Cold storage is the vital infrastructure of cold chain logistics. In this study, we analyzed the spatial pattern evolution characteristics, spatial autocorrelation and influencing factors of cold storage in China by u...Cold storage is the vital infrastructure of cold chain logistics. In this study, we analyzed the spatial pattern evolution characteristics, spatial autocorrelation and influencing factors of cold storage in China by using kernel density estimation(KDE), spatial autocorrelation analysis(SAA), and spatial error model(SEM). Results showed that: 1) the spatial distribution of cold storage in China is unbalanced, and has evolved from ‘one core’ to ‘one core and many spots’, that is, ‘one core’ refers to the Bohai Rim region mainly including Beijing, Tianjin, Hebei, Shandong and Liaoning regions, and ‘many spots’ mainly include the high-density areas such as Shanghai, Fuzhou, Guangzhou, Zhengzhou, Hefei, Wuhan, ürümqi. 2) The distribution of cold storage has significant global spatial autocorrelation and local spatial autocorrelation, and the ‘High-High’ cluster area is the most stable, mainly concentrated in the Bohai Rim;the ‘Low-Low’ cluster area is grouped in the southern China. 3) Economic development level, population density, traffic accessibility, temperature and land price, all affect the location choice of cold storage in varying degrees, while the impact of market demand on it is not explicit.展开更多
We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze R...We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.展开更多
This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employ...This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.展开更多
Lakes are important ecological water sources in the Bashang Plateau. Its expansion or shrinkage directly affects the ecological security of the plateau and its surrounding areas. In this study, Landsat images from 198...Lakes are important ecological water sources in the Bashang Plateau. Its expansion or shrinkage directly affects the ecological security of the plateau and its surrounding areas. In this study, Landsat images from 1984 to 2015 were selected to monitor the area of lakes in the Bashang Plateau and to analyze the spatiotemporal evolution and driving forces of lakes in the Bashang Plateau. The results showed that there were 47 lakes in the Bashang Plateau in 2015, with a total area of 37.63 km2, mainly distributed in the central and western regions of the region. From 1984 to 2015, the lakes in Bashang Plateau showed a shrinking trend. At the same time, there are obvious stage differences in lake changes. During 1984-1996, the number of lakes increased by 99 and the total area increased by 124.43 km2. From 1996 to 2015, the number of lakes decreased by 142, and the total area decreased by 183.96 km2. Before 1996, climate change was the dominant factor. However, the shrinkage of lakes after 1996 is the result of climate change and human activities. Among them, the large-scale planting of water consuming crops such as vegetables is the main human activity mode leading to lake shrinkage. This study will help to understand the expansion and contraction factors of the Bashang Plateau lakes in Hebei province and provide a reference for the future protection and management of the lakes.展开更多
Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of...Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of becoming a leading nation for tourism.This study accordingly constructs a new evaluation system that covers tourism market demand,industry supply,and structural transformation,and analyzes data from 31 Chinese provincial regions(2010–2019).The entropy method and spatial autocorrelation analysis were applied to examine the driving forces for sustainable regional tourism development.The results revealed that:First,at the national level,the driving forces for sustainable regional tourism development exhibited a clear upward trend from 2010 to 2019,with an acceleration in growth after 2015.However,there was significant regional heterogeneity:The eastern region displayed the highest levels of driving forces,followed by the central and western regions.Second,high-value clusters of these driving forces expanded from the eastern to the western regions,while the central provinces remained relatively balanced.Specifically,provincial regions such as Guangdong,Beijing,and Zhejiang were able to successively enter the high-value clusters,whereas the Xinjiang Uygur autonomous region,Gansu,and Qinghai consistently remained in the low-value clusters.Third,the driving forces exhibited a significant spatial agglomeration effect.The degree of clustering followed an inverted“U”trend over the study period,while the spatial patterns of the provincial regions remained relatively stable.展开更多
China’s policy on cropland protection is a fundamental agricultural policy,which supports the state’s sustainable development goals of eradicating hunger,achieving food security,improving nutrition and promoting sus...China’s policy on cropland protection is a fundamental agricultural policy,which supports the state’s sustainable development goals of eradicating hunger,achieving food security,improving nutrition and promoting sustainable agriculture.We combined the SD and PLUS models to construct an integrated framework for simulating future areas of cropland and their spatial distribution.We simulated the spatial and temporal changes in cropland in Guangxi Autonomous Region under different scenarios in 2030,2040 and 2050.The results showed that the simulation error for historical cropland areas using the SD model was≤3%.The PLUS model results for the spatial distribution of cropland in Guangxi in 2020 was 0.92 for overall accuracy(OA),0.77 for Kappa,and 0.33 for the figure of merit(FOM).Thus,the integrated model was suitable for simulating cropland in Guangxi under different future scenarios.Analyses of the landscape index,standard deviation ellipse and hot spots were performed to examine the spatial and temporal distribution characteristics of Guangxi’s cropland under different future scenarios in more detail.They indicated that the area of cropland in Guangxi under different future scenarios gradually decreased,with the SSP245 scenario showing the greatest decrease in the area of cropland.Cropland in Guangxi showed a westward shift under different future scenarios,which was most rapid under the SSP245 scenario.cropland remained fragmented from 2000 to 2020,with fragmentation intensifying under different future scenarios,while cropland shifted to western rocky,desertified and poverty-affected areas.In sum,the results show that the SD-PLUS integrated model can predict the change trend of cropland in Guangxi under different future scenarios,which facilitates optimisation of the spatial allocation and planning of cropland and provides key data for implementing future cropland protection policies in Guangxi.展开更多
基金Under the auspices of the National Social Science Fund of China(No.15BGL185,19XJL004)General Project of Humanities and Social Sciences Research and Planning Fund of Ministry of Education(No.19YJA790097)+1 种基金Social Science Fund of Fujian Province(No.FJ2017C080)A Key Discipline of Henan University of Animal Husbandry and Economy‘Business Enterprise Management’(No.MXK2016201)。
文摘Cold storage is the vital infrastructure of cold chain logistics. In this study, we analyzed the spatial pattern evolution characteristics, spatial autocorrelation and influencing factors of cold storage in China by using kernel density estimation(KDE), spatial autocorrelation analysis(SAA), and spatial error model(SEM). Results showed that: 1) the spatial distribution of cold storage in China is unbalanced, and has evolved from ‘one core’ to ‘one core and many spots’, that is, ‘one core’ refers to the Bohai Rim region mainly including Beijing, Tianjin, Hebei, Shandong and Liaoning regions, and ‘many spots’ mainly include the high-density areas such as Shanghai, Fuzhou, Guangzhou, Zhengzhou, Hefei, Wuhan, ürümqi. 2) The distribution of cold storage has significant global spatial autocorrelation and local spatial autocorrelation, and the ‘High-High’ cluster area is the most stable, mainly concentrated in the Bohai Rim;the ‘Low-Low’ cluster area is grouped in the southern China. 3) Economic development level, population density, traffic accessibility, temperature and land price, all affect the location choice of cold storage in varying degrees, while the impact of market demand on it is not explicit.
基金Under the auspices of the post-funded project of National Social Science Foundation of China(No.16FJL009)
文摘We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.
基金Humanities and Social Science Project of the Ministry of Education(NO.17YJCZH041)。
文摘This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.
文摘Lakes are important ecological water sources in the Bashang Plateau. Its expansion or shrinkage directly affects the ecological security of the plateau and its surrounding areas. In this study, Landsat images from 1984 to 2015 were selected to monitor the area of lakes in the Bashang Plateau and to analyze the spatiotemporal evolution and driving forces of lakes in the Bashang Plateau. The results showed that there were 47 lakes in the Bashang Plateau in 2015, with a total area of 37.63 km2, mainly distributed in the central and western regions of the region. From 1984 to 2015, the lakes in Bashang Plateau showed a shrinking trend. At the same time, there are obvious stage differences in lake changes. During 1984-1996, the number of lakes increased by 99 and the total area increased by 124.43 km2. From 1996 to 2015, the number of lakes decreased by 142, and the total area decreased by 183.96 km2. Before 1996, climate change was the dominant factor. However, the shrinkage of lakes after 1996 is the result of climate change and human activities. Among them, the large-scale planting of water consuming crops such as vegetables is the main human activity mode leading to lake shrinkage. This study will help to understand the expansion and contraction factors of the Bashang Plateau lakes in Hebei province and provide a reference for the future protection and management of the lakes.
基金funded by the Ministry of Education’s Humanities and Social Sciences Research Planning Project(23YJA790070).
文摘Sustainable development,underpinned by robust systemic driving forces,is central to the growth of high-quality tourism.Therefore,identifying these forces at the regional level is crucial for advancing China’s goal of becoming a leading nation for tourism.This study accordingly constructs a new evaluation system that covers tourism market demand,industry supply,and structural transformation,and analyzes data from 31 Chinese provincial regions(2010–2019).The entropy method and spatial autocorrelation analysis were applied to examine the driving forces for sustainable regional tourism development.The results revealed that:First,at the national level,the driving forces for sustainable regional tourism development exhibited a clear upward trend from 2010 to 2019,with an acceleration in growth after 2015.However,there was significant regional heterogeneity:The eastern region displayed the highest levels of driving forces,followed by the central and western regions.Second,high-value clusters of these driving forces expanded from the eastern to the western regions,while the central provinces remained relatively balanced.Specifically,provincial regions such as Guangdong,Beijing,and Zhejiang were able to successively enter the high-value clusters,whereas the Xinjiang Uygur autonomous region,Gansu,and Qinghai consistently remained in the low-value clusters.Third,the driving forces exhibited a significant spatial agglomeration effect.The degree of clustering followed an inverted“U”trend over the study period,while the spatial patterns of the provincial regions remained relatively stable.
文摘China’s policy on cropland protection is a fundamental agricultural policy,which supports the state’s sustainable development goals of eradicating hunger,achieving food security,improving nutrition and promoting sustainable agriculture.We combined the SD and PLUS models to construct an integrated framework for simulating future areas of cropland and their spatial distribution.We simulated the spatial and temporal changes in cropland in Guangxi Autonomous Region under different scenarios in 2030,2040 and 2050.The results showed that the simulation error for historical cropland areas using the SD model was≤3%.The PLUS model results for the spatial distribution of cropland in Guangxi in 2020 was 0.92 for overall accuracy(OA),0.77 for Kappa,and 0.33 for the figure of merit(FOM).Thus,the integrated model was suitable for simulating cropland in Guangxi under different future scenarios.Analyses of the landscape index,standard deviation ellipse and hot spots were performed to examine the spatial and temporal distribution characteristics of Guangxi’s cropland under different future scenarios in more detail.They indicated that the area of cropland in Guangxi under different future scenarios gradually decreased,with the SSP245 scenario showing the greatest decrease in the area of cropland.Cropland in Guangxi showed a westward shift under different future scenarios,which was most rapid under the SSP245 scenario.cropland remained fragmented from 2000 to 2020,with fragmentation intensifying under different future scenarios,while cropland shifted to western rocky,desertified and poverty-affected areas.In sum,the results show that the SD-PLUS integrated model can predict the change trend of cropland in Guangxi under different future scenarios,which facilitates optimisation of the spatial allocation and planning of cropland and provides key data for implementing future cropland protection policies in Guangxi.
