Journal of Geo-information Science >
Landscape Spatial Distribution Modeling Based on CLUE-S Model in the LiaoheWatershed
Received date: 2014-05-04
Revised date: 2014-07-03
Online published: 2014-11-01
In this paper, we took the Liaohe watershed as the study area and applied the CLUE-S model for the purpose of landscape pattern simulation, based on the land use data in 2000 and 2010. Eight key driving factors were selected in this study, which include elevation, DEM, slope, distance, soil and others. Firstly, the land use data in 2000 was used to simulate the spatial pattern of land use in 2010 for the Liaohe watershed. Based on theadjusted model parameters, the land use patterns of 2020 were then simulated respectively for the natural increase scenario, economic development scenario, and ecological protection scenario. The results showed that the simulation accuracy for 2010 reached a considerably 90.7%, implying that the CLUE-S model is well fitted for modeling the land use pattern in the Liaohe watershed. In different scenarios, it shows explicitly an increase in urban land and a decrease in cultivated land. Under the economic development scenario, we concluded that: the cultivated land conversion range is the largest; the forest reduction is relatively small; and the construction land surrounding the developing zones of the Liaohe River basin had gradually expanded, which mainly aggregated in Shenyang, Fushun, Anshan and other industrial developed cities. Under the ecological protection scenario, we discovered that the forests and wetlands that located at the mouth of the Liaohe River had gradually increased. This is due to the conversion of farmland into forest in the east region. The conclusions made in this study will provide data reference and basic information for the ecological protection in the Liaohe watershed, the land use planning management, and policy-making in future.
WANG Xin, LIU Weiling, ZHANG Li, ZHANG Linbo, ZHENG Jiaoqi . Landscape Spatial Distribution Modeling Based on CLUE-S Model in the LiaoheWatershed[J]. Journal of Geo-information Science, 2014 , 16(6) : 925 -932 . DOI: 10.3724/SP.J.1047.2014.00925
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