2021 Vol. 31, No. 5
Display Method:
2021, 31(5): 765-781.
doi: 10.1007/s11769-021-1225-5
Abstract:
Based on Remote Sensing (RS) and Geographical Information System (GIS) technology, urban expansion of 75 cities in China from the 1970s to 2020 was reconstructed by visual-interpretation method, which described the growing process of urban lands and its influences on local land use structures synchronously. By employing annual expansion area per city and urban expansion density, spatial-temporal characteristics and macro patterns of urban expansion were analyzed from the aspects of regional-distributions, administrative-levels and population-sizes comprehensively. Results indicate that: 1) urban expansion in China was universal, distinct, persistent, periodic and fluctuating. In the past five decades, urban lands of 75 monitored cities in China expanded dramatically from 3606.26 km2 to 30 521.13 km2. 2) Though urban expansion presented significant differences from the aspects of regional distribution, administrative levels, and population sizes, it exhibited a deceleration trend in the 13th Five-Year Plan among all kinds of cities. 3) Cultivated lands were the first land resource for urban expansion, and 55.17% of newly-expanded urban lands appeared by encroaching this land use type. China’s urban expansion has caused sustained pressure on cultivated land protection, especially in super megacities, and the contradiction between urban expansion and cultivated land protection will always exist. 4) The compactness of urban lands in China increased before 1987 and reduced in the next three decades, which was consistent with the implementation of major policies and the deployment of national strategies, and is expected to become compact with a stopping declining or even rebounding after the 13th Five-Year Plan.
Based on Remote Sensing (RS) and Geographical Information System (GIS) technology, urban expansion of 75 cities in China from the 1970s to 2020 was reconstructed by visual-interpretation method, which described the growing process of urban lands and its influences on local land use structures synchronously. By employing annual expansion area per city and urban expansion density, spatial-temporal characteristics and macro patterns of urban expansion were analyzed from the aspects of regional-distributions, administrative-levels and population-sizes comprehensively. Results indicate that: 1) urban expansion in China was universal, distinct, persistent, periodic and fluctuating. In the past five decades, urban lands of 75 monitored cities in China expanded dramatically from 3606.26 km2 to 30 521.13 km2. 2) Though urban expansion presented significant differences from the aspects of regional distribution, administrative levels, and population sizes, it exhibited a deceleration trend in the 13th Five-Year Plan among all kinds of cities. 3) Cultivated lands were the first land resource for urban expansion, and 55.17% of newly-expanded urban lands appeared by encroaching this land use type. China’s urban expansion has caused sustained pressure on cultivated land protection, especially in super megacities, and the contradiction between urban expansion and cultivated land protection will always exist. 4) The compactness of urban lands in China increased before 1987 and reduced in the next three decades, which was consistent with the implementation of major policies and the deployment of national strategies, and is expected to become compact with a stopping declining or even rebounding after the 13th Five-Year Plan.
2021, 31(5): 782-794.
doi: 10.1007/s11769-021-1226-4
Abstract:
Annual Land Use/Land Cover (LULC) change information at medium spatial resolution (i.e., at 30 m) is used in applications ranging from land management to achieving sustainable development goals related to food security. However, obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities, training data, and workflow design. Using the Google Earth Engine (GEE), which provides a catalog of multi-source data and a cloud-based environment, we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery. Our major contribution is a hybrid approach that includes three major components: 1) a high-quality training dataset derived from multi-source LULC products, filtered by k-means clustering analysis; 2) a yearly 39-band stack feature space, utilizing all available Landsat data and DEM data; and 3) a self-adaptive Random Forest (RF) method, introduced for LULC classification. Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33% in the entire Delta. The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability. In addition, as the proposed workflow is based on open source data and the GEE cloud platform, it can be used anywhere by anyone in the world.
Annual Land Use/Land Cover (LULC) change information at medium spatial resolution (i.e., at 30 m) is used in applications ranging from land management to achieving sustainable development goals related to food security. However, obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities, training data, and workflow design. Using the Google Earth Engine (GEE), which provides a catalog of multi-source data and a cloud-based environment, we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery. Our major contribution is a hybrid approach that includes three major components: 1) a high-quality training dataset derived from multi-source LULC products, filtered by k-means clustering analysis; 2) a yearly 39-band stack feature space, utilizing all available Landsat data and DEM data; and 3) a self-adaptive Random Forest (RF) method, introduced for LULC classification. Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33% in the entire Delta. The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability. In addition, as the proposed workflow is based on open source data and the GEE cloud platform, it can be used anywhere by anyone in the world.
2021, 31(5): 795-814.
doi: 10.1007/s11769-021-1227-3
Abstract:
In this study, we developed an evaluation index system for green total-factor water-use efficiency (GTFWUE) which reflected both economic and green efficiencies of water resource utilization. Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions (hereafter provinces) in China (not including Tibet, Hong Kong, Macao, Taiwan as no data) from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output. We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics, and empirically determined the factors affecting GTFWUE using a spatial econometric model. The evaluation results revealed that the GTFWUE differed substantially between the regions. The provinces with high and low GTFWUE values were located in the coastal and inland areas of China, respectively. The eastern region had a significantly higher GTFWUE than the central and western regions. The GTFWUEs for all three regions (eastern, central, and western regions) decreased slowly from 2000 to 2011 (except 2005), remained stable from 2012 to 2016, and rapidly increased in 2017 before decreasing again in 2018. We found significant spatial correlations between the provincial GTFWUEs. The GTFWUE for most provinces belonged to the high-high or low-low cluster region, revealing a significant spatial clustering effect of provincial GTFWUEs. We also found that China’s GTFWUE was highly promoted by economic growth, population size, opening-up level, and urbanization level, and was evidently hindered by water endowment, technological progress, and government influence. However, the water-use structure had little impact on GTFWUE. This study fully demonstrated that the water use mode would be improved, and water resources needed to be used more efficiently and green in China. Moreover, based on the findings of this study, several policy recommendations were proposed from the aspects of cross-regional cooperation, economy, society, and institution.
In this study, we developed an evaluation index system for green total-factor water-use efficiency (GTFWUE) which reflected both economic and green efficiencies of water resource utilization. Then we measured the GTFWUE of 30 provinces/municipalities/autonomous regions (hereafter provinces) in China (not including Tibet, Hong Kong, Macao, Taiwan as no data) from 2000 to 2018 using a minimum distance to the strong frontier model that contained an undesirable output. We further analyzed the regional differences and spatial correlations of GTFWUE using these values based on Global and Local Moran’s I statistics, and empirically determined the factors affecting GTFWUE using a spatial econometric model. The evaluation results revealed that the GTFWUE differed substantially between the regions. The provinces with high and low GTFWUE values were located in the coastal and inland areas of China, respectively. The eastern region had a significantly higher GTFWUE than the central and western regions. The GTFWUEs for all three regions (eastern, central, and western regions) decreased slowly from 2000 to 2011 (except 2005), remained stable from 2012 to 2016, and rapidly increased in 2017 before decreasing again in 2018. We found significant spatial correlations between the provincial GTFWUEs. The GTFWUE for most provinces belonged to the high-high or low-low cluster region, revealing a significant spatial clustering effect of provincial GTFWUEs. We also found that China’s GTFWUE was highly promoted by economic growth, population size, opening-up level, and urbanization level, and was evidently hindered by water endowment, technological progress, and government influence. However, the water-use structure had little impact on GTFWUE. This study fully demonstrated that the water use mode would be improved, and water resources needed to be used more efficiently and green in China. Moreover, based on the findings of this study, several policy recommendations were proposed from the aspects of cross-regional cooperation, economy, society, and institution.
2021, 31(5): 815-828.
doi: 10.1007/s11769-021-1228-2
Abstract:
The Healthy China Initiative is a major health strategy being pursued by the country. To prevent and control different types of diseases as well as their complex variants, research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide. This study analyzed monthly data on the incidence of influenza by using different methods, including Moran’s I, the hotspot analysis model, concentration analysis, and correlation analysis, to determine the characteristics of spatio-temporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017, and to examine its relationship with air pollution. According to the results, the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017, with small peaks in 2009 and 2014. More cases of influenza were recorded in the first and fourth quarters of each year. Regions with higher incidences of influenza were concentrated in northwestern and northern China, and in the coastal areas of southeastern China. Over time, the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country. A significant relationship was observed between the incidence of influenza and factors related to air pollution. The contents of five air pollutants (PM2.5, PM10, SO2, NO2, and CO) were significantly positively correlated with the incidence of influenza, with a decreasing order of contribution to it of SO2 > CO > NO2 > PM2.5 > PM10. The content of O3 in the air was negatively correlated with the incidence of influenza. The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences. The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.
The Healthy China Initiative is a major health strategy being pursued by the country. To prevent and control different types of diseases as well as their complex variants, research on the spatio-temporal differentiation among and mechanisms of influence of epidemic diseases is growing worldwide. This study analyzed monthly data on the incidence of influenza by using different methods, including Moran’s I, the hotspot analysis model, concentration analysis, and correlation analysis, to determine the characteristics of spatio-temporal differentiation in the incidence of influenza across prefecture-level cities in China from 2004 to 2017, and to examine its relationship with air pollution. According to the results, the overall incidence of influenza in China exhibited a trend of increase from 2004 to 2017, with small peaks in 2009 and 2014. More cases of influenza were recorded in the first and fourth quarters of each year. Regions with higher incidences of influenza were concentrated in northwestern and northern China, and in the coastal areas of southeastern China. Over time, the distribution of regions with a higher incidence of influenza has shifted from the west to the east of the country. A significant relationship was observed between the incidence of influenza and factors related to air pollution. The contents of five air pollutants (PM2.5, PM10, SO2, NO2, and CO) were significantly positively correlated with the incidence of influenza, with a decreasing order of contribution to it of SO2 > CO > NO2 > PM2.5 > PM10. The content of O3 in the air was negatively correlated with the incidence of influenza. The influence of air pollution-related factors on the incidence of influenza in different regions and seasons showed minor differences. The large-scale empirical results provided here can supply a scientific basis for governmental disease control authorities to formulate strategies for regional prevention and control.
2021, 31(5): 829-847.
doi: 10.1007/s11769-021-1229-1
Abstract:
Rapid urbanization leads to dramatic changes in land use patterns, and the land use/cover change (LUCC) can reflect the spatial impact of urbanization on the ecological environment. Simulating the process of LUCC and predicting the ecological risk future changes can provide supports for urban ecological management. Taking the Yangtze River Delta Urban Agglomeration (YRDUA), China as the study area, four developmental scenarios were set on the basis of the land use data from 2005 to 2015. The temporal land use changes were predicted by the integration of the system dynamic and the future land use simulation (SD-FLUS) model, and the geographically weighted regression (GWR) model was used to identify the spatial heterogeneity and evolution characteristics between ecological risk index (ERI) and socio-economic driving forces. Results showed that: 1) From 2005 to 2015, the expansion of construction land (7670.24 km2) mainly came from the occupation of cultivated land (7854.22 km2). The Kappa coefficient of the SD-FLUS model was 0.886, indicating that this model could be used to predict the future land use changes in the YRDUA. 2) Gross domestic production (GDP) and population density (POP) showed a positive effect on the ERI, and the impact of POP exceeded that of GDP. The ERI showed the characteristics of zonal diffusion and a slight upward trend, and the high ecological risk region increased by 6.09%, with the largest increase. 3) Under different developmental scenarios, the land use and ecological risk patterns varied. The construction land is increased by 5.76%, 7.41%, 5.25% and 6.06%, respectively. And the high ecological risk region accounted for 12.71%, 15.06%, 11.89%, and 12.94%, correspondingly. In Scenario D, the structure of land use and ecological risk pattern was better compared with other scenarios considering the needs of rapid economic and ecological protection. This study is helpful to understand the spatio-temporal pattern and demand of land use types, grasp the ecological security pattern of large-scale areas, and provide scientific basis for the territory development of urban agglomeration in the future.
Rapid urbanization leads to dramatic changes in land use patterns, and the land use/cover change (LUCC) can reflect the spatial impact of urbanization on the ecological environment. Simulating the process of LUCC and predicting the ecological risk future changes can provide supports for urban ecological management. Taking the Yangtze River Delta Urban Agglomeration (YRDUA), China as the study area, four developmental scenarios were set on the basis of the land use data from 2005 to 2015. The temporal land use changes were predicted by the integration of the system dynamic and the future land use simulation (SD-FLUS) model, and the geographically weighted regression (GWR) model was used to identify the spatial heterogeneity and evolution characteristics between ecological risk index (ERI) and socio-economic driving forces. Results showed that: 1) From 2005 to 2015, the expansion of construction land (7670.24 km2) mainly came from the occupation of cultivated land (7854.22 km2). The Kappa coefficient of the SD-FLUS model was 0.886, indicating that this model could be used to predict the future land use changes in the YRDUA. 2) Gross domestic production (GDP) and population density (POP) showed a positive effect on the ERI, and the impact of POP exceeded that of GDP. The ERI showed the characteristics of zonal diffusion and a slight upward trend, and the high ecological risk region increased by 6.09%, with the largest increase. 3) Under different developmental scenarios, the land use and ecological risk patterns varied. The construction land is increased by 5.76%, 7.41%, 5.25% and 6.06%, respectively. And the high ecological risk region accounted for 12.71%, 15.06%, 11.89%, and 12.94%, correspondingly. In Scenario D, the structure of land use and ecological risk pattern was better compared with other scenarios considering the needs of rapid economic and ecological protection. This study is helpful to understand the spatio-temporal pattern and demand of land use types, grasp the ecological security pattern of large-scale areas, and provide scientific basis for the territory development of urban agglomeration in the future.
2021, 31(5): 848-866.
doi: 10.1007/s11769-021-1230-8
Abstract:
The relationship between landscape patterns and soil conservation, as well as the need for nature-based soil erosion control and landscape pattern optimization, have increasingly gained attention in the scientific and political community in the past decade. With the implementation of a series of afforestation/reforestation projects in the western China, the optimization and management of forest landscape patterns will become more important for soil conservation. In this study, the Bailongjiang Watershed (BLJW), in the western China, was used as a case study to explore the relationship between the forest landscape pattern and soil conservation services using mathematical and spatial statistics methods. A spatially-explicit model called the sediment delivery ratio (SDR) model of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) was used to assess the soil conservation service in each sub-basin of BLJW in 1990, 2002, and 2014, and landscape indices were used to describe changes in forest landscape patterns in each sub-basin. Nine forest landscape indices, including the percentage of landscape (PLAND), largest patch index (LPI), edge density (ED), landscape shape index (LSI), mean patch shape (SHAPE_MN), patch cohesion index (COHESION), landscape division index (DIVISION), splitting index (SPLIT) and aggregation index (AI), were significantly correlated to the soil conservation service. PLAND, AI, LSI and SPLIT of forestland were determined to be the more important landscape indicators. The results also indicated that soil conservation was substantially scale-dependent. The results demonstrated that landscape type diversity greatly affected watershed soil conservation and can be used for forest landscape restoration and management. Furthermore, spatial statistics analysis indicated that the Spatial Lag Model (SLM) was superior to the Ordinary Least Squares (OLS) for soil conservation regressions in 1990 and 2014, while OLS was more appropriate for the regression in 2002. These findings will be useful for enhancing soil conservation and for optimizing mountainous forest landscape patterns for afforestation/reforestation and regional development. Future planning and implementation of ecological restoration should focus more on strategic spatial planning and integrated landscape management with full consideration of future climate, water availability/consumption, hydrological regime, topography, and watershed features, especially on afforestation and revegetation projects in western mountainous China, where the socio-ecological system is fragile and poor.
The relationship between landscape patterns and soil conservation, as well as the need for nature-based soil erosion control and landscape pattern optimization, have increasingly gained attention in the scientific and political community in the past decade. With the implementation of a series of afforestation/reforestation projects in the western China, the optimization and management of forest landscape patterns will become more important for soil conservation. In this study, the Bailongjiang Watershed (BLJW), in the western China, was used as a case study to explore the relationship between the forest landscape pattern and soil conservation services using mathematical and spatial statistics methods. A spatially-explicit model called the sediment delivery ratio (SDR) model of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) was used to assess the soil conservation service in each sub-basin of BLJW in 1990, 2002, and 2014, and landscape indices were used to describe changes in forest landscape patterns in each sub-basin. Nine forest landscape indices, including the percentage of landscape (PLAND), largest patch index (LPI), edge density (ED), landscape shape index (LSI), mean patch shape (SHAPE_MN), patch cohesion index (COHESION), landscape division index (DIVISION), splitting index (SPLIT) and aggregation index (AI), were significantly correlated to the soil conservation service. PLAND, AI, LSI and SPLIT of forestland were determined to be the more important landscape indicators. The results also indicated that soil conservation was substantially scale-dependent. The results demonstrated that landscape type diversity greatly affected watershed soil conservation and can be used for forest landscape restoration and management. Furthermore, spatial statistics analysis indicated that the Spatial Lag Model (SLM) was superior to the Ordinary Least Squares (OLS) for soil conservation regressions in 1990 and 2014, while OLS was more appropriate for the regression in 2002. These findings will be useful for enhancing soil conservation and for optimizing mountainous forest landscape patterns for afforestation/reforestation and regional development. Future planning and implementation of ecological restoration should focus more on strategic spatial planning and integrated landscape management with full consideration of future climate, water availability/consumption, hydrological regime, topography, and watershed features, especially on afforestation and revegetation projects in western mountainous China, where the socio-ecological system is fragile and poor.
2021, 31(5): 867-876.
doi: 10.1007/s11769-021-1231-7
Abstract:
Baseflow, a component of the total streamflow, plays a key role in maintaining aquatic habitats, particularly during extreme drought events. This study investigated baseflow response to a prolonged and extreme meteorological drought event in the Baiyangdian Basin (BYD basin), a temperate water-limited basin in North China. Applying a precipitation series, piecewise regression was used to determine this extreme meteorological drought event, while the Automatic Baseflow Identification Technique (ABIT) was used to estimate a recession parameter (α), which was used to isolate baseflow from total streamflow. Results showed that: 1) annual precipitation exhibited significant decreasing trends (P < 0.05) with an average change of –1.81 mm/yr2. The precipitation deficit revealed that the start and end date of the extreme meteorological drought event was from August 1996 to May 2011, respectively, persisting for a total of 178 months (roughly 15 yr); 2) hydrological drought (including streamflow and baseflow) lagged behind meteorological drought while predictably persisting longer than extreme meteorological drought (i.e., precipitation); and 3) baseflow decreased dramatically under meteorological drought at both seasonal and annual scales, resulting in significantly decreasing trends during drought periods. Findings from this study confirmed that hydrological events caused by extreme meteorological drought can alter the magnitude and duration of baseflow and total streamflow, which will have an inevitable influence on aquatic ecosystems.
Baseflow, a component of the total streamflow, plays a key role in maintaining aquatic habitats, particularly during extreme drought events. This study investigated baseflow response to a prolonged and extreme meteorological drought event in the Baiyangdian Basin (BYD basin), a temperate water-limited basin in North China. Applying a precipitation series, piecewise regression was used to determine this extreme meteorological drought event, while the Automatic Baseflow Identification Technique (ABIT) was used to estimate a recession parameter (α), which was used to isolate baseflow from total streamflow. Results showed that: 1) annual precipitation exhibited significant decreasing trends (P < 0.05) with an average change of –1.81 mm/yr2. The precipitation deficit revealed that the start and end date of the extreme meteorological drought event was from August 1996 to May 2011, respectively, persisting for a total of 178 months (roughly 15 yr); 2) hydrological drought (including streamflow and baseflow) lagged behind meteorological drought while predictably persisting longer than extreme meteorological drought (i.e., precipitation); and 3) baseflow decreased dramatically under meteorological drought at both seasonal and annual scales, resulting in significantly decreasing trends during drought periods. Findings from this study confirmed that hydrological events caused by extreme meteorological drought can alter the magnitude and duration of baseflow and total streamflow, which will have an inevitable influence on aquatic ecosystems.
2021, 31(5): 877-887.
doi: 10.1007/s11769-021-1232-6
Abstract:
Biochar amendment is considered as an efficient practice for improving carbon storage in soils. However, to what extent that biochar application promotes organic carbon in saline-sodic soils remains poorly understood. By comparing soil organic carbon (SOC) contents change before and after biochar addition, we deciphered the driving factors or processes that control SOC change in response to biochar application. A limited increase in SOC was observed, about by 1.16%−12.80%, even when biochar was applied at the rate of 10% of bulk soil weight. Biochar application enhanced soil dissolved organic carbon (DOC) significantly by up to 67%. It was estimated that about 50% SOC was allocated to small macroaggregates (250−2000 μm, CPOC), and SOC in silt and clay-sized particles (< 53 μm) decreased obviously after biochar addition. Microbial biomass increased with biochar amendment, of which actinomycetes (ACT), fungus (FUN), protozoon (PRO), and bacteria with straight-chain saturated fatty acids (OB) increased remarkably. Multiple linear regression models implied that DOC was governed by ACT and soil N∶P ratio, while SOC mostly depended on CPOC. The principal component analysis and the partial least square path model (PLS-PM) indicated that biochar addition aggravated nitrogen limitation in saline-sodic soils, and effects of microorganisms on regulating SOC greatly depended on nitrogen bioavailability. Biochar application had vastly changed interactions between environmental factors and SOC in saline-sodic soils. Effects of nutrients on SOC shifted to great inhibition from strong stimulation after biochar addition, meanwhile, aggregation was the only factor presenting positive effects on SOC. How to eliminate nutrient limitation and better soil aggregation process should be considered in priority when biochar was used to improve SOC in saline-sodic soils.
Biochar amendment is considered as an efficient practice for improving carbon storage in soils. However, to what extent that biochar application promotes organic carbon in saline-sodic soils remains poorly understood. By comparing soil organic carbon (SOC) contents change before and after biochar addition, we deciphered the driving factors or processes that control SOC change in response to biochar application. A limited increase in SOC was observed, about by 1.16%−12.80%, even when biochar was applied at the rate of 10% of bulk soil weight. Biochar application enhanced soil dissolved organic carbon (DOC) significantly by up to 67%. It was estimated that about 50% SOC was allocated to small macroaggregates (250−2000 μm, CPOC), and SOC in silt and clay-sized particles (< 53 μm) decreased obviously after biochar addition. Microbial biomass increased with biochar amendment, of which actinomycetes (ACT), fungus (FUN), protozoon (PRO), and bacteria with straight-chain saturated fatty acids (OB) increased remarkably. Multiple linear regression models implied that DOC was governed by ACT and soil N∶P ratio, while SOC mostly depended on CPOC. The principal component analysis and the partial least square path model (PLS-PM) indicated that biochar addition aggravated nitrogen limitation in saline-sodic soils, and effects of microorganisms on regulating SOC greatly depended on nitrogen bioavailability. Biochar application had vastly changed interactions between environmental factors and SOC in saline-sodic soils. Effects of nutrients on SOC shifted to great inhibition from strong stimulation after biochar addition, meanwhile, aggregation was the only factor presenting positive effects on SOC. How to eliminate nutrient limitation and better soil aggregation process should be considered in priority when biochar was used to improve SOC in saline-sodic soils.
2021, 31(5): 888-899.
doi: 10.1007/s11769-021-1223-7
Abstract:
The Qinghai-Tibet Plateau (QTP) is the most unique region of human-land relations, and its main factor is population. By building a population and space dataset of the QTP at the township level from 1982 to 2017, this paper presents the pattern evolvement and regional distribution characteristics of township-level population in the QTP in detail for the first time. By using Geodetector method to analyze the influencing factors of township-level population change in the QTP, this paper provides scientific foundations for studying the Third Pole, ecological environment protection of the QTP, and human-land relations. The conclusions are as follows: 1) The population spatial distribution is not balanced at the township level, presents the regional differentiation characteristics of ‘dense in southeast and sparse in northwest’ along the ‘Qilian-Jilong Line’, and demonstrates the phenomenon of population center of gravity moving to the hinterland of the plateau at an accelerated speed; 2) The township-level population develops in a decentralized trend in general, and the cold- and hot-spot distribution of population has prominent spatial distribution characteristics. The population hot spots are concentrated in the surrounding areas of Xining, Golmud, Hotan and Lijiang; 3) The population of the QTP is increasing, and the inter-annual change of township population has a relatively stable regional regularity; 4) The level of per capita income is the leading factor in the change of township population, and its effect intensity is increasing continuously. The relative effect intensity of urbanization level and location conditions on population change has decreased significantly after 2000. The adaptability of living environment, such as topography and climate, has little influence on population change.
The Qinghai-Tibet Plateau (QTP) is the most unique region of human-land relations, and its main factor is population. By building a population and space dataset of the QTP at the township level from 1982 to 2017, this paper presents the pattern evolvement and regional distribution characteristics of township-level population in the QTP in detail for the first time. By using Geodetector method to analyze the influencing factors of township-level population change in the QTP, this paper provides scientific foundations for studying the Third Pole, ecological environment protection of the QTP, and human-land relations. The conclusions are as follows: 1) The population spatial distribution is not balanced at the township level, presents the regional differentiation characteristics of ‘dense in southeast and sparse in northwest’ along the ‘Qilian-Jilong Line’, and demonstrates the phenomenon of population center of gravity moving to the hinterland of the plateau at an accelerated speed; 2) The township-level population develops in a decentralized trend in general, and the cold- and hot-spot distribution of population has prominent spatial distribution characteristics. The population hot spots are concentrated in the surrounding areas of Xining, Golmud, Hotan and Lijiang; 3) The population of the QTP is increasing, and the inter-annual change of township population has a relatively stable regional regularity; 4) The level of per capita income is the leading factor in the change of township population, and its effect intensity is increasing continuously. The relative effect intensity of urbanization level and location conditions on population change has decreased significantly after 2000. The adaptability of living environment, such as topography and climate, has little influence on population change.
2021, 31(5): 900-914.
doi: 10.1007/s11769-021-1224-6
Abstract:
As an important step enhancing regional innovation, researches on collaborative innovation have attracted much more attention recently. One significant reason is that cities can get excessive benefits while they take collaborative innovation activities. Based on the theories of innovation geography, this paper takes the collaborative innovation of the Yangtze River Delta (YRD) Urban Agglomeration as a case study and measures the collaborative innovation capacity from innovation actors and innovation cities by adopting the catastrophe progression model. Then on this basis, the study depicts the spatial pattern and the benefit allocation of collaborative innovation by using the coupling collaborative degree model and benefit allocation model of collaborative innovation. The results show that: 1) The collaborative innovation capacity of cities in the Yangtze River Delta has strengthened largely, while the capacity still is not high enough. Cities with high collaborative innovation capacity are concentrated in Shanghai, the southern part of Jiangsu, and Hangzhou Bay, yet the cooperation of the universities-industries-research institutes need to improve. 2) The spatial pattern of collaborative innovation of the Yangtze River Delta presents several innovation circles, which are in Suzhou-Wuxi-Changzhou Metropolitan Circle, Nanjing Metropolitan Circle, Hangzhou Metropolitan Circle, Ningbo Metropolitan Circle, and Hefei Metropolitan Circle. Shanghai plays the role of the central city of collaborative innovation, while Suzhou, Nanjing, Hangzhou, Ningbo, and Hefei act as sub-central cities. 3) The benefit each city allocated from collaborative innovation activities has increased. However, the allocations of the benefit show that cities with higher innovation capacity have significant advantages in most cases, which lead to serious disparities in space.
As an important step enhancing regional innovation, researches on collaborative innovation have attracted much more attention recently. One significant reason is that cities can get excessive benefits while they take collaborative innovation activities. Based on the theories of innovation geography, this paper takes the collaborative innovation of the Yangtze River Delta (YRD) Urban Agglomeration as a case study and measures the collaborative innovation capacity from innovation actors and innovation cities by adopting the catastrophe progression model. Then on this basis, the study depicts the spatial pattern and the benefit allocation of collaborative innovation by using the coupling collaborative degree model and benefit allocation model of collaborative innovation. The results show that: 1) The collaborative innovation capacity of cities in the Yangtze River Delta has strengthened largely, while the capacity still is not high enough. Cities with high collaborative innovation capacity are concentrated in Shanghai, the southern part of Jiangsu, and Hangzhou Bay, yet the cooperation of the universities-industries-research institutes need to improve. 2) The spatial pattern of collaborative innovation of the Yangtze River Delta presents several innovation circles, which are in Suzhou-Wuxi-Changzhou Metropolitan Circle, Nanjing Metropolitan Circle, Hangzhou Metropolitan Circle, Ningbo Metropolitan Circle, and Hefei Metropolitan Circle. Shanghai plays the role of the central city of collaborative innovation, while Suzhou, Nanjing, Hangzhou, Ningbo, and Hefei act as sub-central cities. 3) The benefit each city allocated from collaborative innovation activities has increased. However, the allocations of the benefit show that cities with higher innovation capacity have significant advantages in most cases, which lead to serious disparities in space.
2021, 31(5): 915-930.
doi: 10.1007/s11769-021-1233-5
Abstract:
The value of the high-resolution data lies in the high-precision information discovery. The fine-detailed landform element extraction is thus the basis of high-fidelity application of the high-resolution digital elevation models (DEMs). However, the results of landform element extraction generated by classical methods might be ungrounded on high-resolution DEMs. This paper presents our research on using the aspect to reinforce the applicability and robustness of the classical approaches in landform element extraction. First, according to the research of pattern recognition, we assume that aspect-enhanced landform representation is robust to rotation, scaling and affine variance. To testify the role of aspect, we respectively integrated the aspect into three classical approaches: mean curvature-based fuzzy classification, elevation-based feature descriptor, and object-based segmentation. In the experiment, based on four types of high-resolution DEMs (1 m, 2 m, 4 m and 8 m), we compare each classical approaches and their corresponding aspect-enhanced approaches based on extracting the rims of two craters having different landforms, and the ridgelines and valleylines of a region covered by few vegetables and man-made buildings. In comparison to the results generated by curvature-based fuzzy classification, the aspect enhanced curvature-based fuzzy classification can effectively filter a number of noises outperforms the curvature-based one. Otherwise, the aspect-enhanced feature descriptor can detect more landform elements than the elevation-based feature descriptor. Moreover, the aspect-based segmentation can detect the main structure of landform, while the boundaries segmented by classical approaches are messing and meaningless. The systematic experiments on meter-level resolution DEMs proved that the aspect in topography could effectively to improve the classical method-system, including fuzzy-based classification, feature descriptors-based detection and object-based segmentation. The value of aspect is significantly great to be worthy of attentions in landform representation.
The value of the high-resolution data lies in the high-precision information discovery. The fine-detailed landform element extraction is thus the basis of high-fidelity application of the high-resolution digital elevation models (DEMs). However, the results of landform element extraction generated by classical methods might be ungrounded on high-resolution DEMs. This paper presents our research on using the aspect to reinforce the applicability and robustness of the classical approaches in landform element extraction. First, according to the research of pattern recognition, we assume that aspect-enhanced landform representation is robust to rotation, scaling and affine variance. To testify the role of aspect, we respectively integrated the aspect into three classical approaches: mean curvature-based fuzzy classification, elevation-based feature descriptor, and object-based segmentation. In the experiment, based on four types of high-resolution DEMs (1 m, 2 m, 4 m and 8 m), we compare each classical approaches and their corresponding aspect-enhanced approaches based on extracting the rims of two craters having different landforms, and the ridgelines and valleylines of a region covered by few vegetables and man-made buildings. In comparison to the results generated by curvature-based fuzzy classification, the aspect enhanced curvature-based fuzzy classification can effectively filter a number of noises outperforms the curvature-based one. Otherwise, the aspect-enhanced feature descriptor can detect more landform elements than the elevation-based feature descriptor. Moreover, the aspect-based segmentation can detect the main structure of landform, while the boundaries segmented by classical approaches are messing and meaningless. The systematic experiments on meter-level resolution DEMs proved that the aspect in topography could effectively to improve the classical method-system, including fuzzy-based classification, feature descriptors-based detection and object-based segmentation. The value of aspect is significantly great to be worthy of attentions in landform representation.
2021, 31(5): 931-950.
doi: 10.1007/s11769-021-1212-x
Abstract:
In recent years, O2O e-commerce, represented by online group-buying, has developed vigorously, which had significant impacts on urban commercial space. Zhengzhou City is a rising national central city in China, and its e-commerce development level is ahead, but relevant researches are rare. Therefore, the data of online retailers of Meituan.com was collected and combined with Baidu map and Baidu heat map data. Then, we adopted the methods such as spatial statistics and geodetector to explore the geography and determinants of O2O online retailers in Zhengzhou urban area. The main conclusions are 1) The spatial development of O2O online retailers is characterized by significant global high-value agglomeration. 2) The agglomeration areas of different types of O2O online retailers are different. Most of them are concentrated in the old urban area within the Third Ring Road of Zhengzhou City, forming five comprehensive agglomeration areas. 3) The areas with the high e-commerce development level are mainly concentrated in the northeast and southwest of the x-shaped region formed by the intersection of Lianyungang-Lanzhou and Beijing-Guangzhou railways. Erqi Square and Guomao 360 Plaza are at the highest development level, followed by Zhongyuan Wanda Plaza and Daxue Middle Road. The development level at other areas is relatively low. 4) Zhengzhou’s O2O commercial pattern is highly dependent on physical business. The population distribution, especially the population distribution during the nightlife period, plays a vital role in its spatial development, followed by accessibility. The influences of physical distance are slightly larger than that of time cost, but the difference between them is little. In addition, travelling costs have the least impact. This paper could provide certain references for urban commercial planning.
In recent years, O2O e-commerce, represented by online group-buying, has developed vigorously, which had significant impacts on urban commercial space. Zhengzhou City is a rising national central city in China, and its e-commerce development level is ahead, but relevant researches are rare. Therefore, the data of online retailers of Meituan.com was collected and combined with Baidu map and Baidu heat map data. Then, we adopted the methods such as spatial statistics and geodetector to explore the geography and determinants of O2O online retailers in Zhengzhou urban area. The main conclusions are 1) The spatial development of O2O online retailers is characterized by significant global high-value agglomeration. 2) The agglomeration areas of different types of O2O online retailers are different. Most of them are concentrated in the old urban area within the Third Ring Road of Zhengzhou City, forming five comprehensive agglomeration areas. 3) The areas with the high e-commerce development level are mainly concentrated in the northeast and southwest of the x-shaped region formed by the intersection of Lianyungang-Lanzhou and Beijing-Guangzhou railways. Erqi Square and Guomao 360 Plaza are at the highest development level, followed by Zhongyuan Wanda Plaza and Daxue Middle Road. The development level at other areas is relatively low. 4) Zhengzhou’s O2O commercial pattern is highly dependent on physical business. The population distribution, especially the population distribution during the nightlife period, plays a vital role in its spatial development, followed by accessibility. The influences of physical distance are slightly larger than that of time cost, but the difference between them is little. In addition, travelling costs have the least impact. This paper could provide certain references for urban commercial planning.
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