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Advances in Meteorology
Volume 2013 (2013), Article ID 908307, 9 pages
Research Article

Projection of the Spatially Explicit Land Use/Cover Changes in China, 2010–2100

1Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
2Bureau of Science and Technology for Development, Chinese Academy of Sciences, Beijing 100864, China
3Shenzhen Environmental Monitoring Center, Shenzhen, Guangdong 518049, China
4Institute of Geographic and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
5State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China

Received 18 July 2013; Accepted 31 August 2013

Academic Editor: Xiangzheng Deng

Copyright © 2013 Yongwei Yuan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Land use/cover change (LUCC) is an important part of the global environmental change. This study predicted the future structure of land use/cover on the basis of the Global Change Assessment Model (GCAM) and an econometric model with the socioeconomic factors as the driving forces. The future spatial pattern of land use/cover in China was simulated with the Dynamics of Land System (DLS) under the Business as Usual scenario, Rapid Economic Growth scenario and Cooperate Environmental Sustainability scenario. The simulation results showed that the land use/land cover in China will change continually due to the human activities and climate change, and the spatial pattern of land use/cover will also change as time goes by. Besides, the spatial pattern of land cover in China under the three scenarios is consistent on the whole, but with some regional differences. Built-up area will increase rapidly under the three scenarios, while most land cover types will show a decreasing trend to different degrees under different scenarios. The simulation results can provide an underlying land surface data and reference to the methodology research on the prediction of LUCC.