google Satellite",
    attribution="Google",
)
m

Add WMS tile layer

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m = leafmap.Map(center=[40, -100], zoom=4)
naip_url = "https://www.mrlc.gov/geoserver/mrlc_display/NLCD_2019_Land_Cover_L48/wms?"
m.add_wms_layer(
    url=naip_url,
    layers="NLCD_2019_Land_Cover_L48",
    name="NLCD 2019",
    attribution="MRLC",
    format="image/png",
    shown=True,
)
m.add_legend(title="NLCD Land Cover Type", builtin_legend="NLCD")
m

Add COG layer

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m = leafmap.Map()
url = "https://github.com/opengeos/data/releases/download/raster/Libya-2023-07-01.tif"
m.add_cog_layer(url, name="Fire (pre-event)")
m

Add STAC layer

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m = leafmap.Map()
url = "https://canada-spot-ortho.s3.amazonaws.com/canada_spot_orthoimages/canada_spot5_orthoimages/S5_2007/S5_11055_6057_20070622/S5_11055_6057_20070622.json"
m.add_stac_layer(url, bands=["B3", "B2", "B1"], name="False color")
m

Add legend

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m = leafmap.Map()
url = "https://www.mrlc.gov/geoserver/mrlc_display/NLCD_2016_Land_Cover_L48/wms?"
m.add_wms_layer(
    url,
    layers="NLCD_2016_Land_Cover_L48",
    name="NLCD 2016 CONUS Land Cover",
    format="image/png",
    transparent=True,
)
m.add_legend(builtin_legend="NLCD")
m

Add colorbar

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m = leafmap.Map()
m.add_basemap("USGS 3DEP Elevation")
colors = ["006633", "E5FFCC", "662A00", "D8D8D8", "F5F5F5"]
vmin = 0
vmax = 4000
m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax)
m

Add GeoJSON

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m = leafmap.Map(center=[0, 0], zoom=2)
in_geojson = (
    "https://github.com/opengeos/datasets/releases/download/vector/cables.geojson"
)
m.add_geojson(in_geojson, layer_name="Cable lines")
m

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# Add a GeoJSON with random filled color to the map.
m = leafmap.Map(center=[0, 0], zoom=2)
url = "https://raw.githubusercontent.com/opengeos/leafmap/master/examples/data/countries.geojson"
style = {"fillOpacity": 0.5}
m.add_geojson(
    url,
    layer_name="Countries",
    style=style,
    fill_colors=["red", "yellow", "green", "orange"],
)
m

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# Use custom style and hover_style functions.
m = leafmap.Map(center=[0, 0], zoom=2)
url = "https://raw.githubusercontent.com/opengeos/leafmap/master/examples/data/countries.geojson"
style = {
    "stroke": True,
    "color": "#0000ff",
    "weight": 2,
    "opacity": 1,
    "fill": True,
    "fillColor": "#0000ff",
    "fillOpacity": 0.1,
}
hover_style = {"fillOpacity": 0.7}
m.add_geojson(url, layer_name="Countries", style=style, hover_style=hover_style)
m

Add shapefile

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m = leafmap.Map(center=[0, 0], zoom=2)
in_shp = "https://github.com/opengeos/leafmap/raw/master/examples/data/countries.zip"
m.add_shp(in_shp, layer_name="Countries")
m

Add KML

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try:
    import geopandas
except ImportError:
    print("Installing geopandas ...")
    subprocess.check_call(["python", "-m", "pip", "install", "geopandas"])

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m = leafmap.Map()
in_kml = "https://raw.githubusercontent.com/opengeos/leafmap/master/examples/data/us_states.kml"
m.add_kml(in_kml, layer_name="US States KML")
m

Add GeoDataFrame

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import geopandas as gpd

m = leafmap.Map()
gdf = gpd.read_file(
    "https://github.com/opengeos/datasets/releases/download/vector/cables.geojson"
)
m.add_gdf(gdf, layer_name="Cable lines")
m

Create heat map

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m = leafmap.Map()
in_csv = "https://raw.githubusercontent.com/opengeos/leafmap/master/examples/data/world_cities.csv"
m.add_heatmap(
    in_csv,
    latitude="latitude",
    longitude="longitude",
    value="pop_max",
    name="Heat map",
    radius=20,
)

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colors = ["blue", "lime", "red"]
vmin = 0
vmax = 10000
m.add_colorbar(colors=colors, vmin=vmin, vmax=vmax)
m.add_title("World Population Heat Map", font_size="20px", align="center")
m

Save map to HTML

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m = leafmap.Map()
m.add_basemap("Esri.NatGeoWorldMap")
m

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m.to_html("mymap.html")

Add Planet imagery

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os.environ["PLANET_API_KEY"] = "your-api-key"

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m = leafmap.Map()
m.add_planet_by_month(year=2020, month=8)
m.add_planet_by_quarter(year=2019, quarter=2)
m