Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound th...Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound theoretical and practical significance regarding sustainable urban development.This study devised a raster-based land use spatial optimization(LUSO)framework,and utilized ant colony optimization(ACO)algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group(CZTCG)in China.The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth.Multi growth scenario including a single development center,multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050,and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG.The main results are listed as the following.1)It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model,and the optimal form of the spatial pattern can be defined.2)With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns,the total optimization target performance gradually increases,which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group.3)Subject to the regional social and economic development stage,absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration.Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration.The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.展开更多
The optimization of land-use spatio-structure is one of the most important areas of land use management;constructing a spatial optimization model that is based on the micro spatial unit in a bottom-up mode plays an im...The optimization of land-use spatio-structure is one of the most important areas of land use management;constructing a spatial optimization model that is based on the micro spatial unit in a bottom-up mode plays an important role in coupling the quan-tity structure and spatial structure effectively.The objective of this research is to develop a land use spatial optimization model based on particle swarm optimization to make spatial decision in land use management.The model is implemented using real data-sets to emulate the process of spatial structure optimization in order to get the best landscape pattern under the control of decision environments.Simulation results revealed that the particle swarm optimization model has the ability to utilize the quantity and spa-tial structure.Furthermore,the result demonstrated that it can be used to stimulate the landscape pattern in designing the appropriate optimization environment,which could land quantity target to the basic spatial units effectively and provide appropriate spa-tio-structure for regional land use space layout decision making.展开更多
基金Under the auspices of National Nature Science Foundation of China(No.41901311)。
文摘Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy.Hence,a better understanding of the urban growth boundary(UGB)has profound theoretical and practical significance regarding sustainable urban development.This study devised a raster-based land use spatial optimization(LUSO)framework,and utilized ant colony optimization(ACO)algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group(CZTCG)in China.The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth.Multi growth scenario including a single development center,multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050,and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG.The main results are listed as the following.1)It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model,and the optimal form of the spatial pattern can be defined.2)With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns,the total optimization target performance gradually increases,which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group.3)Subject to the regional social and economic development stage,absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration.Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration.The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.
基金Supported by the National Natural Science Foundation of China (No. 40701145, 40701143) the Open Foundation of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing in Wuhan University, China(2009)
文摘The optimization of land-use spatio-structure is one of the most important areas of land use management;constructing a spatial optimization model that is based on the micro spatial unit in a bottom-up mode plays an important role in coupling the quan-tity structure and spatial structure effectively.The objective of this research is to develop a land use spatial optimization model based on particle swarm optimization to make spatial decision in land use management.The model is implemented using real data-sets to emulate the process of spatial structure optimization in order to get the best landscape pattern under the control of decision environments.Simulation results revealed that the particle swarm optimization model has the ability to utilize the quantity and spa-tial structure.Furthermore,the result demonstrated that it can be used to stimulate the landscape pattern in designing the appropriate optimization environment,which could land quantity target to the basic spatial units effectively and provide appropriate spa-tio-structure for regional land use space layout decision making.
