Showing 1-15 of 15 projects
A collection of techniques for deep learning with satellite and aerial imagery, including object detection and classification.
GDAL is an open-source library for working with various geospatial data formats, useful for remote sensing and GIS applications.
A comprehensive collection of geospatial tools and resources for data analysis, machine learning, and spatial applications.
TorchGeo is a Python library for working with geospatial data using PyTorch, providing datasets, samplers, transforms, and pre-trained models.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
List of satellite image training datasets with annotations for computer vision and deep learning
An open-source library for deep learning on satellite and aerial imagery using Python and PyTorch.
A curated list of tools and resources for working with Earth observation and geospatial satellite imagery data.
A curated list of Google Earth Engine resources for geospatial analysis and remote sensing applications.
An advanced geospatial data analysis platform for tasks like geomorphology, hydrology, and remote sensing.
A community-driven catalog of geospatial datasets for use with Google Earth Engine.
A collection of datasets for deep learning with satellite and aerial imagery.
GRASS is a free and open-source geospatial processing engine for spatial data analysis and visualization.
A curated list of Spectral Indices for Remote Sensing applications, focused on Earth Engine and satellite imagery.
A Python library for searching and downloading Copernicus Sentinel satellite images for geographic data analysis.
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