2020 Vol. 30, No. 4
Display Method:
2020, 30(4): 557-571.
doi: 10.1007/s11769-020-1135-y
Abstract:
Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau. This study investigated spatiotemporal variations in the frozen ground distribution, the active layer thickness (ALT) of permafrost (PF) soil and the soil freeze depth (SFD) in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost (TTOP) model and Stefan equation. We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River (SRYR). The results showed that approximately half of the PF area (20.37% of the SRYR) was projected to degrade into seasonally frozen ground (SFG) during the past four decades; furthermore, the areal average ALT increased by 3.47 cm/yr, and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018. Accordingly, the growing season Normalized Difference Vegetation Index (NDVI) presented an increasing trend of 0.002/10yr, and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG (the PF to SFG zone). A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season. However, a rapid decrease in SFD (< -1.4 cm/10yr) could have reduced the soil moisture and, thus, decreased the NDVI. The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD. However, the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone, which was mainly limited by water condition because of different change rates of the SFD.
Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau. This study investigated spatiotemporal variations in the frozen ground distribution, the active layer thickness (ALT) of permafrost (PF) soil and the soil freeze depth (SFD) in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost (TTOP) model and Stefan equation. We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River (SRYR). The results showed that approximately half of the PF area (20.37% of the SRYR) was projected to degrade into seasonally frozen ground (SFG) during the past four decades; furthermore, the areal average ALT increased by 3.47 cm/yr, and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018. Accordingly, the growing season Normalized Difference Vegetation Index (NDVI) presented an increasing trend of 0.002/10yr, and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG (the PF to SFG zone). A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season. However, a rapid decrease in SFD (< -1.4 cm/10yr) could have reduced the soil moisture and, thus, decreased the NDVI. The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD. However, the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone, which was mainly limited by water condition because of different change rates of the SFD.
2020, 30(4): 572-587.
doi: 10.1007/s11769-020-1134-z
Abstract:
Grassland fires results in carbon emissions, which directly affects the carbon cycle of ecosystems and the carbon balance. The grassland area of Inner Mongolia accounts for 22% of the total grassland area in China, and many fires occur in the area every year. However, there are few models for estimation of carbon emissions from grassland fires. Accurate estimation of direct carbon emissions from grassland fires is critical to quantifying the contribution of grassland fires to the regional balance of atmospheric carbon. In this study, the regression equations for aboveground biomass (AGB) of grassland in growing season and MODIS NDVI (Normalized Difference Vegetation Index) were established through field experiments, then AGB during Nov.-Apr. were retrieved based on that in Oct. and decline rate, finally surface fuel load was obtained for whole year. Based on controlled combustion experiments of different grassland types in Inner Mongolia, the carbon emission rate of grassland fires for each grassland type were determined, then carbon emission was estimated using proposed method and carbon emission rate. Results revealed that annual average surface fuel load of grasslands in Inner Mongolia during 2000-2016 was approximately 1.1978×1012 kg. The total area of grassland which was burned in the Inner Mongolia region over the 17-year period was 5298.75 km2, with the annual average area of 311.69 km2. The spatial distribution of grassland surface fuel loads is characterized by decreasing from northeast to southwest in Inner Mongolia. The total carbon emissions from grassland fires amounted to 2.24×107 kg with an annual average of 1.32×106 for the study area. The areas with most carbon emissions were mainly concentrated in Old Barag Banner and New Barag Right Banner and on the right side of the Oroqin Autonomous Banner. The spatial characteristics of carbon emission depend on the location of grassland fire, mainly in the northeast of Inner Mongolia include Hulunbuir City, Hinggan League, Xilin Gol League and Ulanqab City. The area and spatial location of grassland fires can directly affect the total amount and spatial distribution of carbon emissions. This study provides a reference for estimating carbon emissions from steppe fires. The model and framework for estimation of carbon emissions from grassland fires established can provide a reference value for estimation of carbon emissions from grassland fires in other regions.
Grassland fires results in carbon emissions, which directly affects the carbon cycle of ecosystems and the carbon balance. The grassland area of Inner Mongolia accounts for 22% of the total grassland area in China, and many fires occur in the area every year. However, there are few models for estimation of carbon emissions from grassland fires. Accurate estimation of direct carbon emissions from grassland fires is critical to quantifying the contribution of grassland fires to the regional balance of atmospheric carbon. In this study, the regression equations for aboveground biomass (AGB) of grassland in growing season and MODIS NDVI (Normalized Difference Vegetation Index) were established through field experiments, then AGB during Nov.-Apr. were retrieved based on that in Oct. and decline rate, finally surface fuel load was obtained for whole year. Based on controlled combustion experiments of different grassland types in Inner Mongolia, the carbon emission rate of grassland fires for each grassland type were determined, then carbon emission was estimated using proposed method and carbon emission rate. Results revealed that annual average surface fuel load of grasslands in Inner Mongolia during 2000-2016 was approximately 1.1978×1012 kg. The total area of grassland which was burned in the Inner Mongolia region over the 17-year period was 5298.75 km2, with the annual average area of 311.69 km2. The spatial distribution of grassland surface fuel loads is characterized by decreasing from northeast to southwest in Inner Mongolia. The total carbon emissions from grassland fires amounted to 2.24×107 kg with an annual average of 1.32×106 for the study area. The areas with most carbon emissions were mainly concentrated in Old Barag Banner and New Barag Right Banner and on the right side of the Oroqin Autonomous Banner. The spatial characteristics of carbon emission depend on the location of grassland fire, mainly in the northeast of Inner Mongolia include Hulunbuir City, Hinggan League, Xilin Gol League and Ulanqab City. The area and spatial location of grassland fires can directly affect the total amount and spatial distribution of carbon emissions. This study provides a reference for estimating carbon emissions from steppe fires. The model and framework for estimation of carbon emissions from grassland fires established can provide a reference value for estimation of carbon emissions from grassland fires in other regions.
2020, 30(4): 588-599.
doi: 10.1007/s11769-020-1136-x
Abstract:
Understanding the spatial patterns of land-use and land-cover (LULC) and their driving forces in transnational areas is important for the sustainable development of these regions. However, the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas. In this study, we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River (TATR) in 2016 across two scales: the entire region and the sub-regions of China, the Democratic People’s Republic of Korea (DPRK), and Russia. Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016, which accounted for 66.86% and 13.60% of the entire region, respectively. Meanwhile, the LULC in the three sub-regions exhibited noticeable differences. In the Chinese and the DPRK’s sub-regions, the area of broadleaf forest was greater than those for the other LULC types, while the Russian sub-region was dominated by broadleaf forest and grassland. The spatial patterns of LULC were mainly influenced by topography, climate, soil properties, and human activities. In addition, the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect. Therefore, we suggest that effective policies and regulations with cooperation among China, the DPRK, and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR.
Understanding the spatial patterns of land-use and land-cover (LULC) and their driving forces in transnational areas is important for the sustainable development of these regions. However, the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas. In this study, we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River (TATR) in 2016 across two scales: the entire region and the sub-regions of China, the Democratic People’s Republic of Korea (DPRK), and Russia. Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016, which accounted for 66.86% and 13.60% of the entire region, respectively. Meanwhile, the LULC in the three sub-regions exhibited noticeable differences. In the Chinese and the DPRK’s sub-regions, the area of broadleaf forest was greater than those for the other LULC types, while the Russian sub-region was dominated by broadleaf forest and grassland. The spatial patterns of LULC were mainly influenced by topography, climate, soil properties, and human activities. In addition, the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect. Therefore, we suggest that effective policies and regulations with cooperation among China, the DPRK, and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR.
2020, 30(4): 600-613.
doi: 10.1007/s11769-020-1137-9
Abstract:
Coastal zones are key interconnectors of terrestrial and marine ecosystems. Due to the degradation and fragmentation of coastal wetlands, there is an urgent need to develop assessment methodology to compare the health of wetland ecosystems at different spatial scales. This will help efficiently develop and implement protections using easy-to-access ecosystem health data. This study aims to understand the spatial distribution of coastal and inland wetland health for China’s coastal regions. A Wetland Health Index (WHI) was developed to provide a basis for policy and decision making. Four utilization models—Long Term Model, Open Model, Nature Reserve Model, and Protected and Economic Model—were defined in the context of China’s coastal regions to specifically examine wetland health. Results show that the average WHI score was 63.6 with the range of 44.8-84.3 for 35 National Nature Reserves (NNRs), and the southern NNRs generally performed better than the northern NNRs. The wetlands in the southern provinces/municipalities are relatively healthier than their northern counterparts. The competent authority has slight influence on WHI scores but duration of conservation establishment does not show a clear correlation. With increasing economic activity, the differences in health conditions (WHI scores) of China’s coastal regions also increase. Gross Domestic Product (GDP) or economic intensification does not relate to WHI scores. Appropriate trade-offs between wetland management and economic development could contribute to improve health conditions, conservation and utilization of coastal and inland wetlands.
Coastal zones are key interconnectors of terrestrial and marine ecosystems. Due to the degradation and fragmentation of coastal wetlands, there is an urgent need to develop assessment methodology to compare the health of wetland ecosystems at different spatial scales. This will help efficiently develop and implement protections using easy-to-access ecosystem health data. This study aims to understand the spatial distribution of coastal and inland wetland health for China’s coastal regions. A Wetland Health Index (WHI) was developed to provide a basis for policy and decision making. Four utilization models—Long Term Model, Open Model, Nature Reserve Model, and Protected and Economic Model—were defined in the context of China’s coastal regions to specifically examine wetland health. Results show that the average WHI score was 63.6 with the range of 44.8-84.3 for 35 National Nature Reserves (NNRs), and the southern NNRs generally performed better than the northern NNRs. The wetlands in the southern provinces/municipalities are relatively healthier than their northern counterparts. The competent authority has slight influence on WHI scores but duration of conservation establishment does not show a clear correlation. With increasing economic activity, the differences in health conditions (WHI scores) of China’s coastal regions also increase. Gross Domestic Product (GDP) or economic intensification does not relate to WHI scores. Appropriate trade-offs between wetland management and economic development could contribute to improve health conditions, conservation and utilization of coastal and inland wetlands.
2020, 30(4): 614-630.
doi: 10.1007/s11769-020-1138-8
Abstract:
This study aims to verify the concept of niches at multiple spatial scales in plant communities. To this end, we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three spatial scales. At the local scale, we calculated the Importance Value (IV) of species in five communities in the north of the Da Hinggan Mountains. At the intermediate scale, we examined five communities in their entirety, calculated the niche breadth of the species, and integrated niche overlap and interspecific association to analyze interspecific relationships. Further, the generalized additive model (GAM) was used to analyze the impact of topography and soil factors on niche characteristics. At the regional scale, we analyzed the geographical distribution of dominant species of R. dauricum plant communities in Northeast China and used principal component analysis (PCA) to analyze the impact of geographical and climate factors on species distribution. The results show that at the local scale, the IV of the species in each community varies widely. At the intermediate scale, species with a wide niche breadth tend to have a high value for IV. Larix gmelinii, Betula platyphylla, R. dauricum, Ledum palustre, and Vaccinium vitis-idaea had a relatively wide niche breadth and a high niche overlap, and the interspecific associations were almost all positive. Elevation and soil nutrients were the most dominant environmental factors. At the regional scale, species with a wide niche breadth tend to have a wide range of distribution, and temperature and precipitation were the most dominant environmental factors. This study suggests that the niche characteristics at three scales are both related and different. Niche characteristics at the local scale were various and labile, and niche characteristics at the intermediate and regional scales were relatively regular. These results show some degree of consistency with previous studies from an evolutionary perspective. The action mechanisms of these communities are related to differences in the dominant environmental factors. In addition, the integration of niche overlap and interspecific association determine interspecific relationships more accurately.
This study aims to verify the concept of niches at multiple spatial scales in plant communities. To this end, we analyzed the niche characteristic of Rhododendron dauricum plant communities in Northeast China at three spatial scales. At the local scale, we calculated the Importance Value (IV) of species in five communities in the north of the Da Hinggan Mountains. At the intermediate scale, we examined five communities in their entirety, calculated the niche breadth of the species, and integrated niche overlap and interspecific association to analyze interspecific relationships. Further, the generalized additive model (GAM) was used to analyze the impact of topography and soil factors on niche characteristics. At the regional scale, we analyzed the geographical distribution of dominant species of R. dauricum plant communities in Northeast China and used principal component analysis (PCA) to analyze the impact of geographical and climate factors on species distribution. The results show that at the local scale, the IV of the species in each community varies widely. At the intermediate scale, species with a wide niche breadth tend to have a high value for IV. Larix gmelinii, Betula platyphylla, R. dauricum, Ledum palustre, and Vaccinium vitis-idaea had a relatively wide niche breadth and a high niche overlap, and the interspecific associations were almost all positive. Elevation and soil nutrients were the most dominant environmental factors. At the regional scale, species with a wide niche breadth tend to have a wide range of distribution, and temperature and precipitation were the most dominant environmental factors. This study suggests that the niche characteristics at three scales are both related and different. Niche characteristics at the local scale were various and labile, and niche characteristics at the intermediate and regional scales were relatively regular. These results show some degree of consistency with previous studies from an evolutionary perspective. The action mechanisms of these communities are related to differences in the dominant environmental factors. In addition, the integration of niche overlap and interspecific association determine interspecific relationships more accurately.
Influence of Sea Surface Temperature on Outbreak of Ulva prolifera in the Southern Yellow Sea, China
2020, 30(4): 631-642.
doi: 10.1007/s11769-020-1129-9
Abstract:
In this study, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images and environmental satellite CCD images, the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the period of 2011-2018 was extracted and combined with MODIS Level3 Photosynthetically Active Radiation (PAR) product data and Earth System Research Laboratory (ESRL) Sea Surface Temperature (SST) data to analyze their influences on the growth and outbreak of Ulva prolifera. The following conclusions were drawn: 1) comprehensive analysis of Ulva prolifera distribution during the eight-year period revealed that the coverage area of Ulva prolifera typically exhibited a gradually increasing trend. The coverage area of Ulva prolifera reached a maximum of approximately 1714.21 km2 during the eight-year period in late June 2015. The area affected by Ulva prolifera fluctuated. In mid-July 2014, the area affected by Ulva prolifera reached a maximum of approximately 39 020.63 km2. 2) The average growth rate of Ulva prolifera was positive in May and June but negative in July. During the outbreak of Ulva prolifera, the SST in the southern Yellow Sea tended to increase each month. The SST anomaly and average growth rate of Ulva prolifera were positively correlated in May (R<、i>2 = 0.62), but not significantly correlated in June or July. 3) The variation trends of PAR and SST were approximately the same, and the PAR during this time period maintained a range of 40-50 mol/(m2·d), providing sufficient illumination for the growth and outbreak of Ulva prolifera. In addition, the abundant nutrients and suitable temperature in the sea area near northern Jiangsu shoal resulted in a high growth rate of Ulva prolifera in May. In summary, the outbreak of Ulva prolifera was closely related to the environmental factors including SST, nutrients, and PAR. Sufficient nutrients and suitable temperatures resulted in a fast growth rate of Ulva prolifera. However, under poor nutrient conditions, even more suitable temperatures were not sufficient to trigger an outbreak of Ulva prolifera.
In this study, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images and environmental satellite CCD images, the spatio-temporal distribution of Ulva prolifera in the southern Yellow Sea during the period of 2011-2018 was extracted and combined with MODIS Level3 Photosynthetically Active Radiation (PAR) product data and Earth System Research Laboratory (ESRL) Sea Surface Temperature (SST) data to analyze their influences on the growth and outbreak of Ulva prolifera. The following conclusions were drawn: 1) comprehensive analysis of Ulva prolifera distribution during the eight-year period revealed that the coverage area of Ulva prolifera typically exhibited a gradually increasing trend. The coverage area of Ulva prolifera reached a maximum of approximately 1714.21 km2 during the eight-year period in late June 2015. The area affected by Ulva prolifera fluctuated. In mid-July 2014, the area affected by Ulva prolifera reached a maximum of approximately 39 020.63 km2. 2) The average growth rate of Ulva prolifera was positive in May and June but negative in July. During the outbreak of Ulva prolifera, the SST in the southern Yellow Sea tended to increase each month. The SST anomaly and average growth rate of Ulva prolifera were positively correlated in May (R<、i>2 = 0.62), but not significantly correlated in June or July. 3) The variation trends of PAR and SST were approximately the same, and the PAR during this time period maintained a range of 40-50 mol/(m2·d), providing sufficient illumination for the growth and outbreak of Ulva prolifera. In addition, the abundant nutrients and suitable temperature in the sea area near northern Jiangsu shoal resulted in a high growth rate of Ulva prolifera in May. In summary, the outbreak of Ulva prolifera was closely related to the environmental factors including SST, nutrients, and PAR. Sufficient nutrients and suitable temperatures resulted in a fast growth rate of Ulva prolifera. However, under poor nutrient conditions, even more suitable temperatures were not sufficient to trigger an outbreak of Ulva prolifera.
2020, 30(4): 643-664.
doi: 10.1007/s11769-020-1139-7
Abstract:
China is experiencing conflicts between its large population and scarce arable land, and between a demand for high productivity and the severe soil erosion of arable land. Since 1949, China has committed to soil and water conservation (SWC), for which eight regions and 41 subregions have been developed to improve the environment and increase land productivity. To obtain information from the regional planning and strategies for SWC and to explore whether SWC practices simultaneously contribute to soil conservation, ecosystem functioning, and the livelihoods of local farmers, and to summarize the successful experiences of various SWC paradigms with distinct characteristics and mechanisms of soil erosion, this paper systematically presents seven SWC regions (excluding the Tibetan Plateau region) and 14 typical SWC paradigms, focusing on erosion mechanisms and the key challenges or issues in the seven regions as well as on the core problems, main objectives, key technologies, and the performance of the 14 typical paradigms. In summary, the 14 typical SWC paradigms successfully prevent and control local soil erosion, and have largely enhanced, or at least do not harm, the livelihoods of local farmers. However, there remain many challenges and issues on SWC and socioeconomic development that need to be addressed in the seven SWC regions. China, thus, still has a long way to go in successfully gaining the win-win objective of SWC and human aspects of development.
China is experiencing conflicts between its large population and scarce arable land, and between a demand for high productivity and the severe soil erosion of arable land. Since 1949, China has committed to soil and water conservation (SWC), for which eight regions and 41 subregions have been developed to improve the environment and increase land productivity. To obtain information from the regional planning and strategies for SWC and to explore whether SWC practices simultaneously contribute to soil conservation, ecosystem functioning, and the livelihoods of local farmers, and to summarize the successful experiences of various SWC paradigms with distinct characteristics and mechanisms of soil erosion, this paper systematically presents seven SWC regions (excluding the Tibetan Plateau region) and 14 typical SWC paradigms, focusing on erosion mechanisms and the key challenges or issues in the seven regions as well as on the core problems, main objectives, key technologies, and the performance of the 14 typical paradigms. In summary, the 14 typical SWC paradigms successfully prevent and control local soil erosion, and have largely enhanced, or at least do not harm, the livelihoods of local farmers. However, there remain many challenges and issues on SWC and socioeconomic development that need to be addressed in the seven SWC regions. China, thus, still has a long way to go in successfully gaining the win-win objective of SWC and human aspects of development.
2020, 30(4): 665-676.
doi: 10.1007/s11769-020-1140-1
Abstract:
Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy. Hence, a better understanding of the urban growth boundary (UGB) has profound theoretical and practical significance regarding sustainable urban development. This study devised a raster-based land use spatial optimization (LUSO) framework, and utilized ant colony optimization (ACO) algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group (CZTCG) in China. The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth. Multi growth scenario including a single development center, multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050, and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG. The main results are listed as the following. 1) It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model, and the optimal form of the spatial pattern can be defined. 2) With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns, the total optimization target performance gradually increases, which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group. 3) Subject to the regional social and economic development stage, absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration. Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration. The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.
Urban agglomeration is the main spatial organization mode used by the Chinese government to promote the policy of new urbanization strategy. Hence, a better understanding of the urban growth boundary (UGB) has profound theoretical and practical significance regarding sustainable urban development. This study devised a raster-based land use spatial optimization (LUSO) framework, and utilized ant colony optimization (ACO) algorithm to delimit the smart growth boundaries of the Changsha-Zhuzhou-Xiangtan city group (CZTCG) in China. The aim of this study is to design a LUSO model to explore an optimal pattern of urban agglomeration for sustainable growth. Multi growth scenario including a single development center, multipolar development and balanced development patterns are generated by the LUSO model for the year of 2050, and the optimum spatial pattern is chosen based on objectives comparison and the present stage of economic and social development in CZTCG. The main results are listed as the following. 1) It is feasible to identify the growth boundaries of the urban agglomeration using the land use spatial optimization model, and the optimal form of the spatial pattern can be defined. 2) With the growth trend of the urban agglomeration gradually spreads from a single center to multi-centers and even small towns, the total optimization target performance gradually increases, which means that the traditional pie-shaped development does not meet the maximum comprehensive benefit of the city group. 3) Subject to the regional social and economic development stage, absolute fair development or simply developing the central city is not conducive to promoting the coordinated development of the urban agglomeration. Gradient equalization and gradual advancement are the best choice for UGB delineation of urban agglomeration. The findings of this study would be useful to identify the UGB in CZTCG for more sustainable urban development in the future.
2020, 30(4): 677-694.
doi: 10.1007/s11769-020-1131-2
Abstract:
The objective of this study is to develop a framework for re-examining and re-defining the classical concepts of spatial interaction and reorganization in the urban system. We introduce a modified radiation model for spatial interactions, coupled with migration big data, transport accessibility algorithm, and city competitiveness assessment for efficient distribution of the inter-city flow through the network. The Yangtze River Middle Reaches (YRMR) urban agglomeration (UA) is chosen as the case study region to systematically identify and measure its spatial configuration and to gain insights for other UAs’ sustainable development in China. The results are also compared with those computed by the classical gravity model to systematically discuss the applicability of spatial interaction laws and models, and related practical policies for regional sustainable development are discussed based on the findings as well. The conclusions are highlighted below: 1) Combining with the ‘city network paradigm’ and ‘central place theory’ can better express the spatial configurations of city systems in the context of ‘space of flows’; 2) The results validate the potentialities of a multi-analysis framework to assess the spatial configurations of city network based on the improved radiation model and network analysis tools; 3) The applications of spatial interaction models should be considered according to the specific geographical entity and its spatial scale.
The objective of this study is to develop a framework for re-examining and re-defining the classical concepts of spatial interaction and reorganization in the urban system. We introduce a modified radiation model for spatial interactions, coupled with migration big data, transport accessibility algorithm, and city competitiveness assessment for efficient distribution of the inter-city flow through the network. The Yangtze River Middle Reaches (YRMR) urban agglomeration (UA) is chosen as the case study region to systematically identify and measure its spatial configuration and to gain insights for other UAs’ sustainable development in China. The results are also compared with those computed by the classical gravity model to systematically discuss the applicability of spatial interaction laws and models, and related practical policies for regional sustainable development are discussed based on the findings as well. The conclusions are highlighted below: 1) Combining with the ‘city network paradigm’ and ‘central place theory’ can better express the spatial configurations of city systems in the context of ‘space of flows’; 2) The results validate the potentialities of a multi-analysis framework to assess the spatial configurations of city network based on the improved radiation model and network analysis tools; 3) The applications of spatial interaction models should be considered according to the specific geographical entity and its spatial scale.
2020, 30(4): 695-709.
doi: 10.1007/s11769-020-1130-3
Abstract:
The increasing availability of data in the urban context (e.g., mobile phone, smart card and social media data) allows us to study urban dynamics at much finer temporal resolutions (e.g., diurnal urban dynamics). Mobile phone data, for instance, are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics. While previous studies often use call detail record (CDR) data, this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage. We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data. Specifically, urban areas’ diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data. Urban areas are then classified based on the obtained signatures. The classification provides insights into city planning and development. Using the proposed framework, a case study was implemented in the city of Wuhu, China to understand its urban dynamics. The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone (TAZ) level. This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu. This article concludes with discussions on several common challenges associated with using network-driven mobile phone data, which should be addressed in future studies.
The increasing availability of data in the urban context (e.g., mobile phone, smart card and social media data) allows us to study urban dynamics at much finer temporal resolutions (e.g., diurnal urban dynamics). Mobile phone data, for instance, are found to be a useful data source for extracting diurnal human mobility patterns and for understanding urban dynamics. While previous studies often use call detail record (CDR) data, this study deploys aggregated network-driven mobile phone data that may reveal human mobility patterns more comprehensively and can mitigate some of the privacy concerns raised by mobile phone data usage. We first propose an analytical framework for characterizing and classifying urban areas based on their temporal activity patterns extracted from mobile phone data. Specifically, urban areas’ diurnal spatiotemporal signatures of human mobility patterns are obtained through longitudinal mobile phone data. Urban areas are then classified based on the obtained signatures. The classification provides insights into city planning and development. Using the proposed framework, a case study was implemented in the city of Wuhu, China to understand its urban dynamics. The empirical study suggests that human activities in the city of Wuhu are highly concentrated at the Traffic Analysis Zone (TAZ) level. This large portion of local activities suggests that development and planning strategies that are different from those used by metropolitan Chinese cities should be applied in the city of Wuhu. This article concludes with discussions on several common challenges associated with using network-driven mobile phone data, which should be addressed in future studies.
2020, 30(4): 710-724.
doi: 10.1007/s11769-020-1127-y
Abstract:
This study attempts to evaluate the rationality of the spatial layout of shopping malls and identify the urban area with poor shopping mall accessibility, as well as to provide a reference and assist decision-making for planning. Using the case of Nanjing, China, this study developed a method to evaluate the accessibility of shopping malls by three transport modes (car traffic, public transit, and bicycle). Specially, we divide the urban space into a regular hexagonal grid and harvest the total travel time from each of 7204 hexagon centroids to each of 129 shopping malls using the Baidu Internet map. The door-to-door travel time approach is used to evaluate all travel stages (walking, waiting, transfer, and transportation) based on travel time calculations. We further divide the shopping malls into two levels (super-regional and regional) based on the Dianping App’s information and develop the indicator of accessibility to shopping malls: the number of shopping malls within tolerance time thresholds and apply the closest facility and cumulative opportunities methods to measure accessibility scores. The results show that the accessibility estimations vary greatly with transport modes. The accessibility of shopping malls presents a concentric ring trend centered on the city center under the car traffic and bicycle modes. And public transit accessibility tends to axially extend due to the topology of bus routes and metro lines. In particular, we observe that the accessibility of shopping malls in Nanjing has an uneven spatial distribution pattern, with high accessibility values in the central urban areas and lots of underserved areas in urban fringe regions. Based on the accessibility measurements, we finally map the poor accessibility area and propose corresponding implications for urban planning.
This study attempts to evaluate the rationality of the spatial layout of shopping malls and identify the urban area with poor shopping mall accessibility, as well as to provide a reference and assist decision-making for planning. Using the case of Nanjing, China, this study developed a method to evaluate the accessibility of shopping malls by three transport modes (car traffic, public transit, and bicycle). Specially, we divide the urban space into a regular hexagonal grid and harvest the total travel time from each of 7204 hexagon centroids to each of 129 shopping malls using the Baidu Internet map. The door-to-door travel time approach is used to evaluate all travel stages (walking, waiting, transfer, and transportation) based on travel time calculations. We further divide the shopping malls into two levels (super-regional and regional) based on the Dianping App’s information and develop the indicator of accessibility to shopping malls: the number of shopping malls within tolerance time thresholds and apply the closest facility and cumulative opportunities methods to measure accessibility scores. The results show that the accessibility estimations vary greatly with transport modes. The accessibility of shopping malls presents a concentric ring trend centered on the city center under the car traffic and bicycle modes. And public transit accessibility tends to axially extend due to the topology of bus routes and metro lines. In particular, we observe that the accessibility of shopping malls in Nanjing has an uneven spatial distribution pattern, with high accessibility values in the central urban areas and lots of underserved areas in urban fringe regions. Based on the accessibility measurements, we finally map the poor accessibility area and propose corresponding implications for urban planning.
2020, 30(4): 725-735.
doi: 10.1007/s11769-020-1141-0
Abstract:
Promoting women’s employment is not only the need of social and economic development, but also the historical mission of liberating women. This paper uses data from the 1% Population Sample Survey, taken in Guangdong Province in 2015, to explore how women’s marital status, education, and family environment affect the female non-agricultural employment rate (FNAER) on a county scale using a spatial-lag model. The results show that: 1) The female non-agricultural employment rate in counties of Guangdong Province is low, with more than three-quarters of counties having female non-agricultural employment rate less than 50%. Moreover, the spatial distribution of FNAER is uneven, with the high-value areas concentrated in the southeast and the low-value areas mainly distributed in the central and western parts of Guangdong Province. 2) From the perspective of industry, there are significant spatial differences among women. In the southeast, women are mainly engaged in the secondary industry, while in the central and western regions, women are mainly engaged in the tertiary industry. 3) Women having better skills and more effective support from the elderly can improve the FNAER. Women having lower skills, smaller-scale families, a higher fertility rate, and households with two or more elderly members have a negative effect on the FNAER. 4) Public policies suggest that improving women’s education and their family environment, building social welfare facilities, and repairing the family environment will increase the FNAER.
Promoting women’s employment is not only the need of social and economic development, but also the historical mission of liberating women. This paper uses data from the 1% Population Sample Survey, taken in Guangdong Province in 2015, to explore how women’s marital status, education, and family environment affect the female non-agricultural employment rate (FNAER) on a county scale using a spatial-lag model. The results show that: 1) The female non-agricultural employment rate in counties of Guangdong Province is low, with more than three-quarters of counties having female non-agricultural employment rate less than 50%. Moreover, the spatial distribution of FNAER is uneven, with the high-value areas concentrated in the southeast and the low-value areas mainly distributed in the central and western parts of Guangdong Province. 2) From the perspective of industry, there are significant spatial differences among women. In the southeast, women are mainly engaged in the secondary industry, while in the central and western regions, women are mainly engaged in the tertiary industry. 3) Women having better skills and more effective support from the elderly can improve the FNAER. Women having lower skills, smaller-scale families, a higher fertility rate, and households with two or more elderly members have a negative effect on the FNAER. 4) Public policies suggest that improving women’s education and their family environment, building social welfare facilities, and repairing the family environment will increase the FNAER.
2020, 30(4): 736-748.
doi: 10.1007/s11769-020-1142-z
Abstract:
Green development is an important issue of sustainable development in China. Due to the relatively backward economy and the fragile ecological environment, restricted development zones need to embrace green development. Taking 38 counties in Jilin Province as the empirical research objects, and based on cross-sectional data for each county in 2005, 2010, and 2015, we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency (GDE) in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis (SBM-DEA) model. Moreover, the factors that influence GDE were further analyzed using the Tobit model. We found that: first, GDE showed a V-shaped trend in restricted development zones of Jilin Province. The differences in GDE in the eastern, central, and western Jilin Province increased gradually. Second, 76% of counties in the restricted development zones had high or higher efficiencies. The resource-based cities were the main areas with low or lower GDE. Third, the economic development level was the core factor affecting GDE. Urbanization level had a significant negative effect on GDE in the restricted development zones. The effect of technological innovation level on GDE fluctuated, and we found that a ‘backward mechanism’ of technological innovation was beginning to form. Industrial structure and environmental governance had no significant effects on GDE.
Green development is an important issue of sustainable development in China. Due to the relatively backward economy and the fragile ecological environment, restricted development zones need to embrace green development. Taking 38 counties in Jilin Province as the empirical research objects, and based on cross-sectional data for each county in 2005, 2010, and 2015, we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency (GDE) in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis (SBM-DEA) model. Moreover, the factors that influence GDE were further analyzed using the Tobit model. We found that: first, GDE showed a V-shaped trend in restricted development zones of Jilin Province. The differences in GDE in the eastern, central, and western Jilin Province increased gradually. Second, 76% of counties in the restricted development zones had high or higher efficiencies. The resource-based cities were the main areas with low or lower GDE. Third, the economic development level was the core factor affecting GDE. Urbanization level had a significant negative effect on GDE in the restricted development zones. The effect of technological innovation level on GDE fluctuated, and we found that a ‘backward mechanism’ of technological innovation was beginning to form. Industrial structure and environmental governance had no significant effects on GDE.
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