2020 Vol. 30, No. 5
Display Method:
2020, 30(5): 749-764.
doi: 10.1007/s11769-020-1147-7
Abstract:
Although the factors affecting rural-to-urban migration have been discussed and analyzed in detail, few studies have examined the spatiotemporal dynamic characteristics of rural migrants' employment and working-cities in the post-immigrate era, which is essential for the citizenization and social integration of new-type urbanization in China. This study uses survey data from rural migration laborers across the eastern, central, and western China to construct a comprehensive labor migration stability index, and compares the determinants of the migration stability of rural labor among cities and industries using Geodetector. The results are as follows:1) Compared with the midwestern cities, eastern cities have attracted younger and more skilled rural labor, and industries with higher technical content have higher migration stability among rural laborers. 2) Rural laborers more often adapt to changes by changing employment instead of changing working-cities. 3) The individual experiences of rural laborers and urban characteristics have significant impacts on the stability of migration, and family and societal guanxi (Chinese interpersonal relationships) enhance migration stability. 4) A unified labor market and convenient transportation have somewhat slowed industrial transfers and labor backflow. This study enhances our understanding of the roles of industrial transfer and new-type urbanization in shaping the labor geography landscape and provides policy implications for the promotion of people-oriented urbanization.
Although the factors affecting rural-to-urban migration have been discussed and analyzed in detail, few studies have examined the spatiotemporal dynamic characteristics of rural migrants' employment and working-cities in the post-immigrate era, which is essential for the citizenization and social integration of new-type urbanization in China. This study uses survey data from rural migration laborers across the eastern, central, and western China to construct a comprehensive labor migration stability index, and compares the determinants of the migration stability of rural labor among cities and industries using Geodetector. The results are as follows:1) Compared with the midwestern cities, eastern cities have attracted younger and more skilled rural labor, and industries with higher technical content have higher migration stability among rural laborers. 2) Rural laborers more often adapt to changes by changing employment instead of changing working-cities. 3) The individual experiences of rural laborers and urban characteristics have significant impacts on the stability of migration, and family and societal guanxi (Chinese interpersonal relationships) enhance migration stability. 4) A unified labor market and convenient transportation have somewhat slowed industrial transfers and labor backflow. This study enhances our understanding of the roles of industrial transfer and new-type urbanization in shaping the labor geography landscape and provides policy implications for the promotion of people-oriented urbanization.
2020, 30(5): 765-775.
doi: 10.1007/s11769-020-1148-6
Abstract:
In the 21st century, economic interdependence between countries has gradually become an important source of state power. Globalization and the rise of China's economy have had a significant impact on other economies around the world. China's economic influence is becoming more and more important. On the basis of the sensitivity dependence and vulnerability dependence of asymmetric interdependence theory, the economic spillover between countries is selected to construct a quantitative model to measure economic power. This paper analyzes the evolution of China's economic power both in time and space from 2000 to 2014. Four conclusions were drawn from the study:1) The spatial spillover effect of China's economy on other countries has been continuously growing since the beginning of the 21st century, which has brought about the rapid increase in China's economic power; 2) China's economic power has been significantly strengthened both in intensity and scope, having expanded from the surrounding countries to the whole world. In 2014, China had a high amount of economic power over 18 countries from the 41 main countries in the world, compared to 2 in 2000; 3) China's power in terms of sensitivity dependence takes on an evolutionary trend from point distribution to flaky growth, and it shows a process ‘from point to line’ from the aspect of spatial diffusion. Furthermore, China's power in terms of vulnerability dependence shows a trend that extends from the surrounding countries to European and South American countries; 4) comprehensively, China's power in terms of vulnerability dependence is higher than that of sensitivity dependence, and the spatial distribution pattern demonstrates a process from centralization to decentralization from 2000 to 2014.
In the 21st century, economic interdependence between countries has gradually become an important source of state power. Globalization and the rise of China's economy have had a significant impact on other economies around the world. China's economic influence is becoming more and more important. On the basis of the sensitivity dependence and vulnerability dependence of asymmetric interdependence theory, the economic spillover between countries is selected to construct a quantitative model to measure economic power. This paper analyzes the evolution of China's economic power both in time and space from 2000 to 2014. Four conclusions were drawn from the study:1) The spatial spillover effect of China's economy on other countries has been continuously growing since the beginning of the 21st century, which has brought about the rapid increase in China's economic power; 2) China's economic power has been significantly strengthened both in intensity and scope, having expanded from the surrounding countries to the whole world. In 2014, China had a high amount of economic power over 18 countries from the 41 main countries in the world, compared to 2 in 2000; 3) China's power in terms of sensitivity dependence takes on an evolutionary trend from point distribution to flaky growth, and it shows a process ‘from point to line’ from the aspect of spatial diffusion. Furthermore, China's power in terms of vulnerability dependence shows a trend that extends from the surrounding countries to European and South American countries; 4) comprehensively, China's power in terms of vulnerability dependence is higher than that of sensitivity dependence, and the spatial distribution pattern demonstrates a process from centralization to decentralization from 2000 to 2014.
2020, 30(5): 776-790.
doi: 10.1007/s11769-020-1145-9
Abstract:
Ecological civilisation construction is a strategy for regional sustainable development based on a regional system of human-land relations. The comprehensive measurement and regional differentiation in construction levels are the key issues of ecological civilisation construction. This study aims to build 35 index systems that coalesce on four aspects:ecological economic adjustment and operation, ecological and social development and progress, ecological resources and environmental security, and ecological institutional and cultural awareness. We measured and evaluated the level of ecological civilisation construction of 329 cities (prefecture-level cities, autonomous prefectures and leagues) in 2018 using a comprehensive evaluation system and a spatial autocorrelation method to assess spatial differences in the level of ecological civilisation construction across China. This approach takes ‘the humanities-economic geography’ comprehensive perspective and uses a GWR (geographically weighted regression) model to analyse 10 influencing factors. Results show that:1) the level of ecological construction can be divided into five types:higher, high, medium, low, and lower levels, according to the evaluation score. The five types are spindle-shaped in quantity and there is a significant imbalance in their spatial distribution, mainly trending from the southeast coast to the northwest. The land is decreasing, and the southern region is higher in level than the northern region. 2) The results of the spatial autocorrelation method show obvious spatial differences in ecological civilisation construction across China and that the level of ecological civilisation construction is positively autocorrelated. From east to west, the hot zone gradually transitions to a cold zone. A high-high type is mainly distributed in eastern coastal cities of China, and the number of high-low and low-high types are small. The low-low type is mainly distributed in the northwestern and northeastern regions. 3) The effect of influencing factors is heterogeneous in their spatial distribution, and the abundance of ecological resources is the most influential factor. According to the main influencing factors, each region should adhere to the principle of differentiation according to local conditions when choosing its ecological civilisation construction path and establishing an assessment mechanism. This study provides a scientific basis for enriching the regional level measurement of ecological civilisation construction, clarifying the current level of ecological civilisation construction in China, and implementing the regional differentiation path of ecological civilisation construction.
Ecological civilisation construction is a strategy for regional sustainable development based on a regional system of human-land relations. The comprehensive measurement and regional differentiation in construction levels are the key issues of ecological civilisation construction. This study aims to build 35 index systems that coalesce on four aspects:ecological economic adjustment and operation, ecological and social development and progress, ecological resources and environmental security, and ecological institutional and cultural awareness. We measured and evaluated the level of ecological civilisation construction of 329 cities (prefecture-level cities, autonomous prefectures and leagues) in 2018 using a comprehensive evaluation system and a spatial autocorrelation method to assess spatial differences in the level of ecological civilisation construction across China. This approach takes ‘the humanities-economic geography’ comprehensive perspective and uses a GWR (geographically weighted regression) model to analyse 10 influencing factors. Results show that:1) the level of ecological construction can be divided into five types:higher, high, medium, low, and lower levels, according to the evaluation score. The five types are spindle-shaped in quantity and there is a significant imbalance in their spatial distribution, mainly trending from the southeast coast to the northwest. The land is decreasing, and the southern region is higher in level than the northern region. 2) The results of the spatial autocorrelation method show obvious spatial differences in ecological civilisation construction across China and that the level of ecological civilisation construction is positively autocorrelated. From east to west, the hot zone gradually transitions to a cold zone. A high-high type is mainly distributed in eastern coastal cities of China, and the number of high-low and low-high types are small. The low-low type is mainly distributed in the northwestern and northeastern regions. 3) The effect of influencing factors is heterogeneous in their spatial distribution, and the abundance of ecological resources is the most influential factor. According to the main influencing factors, each region should adhere to the principle of differentiation according to local conditions when choosing its ecological civilisation construction path and establishing an assessment mechanism. This study provides a scientific basis for enriching the regional level measurement of ecological civilisation construction, clarifying the current level of ecological civilisation construction in China, and implementing the regional differentiation path of ecological civilisation construction.
2020, 30(5): 791-809.
doi: 10.1007/s11769-020-1149-5
Abstract:
Measuring the economic and social effects of the Northeast China Revitalization Strategy is critical to addressing regional sustainable development in China. To shed light on this issue, an integrated perspective was adopted that is combined with the difference-in-differences method to measure the effects of the strategy on economic growth and social development in Northeast China. The findings suggest that the strategy has significantly improved regional economic growth and per-capita income by increasing its gross domestic product (GDP) and GDP per capita by 25.70% and 46.00%, respectively. However, the strategy has significantly worsened the regional employment in the secondary industry of the region. In addition, the strategy has not significantly improved regional infrastructural road, education investment or social security, and has had no significant effect on mitigating regional disparity. In addition, the policy effects are highly heterogeneous across cities based on city size and characteristics. Therefore, there is no simple answer regarding whether the Northeast China Revitalization Strategy has reached its original goals from an integrated perspective. The next phase of the strategy should emphasize improving research and development (R&D) and human capital investments based on urban heterogeneity to prevent conservative path-dependency and the lock-in of outdated technologies.
Measuring the economic and social effects of the Northeast China Revitalization Strategy is critical to addressing regional sustainable development in China. To shed light on this issue, an integrated perspective was adopted that is combined with the difference-in-differences method to measure the effects of the strategy on economic growth and social development in Northeast China. The findings suggest that the strategy has significantly improved regional economic growth and per-capita income by increasing its gross domestic product (GDP) and GDP per capita by 25.70% and 46.00%, respectively. However, the strategy has significantly worsened the regional employment in the secondary industry of the region. In addition, the strategy has not significantly improved regional infrastructural road, education investment or social security, and has had no significant effect on mitigating regional disparity. In addition, the policy effects are highly heterogeneous across cities based on city size and characteristics. Therefore, there is no simple answer regarding whether the Northeast China Revitalization Strategy has reached its original goals from an integrated perspective. The next phase of the strategy should emphasize improving research and development (R&D) and human capital investments based on urban heterogeneity to prevent conservative path-dependency and the lock-in of outdated technologies.
2020, 30(5): 810-823.
doi: 10.1007/s11769-020-1150-z
Abstract:
Rapid urbanization has triggered large rural population floating into cities, which in turn affects rural human-land relationships. The actual human-land relationship involves the coupling level of a time point and dynamic change of a time interval. However, few studies have identified the rural human-land relationship from these two perspectives. This study combined static coupling analysis with a dynamic decoupling model to analyze the relationships between rural population and settlements from 2009 to 2018 in Jiangsu Province, China. Although the static coupling degree in Jiangsu Province was relatively high, the decoupling analysis found that the rural human-land relationship in most counties was uncoordinated. There were 11 combination types based on the coupling and decoupling relationships. The most common two types (accounting for 76.74%) were recession decoupling with high-level coupling and strong decoupling with high-level coupling. Although the majority of counties had a high-level coupling degree, an uncoordinated change in rural population and rural settlements was observed in these counties. Counties with relatively reasonable human-land relationships accounted for only 12.79% of the total. The combination features for each type were identified and differential policies were proposed for optimizing human-land relationship in rural areas. This study would contribute to our understanding of the multiple relationships between rural population and settlements involved in different patterns and processes, and expect to provide theoretical and methodological support for promoting rural revitalization and sustainable development in practice.
Rapid urbanization has triggered large rural population floating into cities, which in turn affects rural human-land relationships. The actual human-land relationship involves the coupling level of a time point and dynamic change of a time interval. However, few studies have identified the rural human-land relationship from these two perspectives. This study combined static coupling analysis with a dynamic decoupling model to analyze the relationships between rural population and settlements from 2009 to 2018 in Jiangsu Province, China. Although the static coupling degree in Jiangsu Province was relatively high, the decoupling analysis found that the rural human-land relationship in most counties was uncoordinated. There were 11 combination types based on the coupling and decoupling relationships. The most common two types (accounting for 76.74%) were recession decoupling with high-level coupling and strong decoupling with high-level coupling. Although the majority of counties had a high-level coupling degree, an uncoordinated change in rural population and rural settlements was observed in these counties. Counties with relatively reasonable human-land relationships accounted for only 12.79% of the total. The combination features for each type were identified and differential policies were proposed for optimizing human-land relationship in rural areas. This study would contribute to our understanding of the multiple relationships between rural population and settlements involved in different patterns and processes, and expect to provide theoretical and methodological support for promoting rural revitalization and sustainable development in practice.
2020, 30(5): 824-838.
doi: 10.1007/s11769-020-1128-x
Abstract:
Following the trends of Chinese rural transformation development, and the sustainable development goals for resources and environment, reasonable arranging the potential development space and the ecological space, so as to optimize the distributions of rural settlement would be the key challenge for rural areas in ecologically fragile regions. From the perspective of maintaining regional ecological security, this paper takes Da'an City, a typical ecological fragile region in Jilin Province, as the case area, constructing the comprehensive ecological security pattern (ESP) on basis of landscape ecology, and applying the landscape pattern indexes to quantitative analysis the spatial distribution characteristics of rural settlements. Then, different optimization directions and management strategies are put forward for rural settlements in each secure zone under the comprehensive ESP. The experimental results showed that 1) the area of the low security zone, the general security zone, the moderate security zone and the extreme security zone was 1570.18 km2, 1463.36 km2, 1215.80 km2 and 629.77 km2, representing 32.18%, 29.99%, 24.92% and 12.91% of the total area of the target area, respectively. 2) The rural settlements in Da'an City were characterized by a high degree of fragmentation with a large number of small-scale patches. 3) The area of rural settlements in the ecological relocation zone, the in situ remediation zone, the limited development zone and the key development zone was 22.80 km2, 42.31 km2, 36.28 km2 and 19.40 km2, accounting for 18.88%, 35.03%, 30.04% and 16.06% of the total area of rural settlements, respectively. Then, different measures were proposed for settlements in different optimization zones in order to scientifically plan important ecological space, production space and living space in rural areas. This paper aims to provide fundamental support for rural settlements based on redistribution from the perspective of landscape ecology and provide insights for rural planning and rural habitat environmental improvement.
Following the trends of Chinese rural transformation development, and the sustainable development goals for resources and environment, reasonable arranging the potential development space and the ecological space, so as to optimize the distributions of rural settlement would be the key challenge for rural areas in ecologically fragile regions. From the perspective of maintaining regional ecological security, this paper takes Da'an City, a typical ecological fragile region in Jilin Province, as the case area, constructing the comprehensive ecological security pattern (ESP) on basis of landscape ecology, and applying the landscape pattern indexes to quantitative analysis the spatial distribution characteristics of rural settlements. Then, different optimization directions and management strategies are put forward for rural settlements in each secure zone under the comprehensive ESP. The experimental results showed that 1) the area of the low security zone, the general security zone, the moderate security zone and the extreme security zone was 1570.18 km2, 1463.36 km2, 1215.80 km2 and 629.77 km2, representing 32.18%, 29.99%, 24.92% and 12.91% of the total area of the target area, respectively. 2) The rural settlements in Da'an City were characterized by a high degree of fragmentation with a large number of small-scale patches. 3) The area of rural settlements in the ecological relocation zone, the in situ remediation zone, the limited development zone and the key development zone was 22.80 km2, 42.31 km2, 36.28 km2 and 19.40 km2, accounting for 18.88%, 35.03%, 30.04% and 16.06% of the total area of rural settlements, respectively. Then, different measures were proposed for settlements in different optimization zones in order to scientifically plan important ecological space, production space and living space in rural areas. This paper aims to provide fundamental support for rural settlements based on redistribution from the perspective of landscape ecology and provide insights for rural planning and rural habitat environmental improvement.
2020, 30(5): 839-854.
doi: 10.1007/s11769-020-1144-x
Abstract:
The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative (BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy (MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.
The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative (BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy (MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.
2020, 30(5): 855-875.
doi: 10.1007/s11769-020-1151-y
Abstract:
Land surface hydrothermal conditions (LSHCs) reflect land surface moisture and heat conditions, and play an important role in energy and water cycles in soil-plant-atmosphere continuum. Based on comparison of four evaluation methods (namely, the classic statistical method, geostatistical method, information theory method, and fractal method), this study proposed a new scheme for evaluating the spatial heterogeneity of LSHCs. This scheme incorporates diverse remotely sensed surface parameters, e.g., leaf area index-LAI, the normalized difference vegetation index-NDVI, net radiation-Rn, and land surface temperature-LST. The LSHCs can be classified into three categories, namely homogeneous, moderately heterogeneous and highly heterogeneous based on the remotely sensed LAI data with a 30 m spatial resolution and the combination of normalized information entropy (S') and coefficient of variation (CV). Based on the evaluation scheme, the spatial heterogeneity of land surface hydrothermal conditions at six typical flux observation stations in the Heihe River Basin during the vegetation growing season were evaluated. The evaluation results were consistent with the land surface type characteristics exhibited by Google Earth imagery and spatial heterogeneity assessed by high resolution remote sensing evapotranspiration data. Impact factors such as precipitation and irrigation events, spatial resolutions of remote sensing data, heterogeneity in the vertical direction, topography and sparse vegetation could also affect the evaluation results. For instance, short-term changes (precipitation and irrigation events) in the spatial heterogeneity of LSHCs can be diagnosed by energy factors, while long-term changes can be indicated by vegetation factors. The spatial heterogeneity of LSHCs decreases when decreasing the spatial resolution of remote sensing data. The proposed evaluation scheme would be useful for the quantification of spatial heterogeneity of LSHCs over flux observation stations toward the global scale, and also contribute to the improvement of the accuracy of estimation and validation for remotely sensed (or model simulated) evapotranspiration.
Land surface hydrothermal conditions (LSHCs) reflect land surface moisture and heat conditions, and play an important role in energy and water cycles in soil-plant-atmosphere continuum. Based on comparison of four evaluation methods (namely, the classic statistical method, geostatistical method, information theory method, and fractal method), this study proposed a new scheme for evaluating the spatial heterogeneity of LSHCs. This scheme incorporates diverse remotely sensed surface parameters, e.g., leaf area index-LAI, the normalized difference vegetation index-NDVI, net radiation-Rn, and land surface temperature-LST. The LSHCs can be classified into three categories, namely homogeneous, moderately heterogeneous and highly heterogeneous based on the remotely sensed LAI data with a 30 m spatial resolution and the combination of normalized information entropy (S') and coefficient of variation (CV). Based on the evaluation scheme, the spatial heterogeneity of land surface hydrothermal conditions at six typical flux observation stations in the Heihe River Basin during the vegetation growing season were evaluated. The evaluation results were consistent with the land surface type characteristics exhibited by Google Earth imagery and spatial heterogeneity assessed by high resolution remote sensing evapotranspiration data. Impact factors such as precipitation and irrigation events, spatial resolutions of remote sensing data, heterogeneity in the vertical direction, topography and sparse vegetation could also affect the evaluation results. For instance, short-term changes (precipitation and irrigation events) in the spatial heterogeneity of LSHCs can be diagnosed by energy factors, while long-term changes can be indicated by vegetation factors. The spatial heterogeneity of LSHCs decreases when decreasing the spatial resolution of remote sensing data. The proposed evaluation scheme would be useful for the quantification of spatial heterogeneity of LSHCs over flux observation stations toward the global scale, and also contribute to the improvement of the accuracy of estimation and validation for remotely sensed (or model simulated) evapotranspiration.
2020, 30(5): 876-888.
doi: 10.1007/s11769-020-1152-x
Abstract:
As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth's surface energy budget (SEB). Since the Sanjiang Plain has been severely affected by human activities (e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite (GLASS) broadband surface albedo product. The results showed that:1) an increasing annual trend (+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend (+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.
As a key parameter for indicating the fraction of surface-reflected solar incident radiation, land surface albedo plays an important role in the Earth's surface energy budget (SEB). Since the Sanjiang Plain has been severely affected by human activities (e.g., reclamation and shrinking of wetlands), it is important to assess the spatiotemporal variations of surface albedo in this region using a long-term remote sensing dataset. In order to investigate the surface albedo climatology, trends, and mechanisms of change, we evaluated the surface albedo variations in the Sanjiang Plain, China from 1982 to 2015 using the Global LAnd Surface Satellite (GLASS) broadband surface albedo product. The results showed that:1) an increasing annual trend (+0.000 58/yr) of surface albedo was discovered in the Sanjiang Plain based on the GLASS albedo dataset, with a much stronger increasing trend (+0.001 26/yr) occurring during the winter. Most of the increasing trends occurred over the cultivated land, unused land, and land use conversion types located in the northeastern Sanjiang Plain. 2) The increasing trend of land surface albedo in Sanjiang Plain can be largely explained by the changes of both snow cover extent and land use. The surface albedo in winter is highly correlated with the snow cover extent in the Sanjiang Plain, and the increasing trend of surface albedo can be further enhanced by the land use changes.
2020, 30(5): 889-899.
doi: 10.1007/s11769-020-1153-9
Abstract:
More and more ports appeared along China's coastline, which destroyed natural coastline and coastal landscape. Some of them are inefficiency operations. It is important to evaluate operational efficiency of ports to reveal their position in regional competitive environment. In this study, high spatial resolution satellite remote sensing images were used to monitor ship number and plane area. The port-use prosperity index (PUI) was subsequently proposed to quantitatively describe port-use business and reveal port-use efficiency. The PUI was applied to six ports around the Bohai Sea, China. The number, scale, and plane of ships docked in these ports were easily monitored by the high spatial resolution satellite remote sensing images, and the PUI was calculated using a ship's total plane area and length of docked coastline. The PUI is an objective and practical index for evaluating port-use efficiency. It can be used to compare differences in port use and indicate temporal port-use dynamics. The PUI values of Jingtang and Tianjin Ports were the highest (17.75 and 14.14, respectively), whereas that of Yantai Port was the lowest (8.31). The PUI values of the remaining ports were 9.0-10.70. A linear relationship existed between port throughput and PUI in the studied ports. This can forecast port throughput by monitoring and calculating PUI based on high spatial resolution satellite remote sensing images.
More and more ports appeared along China's coastline, which destroyed natural coastline and coastal landscape. Some of them are inefficiency operations. It is important to evaluate operational efficiency of ports to reveal their position in regional competitive environment. In this study, high spatial resolution satellite remote sensing images were used to monitor ship number and plane area. The port-use prosperity index (PUI) was subsequently proposed to quantitatively describe port-use business and reveal port-use efficiency. The PUI was applied to six ports around the Bohai Sea, China. The number, scale, and plane of ships docked in these ports were easily monitored by the high spatial resolution satellite remote sensing images, and the PUI was calculated using a ship's total plane area and length of docked coastline. The PUI is an objective and practical index for evaluating port-use efficiency. It can be used to compare differences in port use and indicate temporal port-use dynamics. The PUI values of Jingtang and Tianjin Ports were the highest (17.75 and 14.14, respectively), whereas that of Yantai Port was the lowest (8.31). The PUI values of the remaining ports were 9.0-10.70. A linear relationship existed between port throughput and PUI in the studied ports. This can forecast port throughput by monitoring and calculating PUI based on high spatial resolution satellite remote sensing images.
2020, 30(5): 900-920.
doi: 10.1007/s11769-020-1143-y
Abstract:
Downstream changes in channel morphology and flow over the ephemeral Dwarkeswar River in the western part of the Bengal Basin, eastren India were investigated. The river stretches from the Proterozoic Granite Gneiss Complex to the recent Holocene alluvium, forming three distinctive geomorphological regions across the river basin:the pediplane and upper and lower alluvial areas. Sixty cross-sections from throughout the main trunk stream were surveyed and the bankfull width, depth, cross-sectional area, and maximum depth were measured. Sediment samples from each location were studied and the flow velocity, stream power, Manning's roughness coefficient, and shear stress were estimated. The results show that the bankfull channel cross-section area, width, width-to-depth ratio, and channel capacity increased between the beginning and middle of the river. Thereafter, the size of the river started to decrease in the lower alluvial area. This was characterized by gentle gradients, cohesive bank materials with grass cover, and channel switching. Within the lower part of the river, the channel capacity was observed to diminish as the drainage area increased. This increased the bankfull flow frequency and accelerated large floodwater losses in the floodplain via overbank flows and floodways.
Downstream changes in channel morphology and flow over the ephemeral Dwarkeswar River in the western part of the Bengal Basin, eastren India were investigated. The river stretches from the Proterozoic Granite Gneiss Complex to the recent Holocene alluvium, forming three distinctive geomorphological regions across the river basin:the pediplane and upper and lower alluvial areas. Sixty cross-sections from throughout the main trunk stream were surveyed and the bankfull width, depth, cross-sectional area, and maximum depth were measured. Sediment samples from each location were studied and the flow velocity, stream power, Manning's roughness coefficient, and shear stress were estimated. The results show that the bankfull channel cross-section area, width, width-to-depth ratio, and channel capacity increased between the beginning and middle of the river. Thereafter, the size of the river started to decrease in the lower alluvial area. This was characterized by gentle gradients, cohesive bank materials with grass cover, and channel switching. Within the lower part of the river, the channel capacity was observed to diminish as the drainage area increased. This increased the bankfull flow frequency and accelerated large floodwater losses in the floodplain via overbank flows and floodways.
2020, 30(5): 921-933.
doi: 10.1007/s11769-020-1154-8
Abstract:
Domestic burning emits large amounts of pollutants into the ambient air due to incomplete and inefficient combustion, with significant impacts on indoor air quality and human health. Northeast China is one of the major contributors to domestic burning emissions in China; however, the high-resolution emissions inventories of domestic biomass and coal burning in Northeast China are lacked, which are needed to estimate the extent of its impact. In this study, we established a town-level emissions inventory of gaseous pollutants and particulate matter (PM) from domestic biomass and coal burning, based on per household consumption in each town in rural region of Northeast China. The results revealed that biomass burning was the major domestic burning source over the region in 2016. Domestic biomass burning is the major contributor to PM and volatile organic compounds (VOCs) emissions, while coal burning is the major contributor to SO2 emissions. High emissions intensities were concentrated around the cities of Harbin, Suihua, Changchun, Qiqihar, and Chifeng, each with emissions intensity for PM2.5 and VOCs of more than 2000 Mg per 27 km×27 km grid cell. Additionally, there are three burning peaks (6-7 am, 12 pm and 4-7 pm) during both the heating (from October to April) and non-heating seasons (from May to September), due to cooking and heating. The burning peaks in the non-heating season were more notable than those in the heating season. These results suggest that the government should pay more attention to domestic biomass and coal burning in rural areas, in order to reduce pollutant emissions and control regional haze during the heating season.
Domestic burning emits large amounts of pollutants into the ambient air due to incomplete and inefficient combustion, with significant impacts on indoor air quality and human health. Northeast China is one of the major contributors to domestic burning emissions in China; however, the high-resolution emissions inventories of domestic biomass and coal burning in Northeast China are lacked, which are needed to estimate the extent of its impact. In this study, we established a town-level emissions inventory of gaseous pollutants and particulate matter (PM) from domestic biomass and coal burning, based on per household consumption in each town in rural region of Northeast China. The results revealed that biomass burning was the major domestic burning source over the region in 2016. Domestic biomass burning is the major contributor to PM and volatile organic compounds (VOCs) emissions, while coal burning is the major contributor to SO2 emissions. High emissions intensities were concentrated around the cities of Harbin, Suihua, Changchun, Qiqihar, and Chifeng, each with emissions intensity for PM2.5 and VOCs of more than 2000 Mg per 27 km×27 km grid cell. Additionally, there are three burning peaks (6-7 am, 12 pm and 4-7 pm) during both the heating (from October to April) and non-heating seasons (from May to September), due to cooking and heating. The burning peaks in the non-heating season were more notable than those in the heating season. These results suggest that the government should pay more attention to domestic biomass and coal burning in rural areas, in order to reduce pollutant emissions and control regional haze during the heating season.
2020, 30(5): 934-946.
doi: 10.1007/s11769-020-1155-7
Abstract:
Soil carbon (C), nitrogen (N) and phosphorus (P) concentrations and stoichiometries can be used to evaluate the success indicators to the effects of wetland restoration and reflect ecosystem function. Restoration of inland soda saline-alkali wetlands is widespread, however, the soil nutrition changes that follow restoration are unclear. We quantified the recovery trajectories of soil physicochemical properties, including soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) pools, for a chronosequence of three restored wetlands (7 yr, 12 yr and 21 yr) and compared these properties to those of degraded and natural wetlands in the western Songnen Plain, Northeast China. Wetland degradation lead to the loss of soil nutrients. Relative to natural wetlands, the mean reductions of in SOC, TN, and TP concentrations were 89.6%, 65.5% and 52.5%, respectively. Nutrients recovered as years passed after restoration. The SOC, TN, and TP concentrations increased by 2.36 times, 1.15 times, and 0.83 times, respectively in degraded wetlands that had been restored for 21 yr, but remained 29.2%, 17.3%, and 12.8% lower, respectively, than those in natural wetlands. The soil C:N (RCN), C:P (RCP), and N:P (RNP) ratios increased from 5.92 to 8.81, 45.36 to 79.19, and 7.67 to 8.71, respectively in the wetland that had been restored for 12 yr. These results were similar to those from the natural wetland and the wetland that had been restored for 21 yr (P > 0.05). Soil nutrients changes occurred mainly in the upper layers (≤ 30 cm), and no significant differences were found in deeper soils (> 30 cm). Based on this, we inferred that it would take at least 34 yr for SOC, TN, and TP concentrations and 12 yr for RCN, RCP, and RNP in the top soils of degraded wetlands to recover to levels of natural wetlands. Soil salinity negatively influenced SOC (r=-0.704, P < 0.01), TN (r=-0.722, P < 0.01), and TP (r=-0.882, P < 0.01) concentrations during wetland restoration, which indicates that reducing salinity is beneficial to SOC, TN, and TP recovery. Moreover, plants were an important source of soil nutrients and vegetation restoration was conducive to soil nutrient accumulation. In brief, wetland restoration increased the accumulation of soil biogenic elements, which indicated that positive ecosystem functions changes had occurred.
Soil carbon (C), nitrogen (N) and phosphorus (P) concentrations and stoichiometries can be used to evaluate the success indicators to the effects of wetland restoration and reflect ecosystem function. Restoration of inland soda saline-alkali wetlands is widespread, however, the soil nutrition changes that follow restoration are unclear. We quantified the recovery trajectories of soil physicochemical properties, including soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) pools, for a chronosequence of three restored wetlands (7 yr, 12 yr and 21 yr) and compared these properties to those of degraded and natural wetlands in the western Songnen Plain, Northeast China. Wetland degradation lead to the loss of soil nutrients. Relative to natural wetlands, the mean reductions of in SOC, TN, and TP concentrations were 89.6%, 65.5% and 52.5%, respectively. Nutrients recovered as years passed after restoration. The SOC, TN, and TP concentrations increased by 2.36 times, 1.15 times, and 0.83 times, respectively in degraded wetlands that had been restored for 21 yr, but remained 29.2%, 17.3%, and 12.8% lower, respectively, than those in natural wetlands. The soil C:N (RCN), C:P (RCP), and N:P (RNP) ratios increased from 5.92 to 8.81, 45.36 to 79.19, and 7.67 to 8.71, respectively in the wetland that had been restored for 12 yr. These results were similar to those from the natural wetland and the wetland that had been restored for 21 yr (P > 0.05). Soil nutrients changes occurred mainly in the upper layers (≤ 30 cm), and no significant differences were found in deeper soils (> 30 cm). Based on this, we inferred that it would take at least 34 yr for SOC, TN, and TP concentrations and 12 yr for RCN, RCP, and RNP in the top soils of degraded wetlands to recover to levels of natural wetlands. Soil salinity negatively influenced SOC (r=-0.704, P < 0.01), TN (r=-0.722, P < 0.01), and TP (r=-0.882, P < 0.01) concentrations during wetland restoration, which indicates that reducing salinity is beneficial to SOC, TN, and TP recovery. Moreover, plants were an important source of soil nutrients and vegetation restoration was conducive to soil nutrient accumulation. In brief, wetland restoration increased the accumulation of soil biogenic elements, which indicated that positive ecosystem functions changes had occurred.
Email
RSS