A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
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Updated
May 16, 2024 - Python
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
Sentinel Hub Cloud Detector for Sentinel-2 images in Python
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
The Clay Foundation Model (in development)
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.
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.
To download products provided by Theia land data center : https://theia.cnes.fr
Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor
Earth Observation Data Analysis Library
A collection of all earth related space Images in one script to set as your Desktop background.
Search, composite, and download Google Earth Engine imagery.
Land surface classification using remote sensing data with unsupervised machine learning (k-means).
Near Real Time monitoring of satellite image time-series
An LSTM to generate a crop mask for Togo
On-Demand Earth System Data Cubes (ESDCs) in Python
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