期刊
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
卷 41, 期 -, 页码 34-45出版社
ELSEVIER
DOI: 10.1016/j.jag.2015.04.015
关键词
Linear spectral mixture analysis; Change detection; Syndrome; Dryland system; Western China
资金
- National Natural Science Foundation of China [41071146]
- China Agricultural University Youth Teacher's Growth project
This study was to detect dryland degradation coupling linear spectral unmixing model of Landsat images with syndrome concept in temperate dryland system, Minqin, China. The phenological contrast and cornplementation between green vegetation fraction in summer, sandland fraction and saline land fraction in spring, was firstly structured to quantify degradation characteristics by simple correlation analysis with ground data. The spatiotemporal patterns of the three degradation indicators were interpreted with the help dust bowl syndrome, qualitatively deciphered the degradation causal clusters, loops and important consequences in the study area. The results indicate water-using and distribution pattern was changed, agricultural intensity and productivity increased, salinization lessened in oasis, whereas sandification risk heightened. This approach developed in this study, has the potentially broad applicability, for dryland system monitoring and modelling. (C) 2015 Elsevier B.V. All rights reserved.
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