Dynamic urban expansion simulation at regional scale is one of the important research methodologies in Land Use/Cover Change （LUCC） and global environmental change influenced by urbanization. However, previous studi...Dynamic urban expansion simulation at regional scale is one of the important research methodologies in Land Use/Cover Change （LUCC） and global environmental change influenced by urbanization. However, previous studies indicate that the single urban expansion simulation for future scenarios at local scale cannot meet the requirements for characterizing and interpreting the interactive mechanisms of regional urbanization and global environmental change. This study constructed a regional Dynamic Urban Expansion Model （Reg-DUEM） suitable for different scenarios by integrating the Artificial Neural Network （ANN） and Cellular Automaton （CA） model. Firstly we analyzed the temporal and spatial characteristics of urban expansion and acquired a prior knowledge rules using land use/cover change datasets of Beijing-Tianjin-Tangshan metropolitan area. The future urban expansion under different scenarios is then simulated based on a baseline model, economic models, policy models and the structural adjustment model. The results indicate that Reg-DUEM has good reliability for a non-linear expansion simulation at regional scale influenced by macro-policies. The simulating results show that future urban expansion patterns from different scenarios of the metropolitan area have the tremendous spatio-temporal differences. Future urban expansion will shift quickly from Beijing metropolis to the periphery of Tianjin and Tangshan city along coastal belt.展开更多
The impervious surface area （ISA） at the regional scale is one of the important environmental factors for examining the interaction and mechanism of Land Use/Cover Change （LUCC）-ecosystem processes-climate change ...The impervious surface area （ISA） at the regional scale is one of the important environmental factors for examining the interaction and mechanism of Land Use/Cover Change （LUCC）-ecosystem processes-climate change under the interactions of urbanization and global environmental change. Timely and accurate extraction of ISA from remotely sensed data at the regional scale is challenging. This study explored the ISA extraction based on MODIS and DMSP-OLS data and the incorporation of China＇s land use/cover data. ISA datasets in Beijing-Tianjin-Tangshan Metropolitan Area （BTTMA） in 2000 and 2008 at a spatial resolution of 250 m were developed, their spatiotemporal changes were analyzed, and their impacts on water quality were then evaluated. The results indicated that ISA in BTTMA increased rapidly along urban fringe, transportation corridors and coastal belt both in intensity and extents from 2000 to 2008. Three cities （Tangshan, Langfang and Qinhuangdao） in Hebei Province had higher ISA growth rates than Beijing due to the pressure of population-resour- ces-environments in the city resulting in increasingly transferring industries to the nearby areas. The dense ISA distribution in BTTMA has serious impacts on water quality in the Haihe River watershed. Meanwhile, the proportion of ISA in sub-watersheds has significantly linear relationships with the densities of river COD and NH3-N.展开更多
基金The Young Scientist Fund of National Natural Science Foundation of China, No.40901224 National Basic Research Program of China, No.2010CB950900+2 种基金 Opening Foundation of State Key Laboratory of Remote Sensing Science, No.2009KFJJ005 Opening Foundation of State Key Lab of Resources and Environmental Information System, No.A0725 Swedish Research Links, No.2006-24724-44416-13
文摘Dynamic urban expansion simulation at regional scale is one of the important research methodologies in Land Use/Cover Change （LUCC） and global environmental change influenced by urbanization. However, previous studies indicate that the single urban expansion simulation for future scenarios at local scale cannot meet the requirements for characterizing and interpreting the interactive mechanisms of regional urbanization and global environmental change. This study constructed a regional Dynamic Urban Expansion Model （Reg-DUEM） suitable for different scenarios by integrating the Artificial Neural Network （ANN） and Cellular Automaton （CA） model. Firstly we analyzed the temporal and spatial characteristics of urban expansion and acquired a prior knowledge rules using land use/cover change datasets of Beijing-Tianjin-Tangshan metropolitan area. The future urban expansion under different scenarios is then simulated based on a baseline model, economic models, policy models and the structural adjustment model. The results indicate that Reg-DUEM has good reliability for a non-linear expansion simulation at regional scale influenced by macro-policies. The simulating results show that future urban expansion patterns from different scenarios of the metropolitan area have the tremendous spatio-temporal differences. Future urban expansion will shift quickly from Beijing metropolis to the periphery of Tianjin and Tangshan city along coastal belt.
基金The Young Scientist Fund of National Natural Science Foundation of China, No.40901224 National Basic Research Program of China, No.2010CB950900+1 种基金 Open Fund of State Key Laboratory of Remote Sensing Science, No.2009KFJJ005 Open Fund of State Key Lab of Resources and Environmental Information System, No.A0725
文摘The impervious surface area （ISA） at the regional scale is one of the important environmental factors for examining the interaction and mechanism of Land Use/Cover Change （LUCC）-ecosystem processes-climate change under the interactions of urbanization and global environmental change. Timely and accurate extraction of ISA from remotely sensed data at the regional scale is challenging. This study explored the ISA extraction based on MODIS and DMSP-OLS data and the incorporation of China＇s land use/cover data. ISA datasets in Beijing-Tianjin-Tangshan Metropolitan Area （BTTMA） in 2000 and 2008 at a spatial resolution of 250 m were developed, their spatiotemporal changes were analyzed, and their impacts on water quality were then evaluated. The results indicated that ISA in BTTMA increased rapidly along urban fringe, transportation corridors and coastal belt both in intensity and extents from 2000 to 2008. Three cities （Tangshan, Langfang and Qinhuangdao） in Hebei Province had higher ISA growth rates than Beijing due to the pressure of population-resour- ces-environments in the city resulting in increasingly transferring industries to the nearby areas. The dense ISA distribution in BTTMA has serious impacts on water quality in the Haihe River watershed. Meanwhile, the proportion of ISA in sub-watersheds has significantly linear relationships with the densities of river COD and NH3-N.
