Reverse Dependencies of geemap

The following projects have a declared dependency on geemap:

• basal-and-bark — Welcome to Basal and Bark, a spatial python package for working with forest data.
• dynamic-world — Land-use land-cover analysis using Dynamic World App from Earth Engine
• eeharvest — An automated, convenient downloader for Google Earth Engine datasets in Python
• eeSDM — Google Earth Engine-based Species Distribution Modeling
• geeft — no summary
• geeltermap — Python mapping application based on Geemap and GEE designed to provide phenology, flood and LST satellite data to eLTER sites
• geemap — A Python package for interactive mapping using Google Earth Engine and ipyleaflet
• geeViz — A package to help with GEE data processing, analysis, and visualization
• geospatial — A Python package for installing commonly used packages for geospatial analysis and data visualization with only one command.
• hagerstrand — A Python package for an interactive space-time Geographic Information System (GIS)
• iteru — Python package for a web app
• metobs-toolkit — A Meteorological observations toolkit for scientists
• ndvi2gif — Python package to create seasonal composites of NDVI or several more vegetation, water, snow, etc. indexes, and download them as pretty gifs or geotiff rasters
• open-geo-engine — no summary
• pygadm — Easy access to administrative boundary defined by GADM from Python scripts
• pygaul — Easy access to administrative boundary defined by FAO GAUL from a Python script.
• pygis — A Python package for installing optional dependencies for geemap and leafmap.
• pylst — A Python package for processing and visualizing Landsat LST data.
• rasterarea — This package provides a more accurate way to claculate the area of rasters.
• rlcms — workflows for regional land cover mapping, built in Google Earth Engine
• Seg2Map — An interactive jupyter notebook for downloading satellite imagery
• sla-sca — Snow Line Altitude (SLA) monitoring for glaciers in Argentina.
• terrapyn — Toolkit to manipulate Earth observations and models.