A ready-to-use curated list of Spectral Indices for Remote Sensing applications.

Global shoreline mapping tool from satellite imagery

Satellite image time series in R

Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray

Sentinel Hub Cloud Detector for Sentinel-2 images in Python

🌱 Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis

The Clay Foundation Model - An open source AI model and interface for Earth

A collection of all earth related space Images in one script to set as your Desktop background.

Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.

The official repository for the EuroCrops dataset.

On-Demand Earth System Data Cubes (ESDCs) in Python

Expandable Datasets for Earth Observation

PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.

This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.

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.

Level-2A processor used for atmospheric correction and cloud-detection. The active repository is the one below, this one is kept to leave access to the older issues.

a deep model that segments water on multispectral images

The STARFM fusion model for Python

A deep learning model for surface water mapping based on satellite optical image.

Tool to download Sentinel images from PEPS sentinel mirror site : https://peps.cnes.fr