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Ambio. Nov 2011; 40(7): 807–818.
Published online Jun 7, 2011. doi:  10.1007/s13280-011-0157-1
PMCID: PMC3357753
Remote Sensing Change Detection and Process Analysis of Long-Term Land Use Change and Human Impacts
Qiming Zhou,corresponding author1 Baolin Li,2 and Yumin Chen3
1Department of Geography, Centre for Geo-computation Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
2State Key Laboratory of Environment and Resources Information System, Institute of Geographical Sciences and Resources Research, Chinese Academy of Sciences, Beijing, 100101 People’s Republic of China
3School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan, Hubei, 430079 People’s Republic of China
Qiming Zhou, Phone: +852-34115048, Fax: +852-34115990, qiming/at/hkbu.edu.hk.
corresponding authorCorresponding author.
Received February 3, 2010; Revised April 1, 2011; Accepted May 4, 2011.
Abstract
This study investigates environmental change over a 30-year period and attempts to gain a better understanding of human impacts on an arid environment and their consequences for regional development. Multi-temporal remotely sensed imagery was acquired and integrated to establish the basis for change detection and process analysis. Land cover changes were investigated in two categories, namely categorical change using image classification and quantitative change using a vegetation index. The results show that human-induced land cover changes have been minor in this remote area. However, the pace of growth of human-induced change has been accelerating since the early 1990s. The analysis of the multi-temporal vegetation index also shows no overall trend of rangeland deterioration, although local change of vegetation cover caused by human activities was noticeable. The results suggest that the current trend of rapid growth may not be sustainable and that the implementation of effective counter-measures for environmentally sound development is a rather urgent matter.
Keywords: Remote sensing, Land use change, Change detection, Human impact assessment, Arid zone
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