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Techniques for deep learning with satellite & aerial imagery
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
Datasets for deep learning with satellite & aerial imagery
framework for large-scale SAR satellite data processing
Implementation of Machine Learning and Deep Learning techniques to find insights from the satellite data.
Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.
AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.
Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.
Generalized data analysis workflow via a consistent easy to use interface.
DSen2-CR: A network for removing clouds from Sentinel-2 images. This repo contains the model code, written in Python/Keras, as well as links to pre-trained checkpoints and the SEN12MS-CR dataset.
API to get enormous amount of high resolution satellite images from satellites.pro quickly through multi-threading! create map your own map dataset. Bringing data to Humans.
A comprehensive list of NASA Earth science data products
Maritime vessel detection from remote sensing SAR data, based on the architectures of the Faster-RCNN and YOLOv5 networks.
Interactive tools for spectral mixture analysis of multispectral raster data in Python
A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification
Software behind the RACE dashboard by ESA and the European Commission (https://race.esa.int), the Green Transition Information Factory - GTIF (https://gtif.esa.int), as well as the Earth Observing Dashboard by NASA, ESA, and JAXA (https://eodashboard.org)
An open-source benchmark framework for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO)
Multi-Class Semantic Segmentation on Dubai's Satellite Images.