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
One of the challenges in global change research is the significant uncertainty in global historical land use and land cover(LUCC)datasets,which are widely used as foundational data.In addition to the regional cropland...One of the challenges in global change research is the significant uncertainty in global historical land use and land cover(LUCC)datasets,which are widely used as foundational data.In addition to the regional cropland area reconstructions,improving the grid allocation method is another feasible way to raise the reliability of historical LUCC data.In this study,an integrated reconstruction of the national cropland areas over the past 200 years was developed for 36 European countries.After that,the allocation algorithm was built using physiogeographic variables and historical city sites for accounting for land suitability and cultivation preferences,respectively.Finally,cropland data in Europe with a spatial resolution of 5′×5′at five time sections from AD 1800 to 2000 were generated using the optimal allocation algorithm in accordance with the stages of the regional history.The results were as follows:(1)The dominant factors governing the distribution of croplands in Europe vary at different agricultural stages,but the results can be merged together.Land suitability was more optimal for allocation during the modern agricultural stage(AD 1950 and 2000);the priority index combined with land suitability and cultivation preference was more reasonable for allocation during the traditional agricultural stage(AD 1800).The average of the allocations by priority index and the land suitability could be adopted as the allocation results during the transitional stage(AD 1850 and 1900)because the grids for absolute differences within±10 and±20 percentage points between the results obtained from the above two allocations were above 80% and 95%,respectively,which means the two allocation results could be merged.(2)Over the past 200 years,the total cropland area in Europe first increased to a peak in AD 1900 and then decreased.Spatially,the centre of the higher cropland fraction shifted from the western part of Europe in AD 1800 to the eastern part of the continent after AD 1950.(3)Both the cropland area and the spatial distribution in this study are more reasonable than the global dataset HYDE3.2.展开更多
Reconstructing historical land use and land cover change using explicit temporal,quantitative,and spatial information is not only the prerequisite for simulating long-term climate change and ecological effects but is ...Reconstructing historical land use and land cover change using explicit temporal,quantitative,and spatial information is not only the prerequisite for simulating long-term climate change and ecological effects but is also a scientific basis for comprehensively understanding the process and mechanism of anthropogenic land use alterations.Considering changes in historical borders and administrative divisions,a provincial cropland area dataset for China over the past millennium was created on the basis of existing estimations since the Song Dynasty.Land suitability for cultivation was then assessed by incorporating altitude,slope,soil texture,and the maximum potential productivity of climate.Subsequently,a gridding allocation model for cropland was constructed,and the provincial cropland area for 24 years over the past millennium was allocated into grids with a resolution of 10 km.The cropland area in China increased from 3.71×10^(7)ha in AD 1000 to 12.92×10^(7)ha in AD 1999,with a peak of 13.50×10^(7)ha in AD 1980.The total cropland area in China showed fluctuating increasing trends that can be divided into three phases:fluctuation without notable net change for AD 1000–1290,slow increase for AD 1290–1661,and rapid increase for AD 1661–1999.Spatially,cropland intensified in the middle-lower reaches of the Yellow and Yangtze Rivers and expanded to mountainous and frontier areas over the last millennium.Specifically,over the entire period,the fractional cropland areas(FCAs)in the middle-lower reaches of the Yellow and Yangtze Rivers increased by 1.4 and 0.8 times,respectively.Since the mid-Qing Dynasty,large-scale land reclamation expanded to areas of low reclamation in southwest and northeast China.The FCAs for southwest and northeast China increased from 2.13%and 0.55%in AD 1661 to 18.00%and 26.61%in AD 1999,respectively.For AD 1661–1999,the proportion of cropland increased by 55%in the hills and low mountains and 27%in the middle and high mountains.The comparison with remote sensing cropland data shows that the grid cells with absolute differences of 0–10%accounted for 70.35%of all grid cells,while grids with differences exceeding 60%accounted for only 0.83%.This finding indicates that the reconstruction method is feasible,and the reconstruction results objectively reveal the historical spatiotemporal changes in cropland.展开更多
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.
基金supported by the National Key Research and Development Program of China(Grant No.2017YFA0603304)。
文摘One of the challenges in global change research is the significant uncertainty in global historical land use and land cover(LUCC)datasets,which are widely used as foundational data.In addition to the regional cropland area reconstructions,improving the grid allocation method is another feasible way to raise the reliability of historical LUCC data.In this study,an integrated reconstruction of the national cropland areas over the past 200 years was developed for 36 European countries.After that,the allocation algorithm was built using physiogeographic variables and historical city sites for accounting for land suitability and cultivation preferences,respectively.Finally,cropland data in Europe with a spatial resolution of 5′×5′at five time sections from AD 1800 to 2000 were generated using the optimal allocation algorithm in accordance with the stages of the regional history.The results were as follows:(1)The dominant factors governing the distribution of croplands in Europe vary at different agricultural stages,but the results can be merged together.Land suitability was more optimal for allocation during the modern agricultural stage(AD 1950 and 2000);the priority index combined with land suitability and cultivation preference was more reasonable for allocation during the traditional agricultural stage(AD 1800).The average of the allocations by priority index and the land suitability could be adopted as the allocation results during the transitional stage(AD 1850 and 1900)because the grids for absolute differences within±10 and±20 percentage points between the results obtained from the above two allocations were above 80% and 95%,respectively,which means the two allocation results could be merged.(2)Over the past 200 years,the total cropland area in Europe first increased to a peak in AD 1900 and then decreased.Spatially,the centre of the higher cropland fraction shifted from the western part of Europe in AD 1800 to the eastern part of the continent after AD 1950.(3)Both the cropland area and the spatial distribution in this study are more reasonable than the global dataset HYDE3.2.
基金supported by the National Key Research and Development Program of China(Grant No.2017YFA0603304)the Chinese Academy of Sciences Strategic Priority Research Program(Grant No.XDA19040101)。
文摘Reconstructing historical land use and land cover change using explicit temporal,quantitative,and spatial information is not only the prerequisite for simulating long-term climate change and ecological effects but is also a scientific basis for comprehensively understanding the process and mechanism of anthropogenic land use alterations.Considering changes in historical borders and administrative divisions,a provincial cropland area dataset for China over the past millennium was created on the basis of existing estimations since the Song Dynasty.Land suitability for cultivation was then assessed by incorporating altitude,slope,soil texture,and the maximum potential productivity of climate.Subsequently,a gridding allocation model for cropland was constructed,and the provincial cropland area for 24 years over the past millennium was allocated into grids with a resolution of 10 km.The cropland area in China increased from 3.71×10^(7)ha in AD 1000 to 12.92×10^(7)ha in AD 1999,with a peak of 13.50×10^(7)ha in AD 1980.The total cropland area in China showed fluctuating increasing trends that can be divided into three phases:fluctuation without notable net change for AD 1000–1290,slow increase for AD 1290–1661,and rapid increase for AD 1661–1999.Spatially,cropland intensified in the middle-lower reaches of the Yellow and Yangtze Rivers and expanded to mountainous and frontier areas over the last millennium.Specifically,over the entire period,the fractional cropland areas(FCAs)in the middle-lower reaches of the Yellow and Yangtze Rivers increased by 1.4 and 0.8 times,respectively.Since the mid-Qing Dynasty,large-scale land reclamation expanded to areas of low reclamation in southwest and northeast China.The FCAs for southwest and northeast China increased from 2.13%and 0.55%in AD 1661 to 18.00%and 26.61%in AD 1999,respectively.For AD 1661–1999,the proportion of cropland increased by 55%in the hills and low mountains and 27%in the middle and high mountains.The comparison with remote sensing cropland data shows that the grid cells with absolute differences of 0–10%accounted for 70.35%of all grid cells,while grids with differences exceeding 60%accounted for only 0.83%.This finding indicates that the reconstruction method is feasible,and the reconstruction results objectively reveal the historical spatiotemporal changes in cropland.
