satellite-data

Techniques for deep learning with satellite & aerial imagery

Satellite imagery for dummies.

A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery

framework for large-scale SAR satellite data processing

Datasets for deep learning with satellite & aerial imagery

Implementation of Machine Learning and Deep Learning techniques to find insights from the satellite data.

AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.

Generalized data analysis workflow via a consistent easy to use interface.

Algorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.

Download and process GOES-16 and GOES-17 data from NOAA's archive on AWS using Python.

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.

Interactive tools for spectral mixture analysis of multispectral raster data in Python

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.

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)

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

End-to-end solution for overhead image analysis

Python scripts to download and preprocess air pollution concentration level data aquired from the Sentinel-5P mission

Tools for Downloading, Customizing, and Processing Time Series of Satellite Images from Landsat, MODIS, and Sentinel

Maritime vessel detection from remote sensing SAR data, based on the architectures of the Faster-RCNN and YOLOv5 networks.

Multi-Class Semantic Segmentation on Dubai's Satellite Images.