Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series DatasetReportar como inadecuado




Detecting Different Types of Directional Land Cover Changes Using MODIS NDVI Time Series Dataset - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

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

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





*

Author to whom correspondence should be addressed.



Academic Editors: James Campbell and Prasad S. Thenkabail

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. 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





Autor: Lili Xu 1,2, Baolin Li 1,3,* , Yecheng Yuan 1, Xizhang Gao 1, Tao Zhang 1,2 and Qingling Sun 1,2

Fuente: http://mdpi.com/



DESCARGAR PDF




Documentos relacionados