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Remote Sens. 2016, 8(6), 495; doi:10.3390/rs8060495

Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset

State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Author to whom correspondence should be addressed.
Academic Editors: James Campbell and Prasad S. Thenkabail
Received: 26 January 2016 / Revised: 13 April 2016 / Accepted: 23 May 2016 / Published: 14 June 2016
(This article belongs to the Special Issue Monitoring of Land Changes)
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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. Detected trends of land cover change indicated high consistency between NDVI (Normalized Difference Vegetation Index), change trends from LTS (Landsat Thematic Mapper and Enhanced Thematic Mapper Plus time series dataset), and MODIS (Moderate Resolution Imaging Spectroradiometer) time series datasets with the percentage of samples indicating consistency of 100%. For cropland, trends of millet yield per unit and average NDVI of cropland indicated high consistency with a linear regression determination coefficient of 0.94 (p < 0.01). Compared with other multi-target change detection methods, the changes detected by the MTHD could be related closely with specific ecosystem changes, reducing the risk of false changes in the area with frequent and strong interannual fluctuations. View Full-Text
Keywords: time series; land cover change detection; NDVI; multi-targets; directional change; abrupt change; trend change time series; land cover change detection; NDVI; multi-targets; directional change; abrupt change; trend change

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Xu, L.; Li, B.; Yuan, Y.; Gao, X.; Zhang, T.; Sun, Q. Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset. Remote Sens. 2016, 8, 495.

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