sentinel-2
There are 303 repositories under sentinel-2 topic.
awesome-spectral-indices/awesome-spectral-indices
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
kvos/CoastSat
Global shoreline mapping tool from satellite imagery
e-sensing/sits
Satellite image time series in R
GeoscienceAustralia/dea-notebooks
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray
sentinel-hub/sentinel2-cloud-detector
Sentinel Hub Cloud Detector for Sentinel-2 images in Python
chrieke/InstanceSegmentation_Sentinel2
🌱 Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis
lennart-rth/Live-Earth-Wallpapers
A collection of all earth related space Images in one script to set as your Desktop background.
sertit/eoreader
Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
Clay-foundation/model
The Clay Foundation Model (in development)
ESDS-Leipzig/cubo
On-Demand Earth System Data Cubes (ESDCs) in Python
maja601/EuroCrops
The official repository for the EuroCrops dataset.
CNES/MAJA
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.
VSainteuf/utae-paps
PyTorch implementation of U-TAE and PaPs for satellite image time series panoptic segmentation.
isikdogan/deepwatermap
a deep model that segments water on multispectral images
ameraner/dsen2-cr
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.
langnico/global-canopy-height-model
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.
ESA-PhiLab/Major-TOM
Expandable Datasets for Earth Observation
nmileva/starfm4py
The STARFM fusion model for Python
olivierhagolle/peps_download
Tool to download Sentinel images from PEPS sentinel mirror site : https://peps.cnes.fr
EOA-team/eodal
Earth Observation Data Analysis Library
Orion-AI-Lab/S4A
Sen4AgriNet: A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation with deep learning
leftfield-geospatial/geedim
Search, composite, and download Google Earth Engine imagery.
biasvariancelabs/aitlas-arena
An open-source benchmark framework for evaluating state-of-the-art deep learning approaches for image classification in Earth Observation (EO)
raoofnaushad/Land-Cover-Classification-using-Sentinel-2-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.
xinluo2018/WatNet
A deep learning model for surface water mapping based on satellite optical image.
granularai/fabric
Urban change model designed to identify changes across 2 timestamps
strath-ai/satellite-cloud-removal-dip
Satellite cloud removal with Deep Image Prior.
qzhang95/PSTCR
Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, "Thick Cloud and Cloud Shadow Removal in Multitemporal Images using Progressively Spatio-Temporal Patch Group Learning", ISPRS Journal, 2020.
MarcYin/SIAC
A sensor invariant Atmospheric Correction (SIAC)
sentinel-hub/time-lapse
Python scripts for creating time lapse videos and gifs from Sentinel-2 images
sentinel-hub/sentinelhub-js
Download and process satellite imagery in JavaScript or TypeScript using Sentinel Hub services.
MarcYin/SIAC_GEE
SIAC GEE version
olivierhagolle/Start_maja
To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor
bellingcat/cloud-free-subregion
Google Earth Engine application that finds Sentinel-2 images that are cloud-free in a particular area of interest.
olivierhagolle/theia_download
To download products provided by Theia land data center : https://theia.cnes.fr