Satellite Imagery
Showing 30 of 30 projects
A comprehensive resource of deep learning techniques and models for analyzing satellite and aerial imagery.
A curated list of open-source geospatial analysis tools, libraries, and resources across multiple programming languages and domains.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
A curated list of satellite and aerial imagery datasets with annotations for computer vision and deep learning tasks.
A curated list of datasets, tools, methods, review papers, and competitions for remote sensing change detection.
A dataset of 129.6 million computer-generated building footprint polygons for the United States, derived from satellite imagery.
An open source Python library and framework for building computer vision models on satellite, aerial, and large imagery sets.
An end-to-end Python pipeline for semantic segmentation of aerial and satellite imagery to extract features like buildings and roads.
A curated collection of tools, tutorials, code, and resources for Earth Observation and geospatial satellite imagery analysis.
Train neural networks with OpenStreetMap data and satellite imagery to classify roads and map features.
A Python framework for processing spatio-temporal satellite imagery and extracting features for machine learning applications.
Interactive interface for browsing global, full-resolution satellite imagery with near real-time updates.
Search and download Copernicus Sentinel satellite images
An open-source framework for building multi-modal geospatial ML models that fuse satellite, drone, and weather data for agriculture and sustainability insights.
A collection of custom JavaScript scripts for visualizing and processing satellite imagery with Sentinel Hub services.
A macOS app that automatically sets your desktop wallpaper to the satellite or map view overhead.
An RViz plugin for displaying satellite maps and aerial imagery based on GPS coordinates.
A curated list of awesome tools, tutorials, and APIs for accessing and processing Copernicus Sentinel satellite data.
Deep learning models for crop yield prediction using remote sensing data, with CNN/LSTM and Gaussian Process approaches.
An open-source desktop app that sets live weather satellite imagery as your Mac or Windows desktop background.
An open service providing a commons of openly licensed aerial and satellite imagery and map layer services.
A configurable Mastodon bot that posts geotagged aerial imagery of random locations worldwide.
A blazing fast JavaScript raster processing engine for analyzing GeoTIFFs in browsers and Node.js.
A Python implementation of Two Source Energy Balance models for estimating evapotranspiration using remote sensing data.
A software system processing Sentinel-2 satellite imagery for agricultural monitoring and Common Agricultural Policy (CAP) management.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A JavaScript/TypeScript library for downloading and processing satellite imagery using Sentinel Hub services.
A curated index of aerial and satellite imagery sources for mapping, with efficient geographic referencing.
An interactive Swift playground that displays a slideshow of Earth photos from the DSCOVR satellite via Twitter.
A Python algorithm for smoothly blending U-Net image segmentation patches using spline interpolation and batch prediction.
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