Technology Application |
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The Detection and Analysis of Land Use Change in the Laoha River Basin During the Past Four Decades |
FANG Xiu-qin1, REN Li-liang2, LI Qiong-fang2 |
1. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China; 2. State Key Laboratory of Hydrology, Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China |
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Abstract On the basis of the multiple remote sensing images of Landsat MSS, TM and ETM+ and other auxiliary data, two classification approaches of decision tree and support vector machine were applied to land use/cover classifications in the semiarid Laoha river basin over the past 40 years since the 1970s. The land use changes and their spatial distribution were analyzed quantitatively and mapped with GIS techniques. The results show that land use/cover maps in 1976, 1989, 1999 and 2007 could be generated based on the implementation of support vector machine classification with satisfying results. The analysis shows that land use has changed very obviously in the study area over the last 40 years. The areas of water body and grassland have decreased while rural and urban areas increased persistently. The cultivated land area has increased substantially. Forest land and fallow land have changed in fluctuation with a decrease on the whole. It’s obvious that the most remarkable change has been the interconversion of lands for agriculture (cultivated land), for forestry (forest land), and for animal husbandry (grassland). Moreover, the spatial distribution of the conversion was greatly different in different periods. An analysis of the intensity of land use changes indicates that the highest annual rate of land use change has been increased gradually and the annual intensity has been spatially heterogeneous. Moreover, the suburbs surrounding Chifeng city always have changed intensively during the past decades, suggesting the persistent urbanization of Chifeng city.
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Keywords
ETM+
alteration
information extraction
SVM
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Issue Date: 03 June 2012
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