This paper compartmentalizes regional land use of rural settlements in China by employing a hierarchical clustering method.The statistic data are sourced from the National Bureau of Statistics of China(NBSC) and the d...This paper compartmentalizes regional land use of rural settlements in China by employing a hierarchical clustering method.The statistic data are sourced from the National Bureau of Statistics of China(NBSC) and the data of land use change from the Ministry of Land and Resources of China(MLRC).The population of rural settlement decreases from the southeast to the northwest of China and the density of rural settlement decreases from the east to the west of China.Land-use scale of rural settlement,the proportion of one-storey houses and the average household area decrease from the north to the south of China.The ratio of area of cultivated land to rural settlement is high in the northeast and southwest of China but low in the southeast of China.The land use regionalization of rural settlement can be divided into four regions,namely:the northern region of China,Qinghai-Tibet,Yunnan-Guizhou,and the middle and eastern region of China.The northern region of China and the middle and eastern region of China can be further divided into nine sub-regions:Xinjiang,Northeast China,Ningxia and Inner Mongolia,North China,the south of the Changjiang(Yantze) River and Sichuan Basin,Jiangsu-Shanghai,South China,the Loess Plateau,and Guangxi.In consideration of the significant regional differences,it is proposed that different policies should be implemented regarding the utilization and management of rural settlements.展开更多
As an important part of land use/cover change(LUCC), historical LUCC in long time series attracts much more attention from scholars. Currently, based on the view of combining the overall control of cropland area and ...As an important part of land use/cover change(LUCC), historical LUCC in long time series attracts much more attention from scholars. Currently, based on the view of combining the overall control of cropland area and ′top-down′ decision-making behaviors, here are two global historical land-use datasets, generally referred as the Sustainability and the Global Environment datasets(SAGE datasets) and History Database of the Global Environment datasets(HYDE datasets). However, at the regional level, these global datasets have coarse resolutions and inevitable errors. Considering various factors that influenced cropland distribution, including cropland connectivity and the limitation of natural and human factors, this study developed a reconstruction model of historical cropland based on constrained Cellular Automaton(CA) of ′bottom-up′. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. Applied the reconstruction model to Shandong Province, we reconstructed its spatial distribution of cropland during 8 periods. The reconstructed results show that: 1) it is properly suitable for constrained CA to simulate and reconstruct the spatial distribution of cropland in traditional cultivated region of China; 2) compared with ′SAGE datasets′ and ′HYDE datasets′, this study have formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format.展开更多
Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the...Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the efforts based satellites have provided a good baseline for present land cover, what the next advancement in the research about LUCC change required is the development of reconstruction of historical LUCC change especially spatially-explicit historical dataset. Being different from other similar studies, this study is based on the analysis of historical land use patterns in the traditional cultivated region of China. Taking no account of the less important factors, altitude, slope and population patterns are selected as the major drivers of reclamation in ancient China, and used to design the HCGM （Historical Cropland Gridding Model, at a 60 km×60 km resolution）, which is an empirical model for allocating the historical cropland inventory data spatially to grid cells in each political unit. Then we use this model to reconstruct cropland distribution of the study area in 1820, and verify the result by prefectural cropland data of 1820, which is from the historical documents. The statistical analyzing result shows that the model can simulate the patterns of the cropland distribution in the historical period in the traditional cultivated region efficiently.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41001108)
文摘This paper compartmentalizes regional land use of rural settlements in China by employing a hierarchical clustering method.The statistic data are sourced from the National Bureau of Statistics of China(NBSC) and the data of land use change from the Ministry of Land and Resources of China(MLRC).The population of rural settlement decreases from the southeast to the northwest of China and the density of rural settlement decreases from the east to the west of China.Land-use scale of rural settlement,the proportion of one-storey houses and the average household area decrease from the north to the south of China.The ratio of area of cultivated land to rural settlement is high in the northeast and southwest of China but low in the southeast of China.The land use regionalization of rural settlement can be divided into four regions,namely:the northern region of China,Qinghai-Tibet,Yunnan-Guizhou,and the middle and eastern region of China.The northern region of China and the middle and eastern region of China can be further divided into nine sub-regions:Xinjiang,Northeast China,Ningxia and Inner Mongolia,North China,the south of the Changjiang(Yantze) River and Sichuan Basin,Jiangsu-Shanghai,South China,the Loess Plateau,and Guangxi.In consideration of the significant regional differences,it is proposed that different policies should be implemented regarding the utilization and management of rural settlements.
基金Under the auspices of National Basic Research Program of China(No.2011CB952001)National Natural Science Foundation of China(No.41340016,412013860)
文摘As an important part of land use/cover change(LUCC), historical LUCC in long time series attracts much more attention from scholars. Currently, based on the view of combining the overall control of cropland area and ′top-down′ decision-making behaviors, here are two global historical land-use datasets, generally referred as the Sustainability and the Global Environment datasets(SAGE datasets) and History Database of the Global Environment datasets(HYDE datasets). However, at the regional level, these global datasets have coarse resolutions and inevitable errors. Considering various factors that influenced cropland distribution, including cropland connectivity and the limitation of natural and human factors, this study developed a reconstruction model of historical cropland based on constrained Cellular Automaton(CA) of ′bottom-up′. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. Applied the reconstruction model to Shandong Province, we reconstructed its spatial distribution of cropland during 8 periods. The reconstructed results show that: 1) it is properly suitable for constrained CA to simulate and reconstruct the spatial distribution of cropland in traditional cultivated region of China; 2) compared with ′SAGE datasets′ and ′HYDE datasets′, this study have formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format.
基金Natiional Natural Science Foundation of China,No.40471007Innovation Knowledge Project of CAS,No.KZCX2-YW-315
文摘Recent studies have demonstrated the importance of LUCC change with climate and ecosystem simulation, but the result could only be determined precisely if a high-resolution underlying land cover map is used. While the efforts based satellites have provided a good baseline for present land cover, what the next advancement in the research about LUCC change required is the development of reconstruction of historical LUCC change especially spatially-explicit historical dataset. Being different from other similar studies, this study is based on the analysis of historical land use patterns in the traditional cultivated region of China. Taking no account of the less important factors, altitude, slope and population patterns are selected as the major drivers of reclamation in ancient China, and used to design the HCGM （Historical Cropland Gridding Model, at a 60 km×60 km resolution）, which is an empirical model for allocating the historical cropland inventory data spatially to grid cells in each political unit. Then we use this model to reconstruct cropland distribution of the study area in 1820, and verify the result by prefectural cropland data of 1820, which is from the historical documents. The statistical analyzing result shows that the model can simulate the patterns of the cropland distribution in the historical period in the traditional cultivated region efficiently.
