Global shoreline mapping tool from satellite imagery
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Updated
Jun 3, 2024 - Jupyter Notebook
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.
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.
The official repository for the EuroCrops dataset.
A deep learning model for surface water mapping based on satellite optical image.
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.
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