03 creating maps

Introduction¶

Geemap has six plotting backends, including folium, ipyleaflet, plotly, pydeck, kepler.gl, 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, kepler.gl, 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

Uncomment and execute the following code block to install geemap if needed.

In [1]:

# !pip install geemap

# !pip install geemap

The ipyleaflet plotting backend¶

You can simply use geemap.Map() to create the default map.

In [2]:

import geemap

import geemap

In [3]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

Out[3]:

Make this Notebook Trusted to load map: File -> Trust Notebook

To customize the map, you can specify various parameters, such as center ([lat, lon]), zoom, width, and height.

In [4]:

Map = geemap.Map(center=[40, -100], zoom=4, height=600)
Map

Map = geemap.Map(center=[40, -100], zoom=4, height=600) Map

Out[4]:

You can also set the visibility of the controls, such as data_ctrl, zoom_ctrl, fullscreen_ctrl, draw_ctrl, measure_ctrl, scale_ctrl, layer_ctrl, toolbar_ctrl, and attribution_ctrl. You can also set lite_mode=True to only show the Zoom Control.

In [5]:

Map = geemap.Map(data_ctrl=False, toolbar_ctrl=False, draw_ctrl=False)
Map

Map = geemap.Map(data_ctrl=False, toolbar_ctrl=False, draw_ctrl=False) Map

Out[5]:

Make this Notebook Trusted to load map: File -> Trust Notebook

In [6]:

Map = geemap.Map(lite_mode=True)
Map

Map = geemap.Map(lite_mode=True) Map

Out[6]:

Make this Notebook Trusted to load map: File -> Trust Notebook

The folium plotting backend¶

In [7]:

import geemap.foliumap as geemap

import geemap.foliumap as geemap

In [8]:

Map = geemap.Map(height=600)
Map

Map = geemap.Map(height=600) Map

Out[8]:

The plotly plotting backend¶

In [9]:

import geemap.plotlymap as geemap

import geemap.plotlymap as geemap

In [10]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

The pydeck plotting backend¶

In [11]:

import geemap.deck as geemap

import geemap.deck as geemap

In [12]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

Out[12]:

The kerler.gl plotting backend¶

In [13]:

import geemap.kepler as geemap

import geemap.kepler as geemap

In [14]:

Map = geemap.Map()
Map

Map = geemap.Map() Map

The heremap plotting backend¶

An API key from the Here Developer Portal is required to use heremap.

In [15]:

import os
import geemap.heremap as geemap

import os import geemap.heremap as geemap

In [16]:

api_key = os.environ.get(
    'HEREMAPS_API_KEY'
)  # Provide your Heremap API key here if it is not set as an environment variable.

api_key = os.environ.get( 'HEREMAPS_API_KEY' ) # Provide your Heremap API key here if it is not set as an environment variable.

In [17]:

Map = geemap.Map(api_key)
Map

Map = geemap.Map(api_key) Map

---

Last update: 2022-03-25