remote sensing Article Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset Lili Xu 1,2, Baolin Li 1,3,*, Yecheng Yuan 1, Xizhang Gao 1, Tao Zhang 1,2 and Qingling Sun 1,2 1 State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
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[email protected] (Q.S.) 2 University of Chinese Academy of Sciences, Beijing 100049, China 3 Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China * Correspondence:
[email protected]; Tel.: +86-010-6488-9072 Academic Editors: James Campbell and Prasad S. Thenkabail Received: 26 January 2016; Accepted: 23 May 2016; Published: 14 June 2016 Abstract: This study proposed a multi-target hierarchical detection (MTHD) method to simultaneously and automatically detect multiple directional land cover changes. MTHD used a hierarchical strategy to detect both abrupt and trend land cover changes successively. First, Grubbs’ test eliminated short-lived changes by considering them outliers. Then, the Brown-Forsythe test and the combination of Tomé’s method and the Chow test were applied to determine abrupt changes. Finally, Sen’s slope estimation coordinated with the Mann-Kendall test detection method was used to detect trend changes. Results demonstrated that both abrupt and trend land cover changes could be detected accurately and automatically. The overall accuracy of abrupt land cover changes was 87.0% and the kappa index was 0.74.