A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
-
Updated
Jun 10, 2024 - Python
A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
A Python package for installing commonly used packages for geospatial analysis and data visualization with only one command.
Geo Assist is a spatial library to manage spatial data in-memory.
A collection of Jupyter notebooks for GEE Courses
A streamlit app template based on streamlit-option-menu
A Python package for visualizing and analyzing hyperspectral data in coastal regions
A streamlit multipage app template for geospatial applications
A Python package for installing optional dependencies for geemap and leafmap.
A template for building a mkdocs website
A collection of Jupyter notebooks for geospatial applications
Leafmap for Jupyterlite
A template for Solara web apps
A multi-page streamlit web app template for geospatial applications
GitHub workflows for building GDAL, geemap, leafmap, and other geospatial packages
Visualizing the Maxar Open Data for the 2023 North India Floods (pre and post event images) on the split map using leafmap.
To analyze the COVID-19 situation in Japan and identify trends and insights using publicly available data, focusing on nonlinear regression and geographical analysis.
Streamlit app for visualizing and labeling COGs
Add a description, image, and links to the leafmap topic page so that developers can more easily learn about it.
To associate your repository with the leafmap topic, visit your repo's landing page and select "manage topics."