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.

Maintainer: Victor Maus <vwmaus1 at gmail.com>

Author(s): Victor Maus*, Marius Appel*, Toni Giorgino*

Install package and any missing dependencies by running this line in your R console:

install.packages("dtwSat")

Depends R (>= 3.2.0), zoo, raster, ggplot2
Imports methods, rgdal, dtw, proxy, scales, reshape2, grDevices, RColorBrewer, plyr, stats, sp, lubridate, caret, mgcv, xtable
Suggests testthat, knitr, rmarkdown, rticles, gridExtra, grid, png, Hmisc, tikzDevice
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Package dtwSat
Materials
URL https://github.com/vwmaus/dtwSat/
Task Views
Version 0.2.3
Published 2017-05-16
License GPL (>= 2) | file LICENSE
BugReports https://github.com/vwmaus/dtwSat/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks dtwSat check results
Package source dtwSat_0.2.3.tar.gz