The relief degree of land surface (RDLS) is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the ent...The relief degree of land surface (RDLS) is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the entire country. Based on the concept and macro-scale digital elevation model datum and ARC/INFO software, the RDLS at a 10 km×10 km grid size of China is extracted. This paper depicts systemically the spatial distributions of RDLS through analyzing the ratio structure and altitudinal characters of RDLS in China. The conclusions are drawn as follows: the RDLS in more than 63% of the area is less than one (1) (relative altitude is less than 500 m), reflecting the fact that most of RDLS in China is low. In general, the RDLS in the west is larger than that in the east and so is the south than that of the north in China. The RDLS decreases with the increase of longitude and latitude and the change of RDLS at the latitudes of 28°N, 35°N, 42°N, as well as at the longitudes of 85°E, 102°E, 115°E could reflect the three major ladders of China. In the vertical direction, the RDLS increases with the increase of altitude. Analysis of the correlation between RDLS and population distribution in China and its regional difference shows that the R2 value between RDLS and population density is 0.91 and RDLS is an important factor influencing the spatial distribution of population. More than 85% of the people in China live in areas where the RDLS is less than one (1), while the population in areas with RDLS greater than 3 accounts only for 0.57% of the total. The regional difference of correlation between RDLS and population within China is significant and such correlation is significant in Central China and South China and weak in Inner Mongolia and Tibet.展开更多
Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods use...Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods used to calculate population density often adopt the administrative region as a scale for statistical analysis. These methods did not consider the effects of the relief degree of land surface(RDLS) on the population distribution. Therefore they cannot accurately reflect the degree of population aggregation, especially in mountainous areas. To explore this issue further, we took the mountainous areas of China as the research area. China has A total area of 666 km2 can be classified as mountainous area,accounting for 69.4% of the country's total landmass. The data used in this research included the digital elevation model(DEM) of China at a scale of 1:1,000,000, National population density raster data, the DEM and the national population density raster data. First, we determined the relief degree of land surface(RDLS). Next, we conducted a correlation analysis between the population distribution and the RDLS using the Statistical Package for Social Science(SPSS). Based on the correlation analysis results and population distribution, this new method was used to revise the provincial population density of themountainous areas. The revised results were used to determine the population pressure of different mountainous areas. Overall, the following results were obtained:(1) The RDLS was low in most mountainous areas(with a value between 0 and 3.5) and exhibited a spatial pattern that followed the physiognomy of China;(2) The relationship between the RDLS and population density were logarithmic, with an R2 value up to 0.798(p<0.05), and the correlation decreased from east to west;(3) The difference between the revised population density(RPD) and the traditional population density(PD) was larger in the southeastern region of China than in the northwestern region;(4) In addition, compared with traditional results, the revised result indicated that the population pressure was larger. Based on these results, the following conclusions were made:(1) the revised method for estimating population density that incorporates the RDLS is reasonable and practical,(2) the potential population pressure in the southeastern mountainous areas is substantial,(3) the characteristics of the terrain in the high mountainous areas are important for the scattered distribution of the population, and(4) the population distribution of mountainous areas in China should be guided by local conditions, such as social, economic, and topographic conditions.展开更多
Urban-rural integration (URI) is a global challenge that is highly related to inequalities, poverty, economic growth, and other Sustainable Development Goals (SDGs). Existing research has evaluated the extent of URI a...Urban-rural integration (URI) is a global challenge that is highly related to inequalities, poverty, economic growth, and other Sustainable Development Goals (SDGs). Existing research has evaluated the extent of URI and explored its influencing factors, but urban-rural linkages are seldom incorporated in evaluation systems, and geographical factors are rarely recognized as the influencing factors. We construct a URI framework including regional economy, rural development, urban-rural linkage, and urban-rural gap. Based on a dataset consisting of 1,669 counties in China in 2020, we reveal the spatial pattern of URI and find a high correlation between the spatial pattern of URI and the relief degree of land surface (RDLS). Using structural equation modeling, we discover that topography has direct ( − 0.18, p < 0.001) and indirect ( − 0.17, p < 0.001) effects on URI. The indirect negative effects are mediated through the infrastructure, and the combination of localized advantages and modern technical conditions could mitigate the negative impact of topography. Finally, we identify 742 counties as lagging regions in URI, which can be clustered into eight types. Our findings could facilitate policy designing for those countries striving for integrated and sustainable development of urban and rural areas.展开更多
为科学确定气象站点地形起伏特征,基于先进星载热发射和反射辐射仪全球数字高程模型(Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model,ASTER GDEM)30 m数据,利用均值变点分析法确定四...为科学确定气象站点地形起伏特征,基于先进星载热发射和反射辐射仪全球数字高程模型(Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model,ASTER GDEM)30 m数据,利用均值变点分析法确定四川省地形起伏度模型的最佳分析窗口。提取地面气象观测站所处的地形起伏特征,探究气象站点布设的区域代表性空间格局。结果表明:(1)四川省地形起伏度的最佳窗口为39×39个像元矩形邻域,对应面积1.369 km^(2)。建立的地形起伏度模型与山脉走向一致,能够捕捉到地表各种尺度的地形起伏状况,符合四川省地貌特征。(2)国家站和区域站所处地势以台地、丘陵和小起伏山地为主,地形起伏较小的国家站占比明显高于区域站,即国家站更具有区域代表性。(3)四川省气象观测站点布设的适宜地区主要集中在盆地、川西高原的北部和西部及攀西地区的东部和南部,占全省面积的69.74%。均值变点分析法确定的分析窗口面积可以兼顾各种地貌类型,提取的地形起伏度能较好地反映气象站点所处地形特征,可为气象站点布局和站网优化提供重要参考依据。展开更多
基金Knowledge Innovation Project of the CAS,No.KZCX2-YW-323
文摘The relief degree of land surface (RDLS) is an important factor for describing the landform at macro-scales. This study defines a concept for RDLS and applies the concept for population distribution study of the entire country. Based on the concept and macro-scale digital elevation model datum and ARC/INFO software, the RDLS at a 10 km×10 km grid size of China is extracted. This paper depicts systemically the spatial distributions of RDLS through analyzing the ratio structure and altitudinal characters of RDLS in China. The conclusions are drawn as follows: the RDLS in more than 63% of the area is less than one (1) (relative altitude is less than 500 m), reflecting the fact that most of RDLS in China is low. In general, the RDLS in the west is larger than that in the east and so is the south than that of the north in China. The RDLS decreases with the increase of longitude and latitude and the change of RDLS at the latitudes of 28°N, 35°N, 42°N, as well as at the longitudes of 85°E, 102°E, 115°E could reflect the three major ladders of China. In the vertical direction, the RDLS increases with the increase of altitude. Analysis of the correlation between RDLS and population distribution in China and its regional difference shows that the R2 value between RDLS and population density is 0.91 and RDLS is an important factor influencing the spatial distribution of population. More than 85% of the people in China live in areas where the RDLS is less than one (1), while the population in areas with RDLS greater than 3 accounts only for 0.57% of the total. The regional difference of correlation between RDLS and population within China is significant and such correlation is significant in Central China and South China and weak in Inner Mongolia and Tibet.
基金supported by a grant from the Major State Basic Research Development Program of China (973 Program) (Grant No. 2015CB452706)National Natural Science Foundation of China (Grant No. 41471469)provided by the national scientific datasharing project Earth System Science Data Sharing Network
文摘Evaluation on the population pressure in the mountainous areas is a necessary condition for the protection and good governance. The evaluation depends on accurate population density assessment. Traditional methods used to calculate population density often adopt the administrative region as a scale for statistical analysis. These methods did not consider the effects of the relief degree of land surface(RDLS) on the population distribution. Therefore they cannot accurately reflect the degree of population aggregation, especially in mountainous areas. To explore this issue further, we took the mountainous areas of China as the research area. China has A total area of 666 km2 can be classified as mountainous area,accounting for 69.4% of the country's total landmass. The data used in this research included the digital elevation model(DEM) of China at a scale of 1:1,000,000, National population density raster data, the DEM and the national population density raster data. First, we determined the relief degree of land surface(RDLS). Next, we conducted a correlation analysis between the population distribution and the RDLS using the Statistical Package for Social Science(SPSS). Based on the correlation analysis results and population distribution, this new method was used to revise the provincial population density of themountainous areas. The revised results were used to determine the population pressure of different mountainous areas. Overall, the following results were obtained:(1) The RDLS was low in most mountainous areas(with a value between 0 and 3.5) and exhibited a spatial pattern that followed the physiognomy of China;(2) The relationship between the RDLS and population density were logarithmic, with an R2 value up to 0.798(p<0.05), and the correlation decreased from east to west;(3) The difference between the revised population density(RPD) and the traditional population density(PD) was larger in the southeastern region of China than in the northwestern region;(4) In addition, compared with traditional results, the revised result indicated that the population pressure was larger. Based on these results, the following conclusions were made:(1) the revised method for estimating population density that incorporates the RDLS is reasonable and practical,(2) the potential population pressure in the southeastern mountainous areas is substantial,(3) the characteristics of the terrain in the high mountainous areas are important for the scattered distribution of the population, and(4) the population distribution of mountainous areas in China should be guided by local conditions, such as social, economic, and topographic conditions.
基金the National Natural Science Foundation of China(Grants No.T2261129477 and 41971220)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23070300).
文摘Urban-rural integration (URI) is a global challenge that is highly related to inequalities, poverty, economic growth, and other Sustainable Development Goals (SDGs). Existing research has evaluated the extent of URI and explored its influencing factors, but urban-rural linkages are seldom incorporated in evaluation systems, and geographical factors are rarely recognized as the influencing factors. We construct a URI framework including regional economy, rural development, urban-rural linkage, and urban-rural gap. Based on a dataset consisting of 1,669 counties in China in 2020, we reveal the spatial pattern of URI and find a high correlation between the spatial pattern of URI and the relief degree of land surface (RDLS). Using structural equation modeling, we discover that topography has direct ( − 0.18, p < 0.001) and indirect ( − 0.17, p < 0.001) effects on URI. The indirect negative effects are mediated through the infrastructure, and the combination of localized advantages and modern technical conditions could mitigate the negative impact of topography. Finally, we identify 742 counties as lagging regions in URI, which can be clustered into eight types. Our findings could facilitate policy designing for those countries striving for integrated and sustainable development of urban and rural areas.
文摘为科学确定气象站点地形起伏特征,基于先进星载热发射和反射辐射仪全球数字高程模型(Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model,ASTER GDEM)30 m数据,利用均值变点分析法确定四川省地形起伏度模型的最佳分析窗口。提取地面气象观测站所处的地形起伏特征,探究气象站点布设的区域代表性空间格局。结果表明:(1)四川省地形起伏度的最佳窗口为39×39个像元矩形邻域,对应面积1.369 km^(2)。建立的地形起伏度模型与山脉走向一致,能够捕捉到地表各种尺度的地形起伏状况,符合四川省地貌特征。(2)国家站和区域站所处地势以台地、丘陵和小起伏山地为主,地形起伏较小的国家站占比明显高于区域站,即国家站更具有区域代表性。(3)四川省气象观测站点布设的适宜地区主要集中在盆地、川西高原的北部和西部及攀西地区的东部和南部,占全省面积的69.74%。均值变点分析法确定的分析窗口面积可以兼顾各种地貌类型,提取的地形起伏度能较好地反映气象站点所处地形特征,可为气象站点布局和站网优化提供重要参考依据。