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Monitoring and analysis of grassland desertification dynamics using Landsat images in Ningxia, China.

Authors :
Li, Jinya
Yang, Xiuchun
Jin, Yunxiang
Yang, Zhi
Huang, Wenguang
Zhao, Lina
Gao, Tian
Yu, Haida
Ma, Hailong
Qin, Zhihao
Xu, Bin
Source :
Remote Sensing of Environment. Nov2013, Vol. 138, p19-26. 8p.
Publication Year :
2013

Abstract

Abstract: State and local governments in China have implemented a series of grassland protection policies to address the problem of grassland degradation. In 2003, Ningxia was the first province to implement a province-wide grazing ban. The effect of this ban is contentious at all levels of government and has become a topic of public concern. Grassland desertification is the most direct indicator of the effect of the grazing ban. We selected 14 counties and cities in north-central Ningxia as the study area. A desertification classification and grading system for Ningxia's grassland was then designed based on fieldwork and expert review. Using the Spectral Mixture Analysis (SMA) and decision-tree methods, we interpreted Landsat TM/ETM+ images of the study area during four years: 1993, 2000, 2006 and 2011. The following results were obtained: from 1993 to 2011, the area of desertified grassland in north-central Ningxia decreased gradually from 8702km2 in 1993 to 7485km2 in 2011, a decrease of 13.98%; the degree of desertification gradually decreased from 3573km2 of severely desertified grassland in 1993 to 1450km2 in 2011, a decrease of 59.41%; desertified grassland vegetation was restored rapidly during 2000–2006 and 2006–2011, reducing the total area of desertified grassland annually by 1.87 and 0.61%, respectively; finally, the area of severely desertified grassland decreased annually by 5.78 and 6.28% during 2000–2006 and 2006–2011, respectively. These results show that the region-wide grazing ban, together with other ecological engineering measures, has helped reverse desertification and promote the restoration of grassland vegetation. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
00344257
Volume :
138
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
90312722
Full Text :
https://doi.org/10.1016/j.rse.2013.07.010