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 compares 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.

Version:	0.2.6
Depends:	R (≥ 3.2.0), zoo, raster, snow, ggplot2
Imports:	methods, rgdal, dtw, proxy, scales, reshape2, grDevices, RColorBrewer, plyr, stats, sp, lubridate, caret, mgcv, xtable, Rdpack, data.table
Suggests:	gridExtra, grid, png, Hmisc, rbenchmark
Published:	2020-03-03
Author:	Victor Maus [aut, cre], Marius Appel [ctb], Nikolas Kuschnig [ctb], Toni Giorgino [ctb]
Maintainer:	Victor Maus <vwmaus1 at gmail.com>
BugReports:	https://github.com/vwmaus/dtwSat/issues
License:	GPL (≥ 3) | file LICENSE
URL:	https://github.com/vwmaus/dtwSat/
NeedsCompilation:	yes
Citation:	dtwSat citation info
Materials:	NEWS
CRAN checks:	dtwSat results

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