Global shoreline mapping tool from satellite imagery

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

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

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

Sentinel Hub Cloud Detector for Sentinel-2 images in Python

Satellite image time series in R

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

a deep model that segments water on multispectral images

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

The STARFM fusion model for 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.

Application of deep learning on Satellite Imagery of Sentinel-2 satellite that move around the earth from June, 2015. This image patches can be trained and classified using transfer learning techniques.

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.

The official repository for the EuroCrops dataset.

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.

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

Docker image of ESA Sentinel Application Platform (SNAP) from http://step.esa.int/main/toolboxes/snap/ . Download at https://hub.docker.com/r/mundialis/esa-snap

To download products provided by Theia land data center : https://theia.cnes.fr

Example JavaScript source code for ArcGIS imagery apps (Landsat Explorer and Sentinel Explorer) that you can expand or customize.

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