气候变化领域集成服务门户(CCPortal): Improved change monitoring using an ensemble of time series algorithms

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DOI	10.1016/j.rse.2019.04.018
	Improved change monitoring using an ensemble of time series algorithms
	Bullock E.L.; Woodcock C.E.; Holden C.E.
发表日期	2020
ISSN	00344257
卷号	238
英文摘要	An ensemble of time series algorithms improves land change monitoring. The methodology combines the Continuous Change Detection and Classification (CCDC; Zhu & Woodcock, 2014) and Cumulative Sum of Residuals (CUSUM) algorithms for break detection and the Chow Test (Chow, 1960) for removing false positives (or breaks in time series not representing land change). The algorithms included are based on fundamentally different approaches to change detection and therefore offer unique advantages. The ensemble, or the combination of the three algorithms, was applied to 3 Landsat scenes in the United States and the results were assessed based on their ability to correctly discern structural breaks from stable time periods. The CUSUM test was shown to detect significant breaks 84.18% of the time and the Chow Test correctly removed breaks in 87.4% of the breaks analyzed. The ensemble produced results with lower frequency of errors of omission and commission (Type-I and Type-II errors) than a single algorithm approach. These results indicate that using a combination of break detection algorithms can be an improvement over typical approaches that utilize only one algorithm. © 2019 Elsevier Inc.
英文关键词	Change detection; Land cover monitoring; Landsat; Structural break detection; Time series analysis
语种	英语
scopus关键词	Motion picture editing machines; Algorithm approaches; Change detection; Land cover; LANDSAT; Lower frequencies; Structural break; Time series algorithms; Type I and type II errors; Time series analysis; algorithm; ensemble forecasting; land cover; land use change; Landsat; methodology; monitoring system; time series analysis; United States
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179482
作者单位	Department of Earth and Environment, Boston University, 685 Commonwealth Avenue, Boston, MA 02215, United States
推荐引用方式 GB/T 7714	Bullock E.L.,Woodcock C.E.,Holden C.E.. Improved change monitoring using an ensemble of time series algorithms[J],2020,238.
APA	Bullock E.L.,Woodcock C.E.,&Holden C.E..(2020).Improved change monitoring using an ensemble of time series algorithms.Remote Sensing of Environment,238.
MLA	Bullock E.L.,et al."Improved change monitoring using an ensemble of time series algorithms".Remote Sensing of Environment 238(2020).