leafmap | Python package for interactive mapping | Map library
kandi X-RAY | leafmap Summary
kandi X-RAY | leafmap Summary
Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). Leafmap has a toolset with various interactive tools that allow users to load vector and raster data onto the map without coding. In addition, users can use the powerful analytical backend (i.e., WhiteboxTools) to perform geospatial analysis directly within the leafmap user interface without writing a single line of code. The WhiteboxTools library currently contains 468 tools for advanced geospatial analysis, such as GIS Analysis, Geomorphometric Analysis, Hydrological Analysis, LiDAR Data Analysis, Mathematical and Statistical Analysis, and Stream Network Analysis.
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Top functions reviewed by kandi - BETA
- Plot a plot
- Get layers
- Return a dictionary of layers
- Return map layer layers
- Adds points to the plot
- Add a legend
- Check if the provided color is valid
- Convert rgb to hex
- Add data to the plot
- Create a legend
- Create a netCDF tile layer
- Convert xyz to a map
- Add a raster
- Convert a numpy array to a ROOT file
- Displays linked maps
- Add a point layer
- Adds labels to the layer
- Add velocity layer
- Add a netCDF layer
- Clip an image
- Split a map into a tileset
- Plot a colormap
- Adds data to the marker cluster
- Add a colormap
- Convert xyz data to folium dict
- Add a STAC layer
leafmap Key Features
leafmap Examples and Code Snippets
Community Discussions
Trending Discussions on leafmap
QUESTION
I currently have an issue in which the Leaflets mapping API is currently showing in front of my dropdown menu overlaying it and hiding it, however, does not currently stop the user from using the drop downs nor the map.
Current Page HTML
and
Current CSS
(only for the map space, drop downs and the columns below the map)
ANSWER
Answered 2021-Feb-07 at 15:38SOLVED: Z indexing-
The map itself was overlaying and must have had a hidden Z index within the API, this was overlaying most things above it.
In changing the .Dropdown-content class to a higher Z index of 20 the drop down menu was able to display over the map once again.
QUESTION
I am new at react redux (and hooks) and I've been following this general tutorial:
I'm also interested in using react-leaflet, which at the time of this writing is on v3 which uses hooks. I've gotten as far as being able to load data containing an array of latlng to generate markers:
...ANSWER
Answered 2020-Dec-06 at 21:03To handle marker click events use eventHandlers
prop and listen to click event inside on Markers
comp like this:
QUESTION
I have a map component inside rc-tabs component
...ANSWER
Answered 2020-Mar-16 at 13:35Obviously you have not set a height to the map properly and also there is somethign wrong with the leaflet.css import in your code
Here is how it should be:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install leafmap
You can use leafmap like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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