Victor Maus
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Time-Weighted Dynamic Time Warping
Plugin for Satellite Image Time Series visualization
Time-Weighted Dynamic Time Warping for satellite image time series analysis
PostGIS Versioning System pgvs - Base System and QGIS Client
This repository contains the code to quantify global fores loss due to mining
Repositories
74Compilation of statistical accounting of data on mineral production
PostGIS Versioning System pgvs - Base System and QGIS Client
This repository provides R scripts to integrate global mining land use datasets and link to mineral commodities
Time-Weighted Dynamic Time Warping
No description provided.
A beautiful, simple, clean, and responsive Jekyll theme for academics
Github Pages template for academic personal websites, forked from academicpages/academicpages.github.io
Time-Weighted Dynamic Time Warping for satellite image time series analysis
This repository contains the code to quantify global fores loss due to mining
Plugin for Satellite Image Time Series visualization
No description provided.
No description provided.
Relative Elevation Model in Python using xarray
Overview of Digital Elevation Model (DEM) datasets
Satellite image time series in R
Data for demos and test of the sits package
This repository contains the R script to produce the mining data gap map for the Nature commentary
Landsat Collection 2 Level-2 Science Products
Research Proposal Master Thesis: Improving reproducibility in Earth Science
Mining and tailings dam detection in satellite imagery using deep learning
Examples of using the Planetary Computer
No description provided.
R Markdown Résumés and CVs
Book for APS 240, Data Analysis with R, in the Department of Animal and Plant Sciences at the University of Sheffield
R Bindings for the UCR Suite for fast time series subsequence search
LiCSBAS: InSAR time series analysis package using LiCSAR products
A Python tool for estimating velocity and time-series from Interferometric Synthetic Aperture Radar (InSAR) data.
SIAC GEE version
Using SNAP as InSAR processor for StaMPS
Stanford Method for Persistent Scatterers