Land use and cover change(LUCC) is one of the important causes of the Earth’s carbon cycle imbalances resulting from failure in optimizing land use. The solution to this problem has been the hotspot of research in la...Land use and cover change(LUCC) is one of the important causes of the Earth’s carbon cycle imbalances resulting from failure in optimizing land use. The solution to this problem has been the hotspot of research in land and environmental science. We took 'low carbon', 'energy saving' and 'high-efficiency' as the goals of land use optimization,and integrated Markov-CA(Cellular Automaton),the Grid-Fractal model and GIS,in order to study carbon emission objective function,to establish a simulation method for land use spatial allocation optimization,to evaluate the effect of the method on carbon emissions. Regulation policy on three types of land use spatial allocation was proposed,including 'low-carbon type', 'low-carbon-economic type' and 'economic type'. We applied the method to analyze the land use spatial allocation in Taixing City of the 'Yangtze River Delta' regions in China,and obtained the following results:(i) The three optimization types would improve carbon emissions by 3. 21%,1. 80% and 0. 36% respectively in 2020,compared with 2010;(ii) The actual planning for 2020 was close to the 'low-carbon-economic type';(iii) The optimization method and regulation policy,combining local optimization and global control,could meet the sustainable multi-objective requirements for low-carbon constraints of land use spatial allocation. The result of this research could also serve as a reference for exploration into patterns of regional low-carbon land use and measures for energy saving and emission reduction.展开更多
Based on the household survey of nine villages in Guangdong Province and Hunan Province,we research the relationship between landless farmers and land adjustment,land transfer in the context of rural land contract rig...Based on the household survey of nine villages in Guangdong Province and Hunan Province,we research the relationship between landless farmers and land adjustment,land transfer in the context of rural land contract rights on a long term basis.We demonstrate that the existence of landless farmers does not pose a serious problem for the current rural community.We also explain the reason why the land is no longer readjusted:the expected return of land adjustment is low and the organizational costs are high.展开更多
The mixed linear programming model is commonly recognized to be an effective means for searching optimal reservoir operation policy in water resources system. In this paper a multi-objective mixed integer linear progr...The mixed linear programming model is commonly recognized to be an effective means for searching optimal reservoir operation policy in water resources system. In this paper a multi-objective mixed integer linear programming model is set up to obtain the optimal operation policy of multi-reservoir water supply system during drought, which is able to consider the operation rule of reservoir-group system within longer-term successive drought periods, according to the basic connotation of indexes expressing the water-supply risk of reservoir during drought, that is, reliability, resilience and vulnerability of reservoir water supply, and mathematical programming principles. The model-solving procedures, particularly, the decomposition-adjustment algorithm, are proposed based on characteristics of the model structure. The principle of model-solving technique is to decompose the complex system into several smaller sub-systems on which some ease-solving mathematical models may be established. The objective of this optimization model aims at maximizing the reliability of water supply and minimizing the maximum water-shortage of single time-period within water- supply system during drought. The multi-objective mixed integer linear programming model and proposed solving procedures are applied to a case study of reservoir-group water-supply system in Huanghe-Huaihe River Basin, China. The desired water-shortage distribution within the system operation term and the maximum shortage of single time-period are achieved. The results of case study verifies that the lighter water-shortage distributed evenly among several time-periods can avoid the calamities resulted from severe water shortage concentrated on a few time-periods during drought.展开更多
基金Supported by National Natural Science Foundation of China(71233004)Nonprofit Industry Financial Program of Ministry of Land and Resources of China(201111011)+1 种基金Project of Jiangsu Province Science and Technology(BE2016302)Humanities and Social Sciences Project of Nanjing Agricultural University(SKZK2015008)
文摘Land use and cover change(LUCC) is one of the important causes of the Earth’s carbon cycle imbalances resulting from failure in optimizing land use. The solution to this problem has been the hotspot of research in land and environmental science. We took 'low carbon', 'energy saving' and 'high-efficiency' as the goals of land use optimization,and integrated Markov-CA(Cellular Automaton),the Grid-Fractal model and GIS,in order to study carbon emission objective function,to establish a simulation method for land use spatial allocation optimization,to evaluate the effect of the method on carbon emissions. Regulation policy on three types of land use spatial allocation was proposed,including 'low-carbon type', 'low-carbon-economic type' and 'economic type'. We applied the method to analyze the land use spatial allocation in Taixing City of the 'Yangtze River Delta' regions in China,and obtained the following results:(i) The three optimization types would improve carbon emissions by 3. 21%,1. 80% and 0. 36% respectively in 2020,compared with 2010;(ii) The actual planning for 2020 was close to the 'low-carbon-economic type';(iii) The optimization method and regulation policy,combining local optimization and global control,could meet the sustainable multi-objective requirements for low-carbon constraints of land use spatial allocation. The result of this research could also serve as a reference for exploration into patterns of regional low-carbon land use and measures for energy saving and emission reduction.
基金Supported by National Social Science Fund Project(11BJY094)211 Project of College of Economics and Management,South China Agricultural University(2011211TD02)
文摘Based on the household survey of nine villages in Guangdong Province and Hunan Province,we research the relationship between landless farmers and land adjustment,land transfer in the context of rural land contract rights on a long term basis.We demonstrate that the existence of landless farmers does not pose a serious problem for the current rural community.We also explain the reason why the land is no longer readjusted:the expected return of land adjustment is low and the organizational costs are high.
文摘The mixed linear programming model is commonly recognized to be an effective means for searching optimal reservoir operation policy in water resources system. In this paper a multi-objective mixed integer linear programming model is set up to obtain the optimal operation policy of multi-reservoir water supply system during drought, which is able to consider the operation rule of reservoir-group system within longer-term successive drought periods, according to the basic connotation of indexes expressing the water-supply risk of reservoir during drought, that is, reliability, resilience and vulnerability of reservoir water supply, and mathematical programming principles. The model-solving procedures, particularly, the decomposition-adjustment algorithm, are proposed based on characteristics of the model structure. The principle of model-solving technique is to decompose the complex system into several smaller sub-systems on which some ease-solving mathematical models may be established. The objective of this optimization model aims at maximizing the reliability of water supply and minimizing the maximum water-shortage of single time-period within water- supply system during drought. The multi-objective mixed integer linear programming model and proposed solving procedures are applied to a case study of reservoir-group water-supply system in Huanghe-Huaihe River Basin, China. The desired water-shortage distribution within the system operation term and the maximum shortage of single time-period are achieved. The results of case study verifies that the lighter water-shortage distributed evenly among several time-periods can avoid the calamities resulted from severe water shortage concentrated on a few time-periods during drought.
