dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R

Maus V, Camara G, Appel M, & Pebesma E (2017). dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R. Journal of Statistical Software (In Press)

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The opening of large archives of satellite data such as LANDSAT, MODIS and the SENTINELs has given researchers unprecedented access to data, allowing them to better quantify and understand local and global land change. The need to analyse such large data sets has lead to the development of automated and semi-automated methods for satellite image time series analysis. However, few of the proposed methods for re mote sensing time series analysis are available as open source software. In this paper we present the R package dtwSat . This package provides an implementation of the Time-Weighted Dynamic Time Warping method for land cover mapping using sequence of multi-band satellite images. Methods based on dynamic time warping are flexible to handle irregular sampling and out-of-phase time series, and they have achieved significant result s in time series analysis. dtwSat is available from the Comprehensive R Archive Network and contributes to making methods for satellite time series analysis available to a larger audience. The package supports the full cycle of land cover classification using image time series, ranging from selecting temporal patterns to visualising and assessing the results.

Item Type: Article
Uncontrolled Keywords: dynamic programming, MODIS time series, land cover changes, crop monitoring
Research Programs: Ecosystems Services and Management (ESM)
Related URLs:
Depositing User: Luke Kirwan
Date Deposited: 31 Mar 2017 09:05
Last Modified: 31 Mar 2017 09:19
URI: http://pure.iiasa.ac.at/14513

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