文章基本信息

标题：dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R
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作者：Victor Maus ; Gilberto Câmara ; Marius Appel 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2019
卷号：88
期号：1
页码：1-31
DOI：10.18637/jss.v088.i05
出版社：University of California, Los Angeles
摘要：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 analyze such large data sets has led to the development of automated and semi-automated methods for satellite image time series analysis. However, few of the proposed methods for remote 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 results in time series analysis. Package dtwSat is available from the Comprehensive R Archive Network (CRAN) 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 visualizing and assessing the results.
关键词：dynamic programming; MODIS time series; land cover changes; crop monitoring.
其他关键词：dynamic programming;MODIS time series;land cover changes;crop monitoring