Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China
AbstractThe importance of accurately monitoring rangeland degradation dynamics over decades is increasing in Linxia rangeland, the birthplace of the Yellow River in China. Since 2000, the Chinese government has implemented the “Grain for Green” program and enforced a grazing ban in Gansu province, one of the most degraded provinces, to mitigate the problem of rangeland degradation. The effects of these policies are controversial and have become a topic of public concern. In this study, a grading system was established for the estimation of Linxia rangeland degradation. Degrees of rangeland degradation were interpreted and the spatio-temporal dynamics of the degraded rangeland through several study periods were mapped and monitored using the Linear Spectral Mixture Analysis method on Landsat Thematic Mapper (TM)/ETM+ (Enhanced Thematic Mapper Plus) images for the years of 1996, 2001, 2006, and 2011. The results demonstrated that the time around the year 2001 appeared to be a turning point of the rangeland degradation reversion course, as the rangeland degradation reversed significantly since 2001. From 1996 to 2001, the total degraded area in Linxia rangeland increased from 2922.01 km2 to 3048.48 km2 (+4.33%), and decreased by 4.54% to 2909.97 km2 in 2011; the non-degraded rangeland gradually increased from 602.74 km2 to 710.01 km2, an increase of 17.80%. Degraded rangeland vegetation was restored significantly during 2001–2011: the area of slightly degraded rangeland increased by 3.71% and 3.83% annually during 2001–2006 and 2006–2011 intervals, respectively, and the area of moderately and severely degraded rangeland decreased annually by 4.77% and 2.41% from 2001 to 2006, and 4.58% and 0.81% during 2006–2011, respectively. These results indicated that the “Grain for Green” program and grazing ban policy, together with other ecological impacting factors, helped reverse the rangeland degradation and promote the rehabilitation of rangeland vegetation. View Full-Text
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Yu, X.; Lu, C.; Zhao, G. Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China. Appl. Sci. 2017, 7, 241.
Yu X, Lu C, Zhao G. Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China. Applied Sciences. 2017; 7(3):241.Chicago/Turabian Style
Yu, Xinyang; Lu, Changhe; Zhao, Gengxing. 2017. "Multi-Temporal Remotely Sensed Data for Degradation Dynamics in Linxia Rangeland, Northwest China." Appl. Sci. 7, no. 3: 241.
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