vwmaus/dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis

Provides an implementation of the Time-Weighted Dynamic Time Warping (TWDTW) method for land cover mapping using satellite image time series. TWDTW is based on the Dynamic Time Warping technique and has achieved high accuracy for land cover classification using satellite data. The method is based on comparing unclassified satellite image time series with a set of known temporal patterns (e.g. phenological cycles associated with the vegetation). Using 'dtwSat' the user can build temporal patterns for land cover types, apply the TWDTW analysis for satellite datasets, visualize the results of the time series analysis, produce land cover maps, create temporal plots for land cover change, and compute accuracy assessment metrics.

Getting started

Package details

AuthorVictor Maus [aut, cre] (<https://orcid.org/0000-0002-7385-4723>), Marius Appel [ctb], Nikolas Kuschnig [ctb], Toni Giorgino [ctb]
MaintainerVictor Maus <[email protected]>
LicenseGPL (>= 2) | file LICENSE
URL https://github.com/vwmaus/dtwSat/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
vwmaus/dtwSat documentation built on Nov. 11, 2019, 2:36 p.m.