Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China
AbstractLand use and land cover (LULC) models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development) and protection scenarios (ecological and cultivated land protection). The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection. View Full-Text
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Han, H.; Yang, C.; Song, J. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China. Sustainability 2015, 7, 4260-4279.
Han H, Yang C, Song J. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China. Sustainability. 2015; 7(4):4260-4279.Chicago/Turabian Style
Han, Huiran; Yang, Chengfeng; Song, Jinping. 2015. "Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China." Sustainability 7, no. 4: 4260-4279.