Leafmap
Leafmap
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 interfaces [GUIs]). 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 500+ tools for advanced geospatial analysis, such as GIS Analysis, Geomorphometric Analysis, Hydrological Analysis, LiDAR Data Analysis, Mathematical and Statistical Analysis, and Stream Network Analysis.
https://github.com/opengeos/leafmap
Leafmap Examples
https://github.com/opengeos/leafmap/tree/master/examples
Weitere Links
WhiteboxTools
WhiteboxTools is an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph’s Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, classification, and common image transformations. WhiteboxTools also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. LiDAR point clouds can be interrogated (LidarInfo, LidarHistogram), segmented, tiled and joined, analyized for outliers, interpolated to rasters (DEMs, intensity images), and ground-points can be classified or filtered. WhiteboxTools is not a cartographic or spatial data visualization package; instead it is meant to serve as an analytical backend for other data visualization software, mainly GIS.
https://github.com/jblindsay/whitebox-tools
python-geospatial
A collection of Python packages for geospatial analysis with binder-ready notebook examples. Launch the interactive notebook tutorials with mybinder.org or binder.pangeo.io test all the pre-installed Python pakcages for geospatial analysis. https://github.com/opengeos/python-geospatial
Awesome Earth Engine
A curated list of Google Earth Engine resources. Please visit the Awesome-GEE GitHub repo if you want to contribute to this project.
Example: https://code.earthengine.google.com/04d67399bf5577419f0ccc750fe4ff9f
https://github.com/opengeos/Awesome-GEE https://spatialthoughts.com/2020/04/04/ndvi-time-series-gee-qgis/
Demo JupytlerLite Wasm
A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
Leaflet Log
Install
https://book.leafmap.org/chapters/1_get_started.html#geospatial-data-science
``` conda create -n geo python conda activate geo conda install -c conda-forge mamba mamba install -c conda-forge pygis