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Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset
Xu L. L.; Li, B. L.; Yuan, Y. C.; Gao, X. Z.; Zhang, T.; Sun, Q. L.
Source PublicationRemote Sensing
2016
Volume8
Issue6
Keywordtime series land cover change detection NDVI multi-targets directional change abrupt change trend change horqin sandy land forest disturbance vegetation activity shelter forests trend analysis china degradation ecosystems impacts climate
AbstractThis 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 Tome'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.
Indexed BySCI
Language英语
ISSN2072-4292
DOI10.3390/rs8060495
Citation statistics
Cited Times:14[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/43332
Collection历年回溯文献
Recommended Citation
GB/T 7714
Xu L. L.,Li, B. L.,Yuan, Y. C.,et al. Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset. 2016.
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