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A fast way to retrieve water surface area time-series from Sentinel-2 and Landsat in GEE
Super-resolution of 10 Sentinel-2 bands to 5-meter resolution, starting from L1C or L2A (Theia format) products.
Conformal prediction for Google Earth Engine
A QGIS plugin tool using Segment Anything Model (SAM) to accelerate segmenting or delineating landforms in geospatial raster images.
A CNN based image segmentation tool oriented to marine data analysis
R code for estimating total suspended solids(TSS) from remote sensing data
Implementation of the Hard and Soft PLS-DA for MATLAB
Code to process ICESat-2 ATL03 photon returns into refraction corrected bathymetry and collocate the data to reflectance values from Landsat 8 multispectral data (Processed in the SeaDAS program) t…
This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datas…
Satellite-Derived Bathymetry using Convolutional Neural Networks
Karlsruhe Library of Urban Materials (KLUM) - a spectral library containing material samples and relevant metadata
Neural Network based Urban Change Detection with Deep-Temporal Multispectral and SAR Remote Sensing Data.
Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.
🌲🌉 Species distribution models with Bayesian additive regression trees
Python based GUI for Satellite Derived Bathymetry processing
AROSICS - Automated and Robust Open-Source Image Co-Registration Software
Earth observation processing framework for machine learning in Python
This repository contains the source code of the COINS tool that allows to deduce natural continuity of street network.
A procedure for autonomous reference data sampling, model training and image classification.
Qgis plugin to estimate nearshore bathymetry using multispectral images
A Python script for preforming refraction correction on Structure from Motion datasets.