Remote Sensing
Showing 26 of 26 projects
A comprehensive resource of deep learning techniques and models for analyzing satellite and aerial imagery.
An open-source translator library for raster and vector geospatial data formats.
A curated collection of geospatial software, data, libraries, and resources for GIS developers and analysts.
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 Python package for interactive mapping and geospatial analysis with minimal coding in Jupyter notebooks.
A curated list of datasets, tools, methods, review papers, and competitions for remote sensing change detection.
An open source Python library and framework for building computer vision models on satellite, aerial, and large imagery sets.
A curated collection of tools, tutorials, code, and resources for Earth Observation and geospatial satellite imagery analysis.
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.
Award-winning, efficient C++ tools for processing LiDAR data in LAS/LAZ formats with multi-core batch processing.
A pure JavaScript library for parsing and reading raster data from TIFF and GeoTIFF files in both browser and Node.js environments.
An open-source framework for building multi-modal geospatial ML models that fuse satellite, drone, and weather data for agriculture and sustainability insights.
An R binding package for calling Google Earth Engine API from within R, integrating with the R spatial ecosystem.
A collection of custom JavaScript scripts for visualizing and processing satellite imagery with Sentinel Hub services.
An airborne LiDAR point cloud ground filtering method based on cloth simulation for bare earth extraction.
A Python framework for scalable organization and processing of SAR satellite data, integrating SNAP and GAMMA.
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 remote sensing dataset and pipeline for agricultural land use classification, featuring 95,186 datapoints with satellite and climatology data.
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.
A curated list of reference papers and applications for common vegetation indices used in multispectral, hyperspectral, and UAV remote sensing.
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