Explore live open-source projects and AI models.

A Python-based project for processing and analyzing geospatial data using machine learning techniques, leveraging libraries like GeoPandas, Scikit-learn, and Folium. Includes examples for spatial analysis, visualization, and predictive modeling with real-world geographic datasets.

Working with keprel.gl on Python to analysis Geospatial data-3D visualize Geospatial data -Animate Geospatial data -Create Choropleth Map

A step-by-step guide to using Folium on Python: Porto, Portugal Taxi Dataset;Geospatial Data Visualization to: -Create Dot distribution map for most common places where a taxi is requested -Create Bar Chart to find the Rush hour -Identify the street with the most traffic during Rush hours

An overview of the Folium library to visualize Geospatial data

Geospatial data analysis with Python - NumPy, Pandas, GeoPandas

A declarative geospatial library for Python to make data-science with maps easier

R 'reticulate' wrapper for `segment-geospatial` 'Python' package for segmenting geospatial data with the ‘Segment Anything Model’ (SAM).

Material for the EGU23 Short Course: "Introduction to Geospatial Raster and Vector Data with Python"

This project creates an interactive map of any city with marked points of interest (POIs) using Python and various geospatial libraries. The city's geospatial data is obtained from an open-source platform like OpenStreetMap or GeoJSON. Users can explore different POIs on the interactive map.

This Python package and web UI allow you to seamlessly convert GeoTiff data into 3D meshes, making geospatial data visualization and analysis a breeze. Whether you're working with elevation maps, terrain models, or any other geospatial information stored in GeoTiff files, this tool simplifies the... Read more