2022年 第32卷 第1期
2022, 32(1): 1-15.
doi: 10.1007/s11769-022-1255-7
摘要:
The relationship between urbanization and economic development has become a hot topic in the scientific community due to its great practical significance, and economic and social value. However, this relationship continues to change dynamically. In the new stage of urbanization, it is urgent to reveal the causal relationship quantitatively and diagnose the future direction systematically. Based on this, this paper calculates the contribution rate of China’s urbanization to economic development from 1978 to 2019 and uses the panel data cointegration test method to explore the causal relationship between urbanization and economic development in China. The study has three principal results. First, the contribution rate of urbanization to economic growth has maintained the overall growth trend from 1978 to 2019, but the growth rate of urbanization’s contribution to economic growth has been relatively low since 2012. It is an important reason that the real estate sector has moved into a new stage of transformation. Second, the cointegration test shows that economic development is a significant factor in advancing urbanization and the urbanization is the product of economic development. Urbanization has a positive feedback effect on economic development, but this effect does not pass the 5% significance level test. The impulse response function shows that the impact of urbanization on economic development is relatively small and stable, indicating that it is limited that the boost of economic development by land-centered urbanization. Third, China’s urbanization and economic development have both shown rapid growth for some time, but their relationship is still the low level of coordination, which has also led to a downward trend in the contribution of new-type, people-oriented urbanization to economic growth in recent years. In the future, China’s urbanization and economy need to maintain relatively medium-low speed growth in the medium-long term, and we should boost the coordinated development of urbanization and economy from low level to high level.
The relationship between urbanization and economic development has become a hot topic in the scientific community due to its great practical significance, and economic and social value. However, this relationship continues to change dynamically. In the new stage of urbanization, it is urgent to reveal the causal relationship quantitatively and diagnose the future direction systematically. Based on this, this paper calculates the contribution rate of China’s urbanization to economic development from 1978 to 2019 and uses the panel data cointegration test method to explore the causal relationship between urbanization and economic development in China. The study has three principal results. First, the contribution rate of urbanization to economic growth has maintained the overall growth trend from 1978 to 2019, but the growth rate of urbanization’s contribution to economic growth has been relatively low since 2012. It is an important reason that the real estate sector has moved into a new stage of transformation. Second, the cointegration test shows that economic development is a significant factor in advancing urbanization and the urbanization is the product of economic development. Urbanization has a positive feedback effect on economic development, but this effect does not pass the 5% significance level test. The impulse response function shows that the impact of urbanization on economic development is relatively small and stable, indicating that it is limited that the boost of economic development by land-centered urbanization. Third, China’s urbanization and economic development have both shown rapid growth for some time, but their relationship is still the low level of coordination, which has also led to a downward trend in the contribution of new-type, people-oriented urbanization to economic growth in recent years. In the future, China’s urbanization and economy need to maintain relatively medium-low speed growth in the medium-long term, and we should boost the coordinated development of urbanization and economy from low level to high level.
2022, 32(1): 31-48.
doi: 10.1007/s11769-022-1257-5
摘要:
The high environmental pollution load caused by the massive pollutant emissions and the accumulation of endogenous and cross-regional pollution has become an important obstacle to the current ecological civilization construction in the Yangtze River Economic Belt (YREB) in China. Taking the YREB as an example, by using four environmental pollutant emission indicators, including chemical oxygen demand (COD), ammonia nitrogen (NH3-N), sulfur dioxide (SO2), and nitrogen oxides (NOx), this paper established an environmental pollution load index (EPLI) based on the entropy-based measurement. Moreover, the Spatial Durbin Model was used to quantitatively analyze the drivers and spatial effects of environmental pollution load. Finally, specific scientific references were provided for formulating environmental regulations of pollution source control in the YREB. The results showed that: 1) During 2011–2015, the EPLI in the YREB was reduced significantly and the environmental pollution load increased from upstream to downstream. Among them, the pollution load levels in the Upper Mainstream subbasin, Taihu Lake subbasin, and Lower Mainstream subbasin were the most prominent. 2) The environmental pollution load situation in the YREB was generally stable and partially improved. High load level areas were mainly concentrated in the Yangtze River Delta Region and the provincial borders in upstream, midstream, and downstream areas. The high load level areas already formed in Chengdu and Chongqing were also the key regulatory points in the future. 3) The degree of local environmental pollution load was apparently affected by the adjacent cities. The population size, industrialization level, and the fiscal decentralization not only drove the increase of the local environmental pollution load level, but also affected the adjacent areas through the spatial spillover effects. The land development intensity mainly drove the increase in the local EPLI in the YREB. While factors such as economic development level and agricultural economic share could only act on the environmental pollution load process in adjacent cities. 4) According to the differentiation characteristics of drivers of each city, the YREB was divided into seven zones based on k-medoids cluster method, and targeted zoning control policy recommendations for alleviating environmental pollution load in the YREB were proposed.
The high environmental pollution load caused by the massive pollutant emissions and the accumulation of endogenous and cross-regional pollution has become an important obstacle to the current ecological civilization construction in the Yangtze River Economic Belt (YREB) in China. Taking the YREB as an example, by using four environmental pollutant emission indicators, including chemical oxygen demand (COD), ammonia nitrogen (NH3-N), sulfur dioxide (SO2), and nitrogen oxides (NOx), this paper established an environmental pollution load index (EPLI) based on the entropy-based measurement. Moreover, the Spatial Durbin Model was used to quantitatively analyze the drivers and spatial effects of environmental pollution load. Finally, specific scientific references were provided for formulating environmental regulations of pollution source control in the YREB. The results showed that: 1) During 2011–2015, the EPLI in the YREB was reduced significantly and the environmental pollution load increased from upstream to downstream. Among them, the pollution load levels in the Upper Mainstream subbasin, Taihu Lake subbasin, and Lower Mainstream subbasin were the most prominent. 2) The environmental pollution load situation in the YREB was generally stable and partially improved. High load level areas were mainly concentrated in the Yangtze River Delta Region and the provincial borders in upstream, midstream, and downstream areas. The high load level areas already formed in Chengdu and Chongqing were also the key regulatory points in the future. 3) The degree of local environmental pollution load was apparently affected by the adjacent cities. The population size, industrialization level, and the fiscal decentralization not only drove the increase of the local environmental pollution load level, but also affected the adjacent areas through the spatial spillover effects. The land development intensity mainly drove the increase in the local EPLI in the YREB. While factors such as economic development level and agricultural economic share could only act on the environmental pollution load process in adjacent cities. 4) According to the differentiation characteristics of drivers of each city, the YREB was divided into seven zones based on k-medoids cluster method, and targeted zoning control policy recommendations for alleviating environmental pollution load in the YREB were proposed.
2022, 32(1): 49-63.
doi: 10.1007/s11769-022-1258-4
摘要:
Although the development of energy and mineral resources strongly supports China’s rapid industrialization and urbanization, it has led to a series of ecological and environmental problems. Strengthening the spatial regulation considering the ecological and environmental protection on energy and mineral resource development areas is an important aspect of realizing China’s sustainable development. In this study, we mapped, categorized, and analyzed the ecological cumulative effects of the Chinese 134 prefectural mining units based on the pressure-state-response model, which is demonstrated as impact of mining activities on ecological environment, ecological environmental fragility, and ecological function. This investigation developed a stress zoning typology of the mining units based on scores of three dimensions of the ecological cumulative effects and classified 134 prefectural mining units into eight types of stress zones. A series of regulation and policy suggestions have been proposed to different types of zones from three aspects: space control, intensity control, and development mode control. The application of this evaluation and spatial zoning system will contribute to the refined spatial management of China’s mining areas.
Although the development of energy and mineral resources strongly supports China’s rapid industrialization and urbanization, it has led to a series of ecological and environmental problems. Strengthening the spatial regulation considering the ecological and environmental protection on energy and mineral resource development areas is an important aspect of realizing China’s sustainable development. In this study, we mapped, categorized, and analyzed the ecological cumulative effects of the Chinese 134 prefectural mining units based on the pressure-state-response model, which is demonstrated as impact of mining activities on ecological environment, ecological environmental fragility, and ecological function. This investigation developed a stress zoning typology of the mining units based on scores of three dimensions of the ecological cumulative effects and classified 134 prefectural mining units into eight types of stress zones. A series of regulation and policy suggestions have been proposed to different types of zones from three aspects: space control, intensity control, and development mode control. The application of this evaluation and spatial zoning system will contribute to the refined spatial management of China’s mining areas.
2022, 32(1): 79-92.
doi: 10.1007/s11769-021-1251-3
摘要:
Urbanization, especially urban land expansion, has a profound influence on the urban thermal environment. Cities in Northeast China face remarkably uneven development and environmental issues, and thus it is necessary to strengthen the diagnosis of thermal environmental pressure brought by urbanization. In this study, multi remote sensing imageries and statistical approaches, involving piecewise linear regression (PLR), were used to explore urban expansion and its effects on the thermal environment of Changchun City in Jilin Province, China. Results show that Changchun experienced rapid urban expansion from 2000 to 2020, with urban built-up areas increasing from 171.77 to 525.14 km2. The area of the city’s urban heat island (UHI) increased dramatically, during both day and night. Using PLR, a positive linear correlation of built-up density with land surface temperature (LST) was detected, with critical breakpoints of 70% – 80% during the daytime and 40% – 50% at nighttime. Above the thresholds, the magnitude of LST in response to built-up density significantly increased with intensifying urbanization, especially for nighttime LST. An analysis of the relative frequency distributions (RFDs) of LST reveals that rapid urbanization resulted in a significant increase of mean LST in newly urbanized areas, but had weak effects on daytime LST change in existing urban area. Urban expansion also contributed to a constant decrease of spatial heterogeneity of LST in existing urban area, especially at daytime. However, in newly urbanized areas, the spatial heterogeneity of LST was decreased during the daytime but increased at nighttime due to urbanization.
Urbanization, especially urban land expansion, has a profound influence on the urban thermal environment. Cities in Northeast China face remarkably uneven development and environmental issues, and thus it is necessary to strengthen the diagnosis of thermal environmental pressure brought by urbanization. In this study, multi remote sensing imageries and statistical approaches, involving piecewise linear regression (PLR), were used to explore urban expansion and its effects on the thermal environment of Changchun City in Jilin Province, China. Results show that Changchun experienced rapid urban expansion from 2000 to 2020, with urban built-up areas increasing from 171.77 to 525.14 km2. The area of the city’s urban heat island (UHI) increased dramatically, during both day and night. Using PLR, a positive linear correlation of built-up density with land surface temperature (LST) was detected, with critical breakpoints of 70% – 80% during the daytime and 40% – 50% at nighttime. Above the thresholds, the magnitude of LST in response to built-up density significantly increased with intensifying urbanization, especially for nighttime LST. An analysis of the relative frequency distributions (RFDs) of LST reveals that rapid urbanization resulted in a significant increase of mean LST in newly urbanized areas, but had weak effects on daytime LST change in existing urban area. Urban expansion also contributed to a constant decrease of spatial heterogeneity of LST in existing urban area, especially at daytime. However, in newly urbanized areas, the spatial heterogeneity of LST was decreased during the daytime but increased at nighttime due to urbanization.
2022, 32(1): 93-109.
doi: 10.1007/s11769-022-1259-3
摘要:
Eco-geographical regionalization involves dividing land into regions by considering both intra-regional consistency and inter-regional disparity and is based on the pattern of differentiation of eco-geographical elements. Owing to the complexity of the land surface, and the limitation of data and appropriate methods, regions in China have hitherto been mapped manually, meaning that the process of mapping was non-repeatable. To make the regionalization technique repeatable, this study aimed to extract and quantify the expert knowledge of regionalization using an automated method. The rough set method was adopted to extract rules of regionalization based on the existing eco-geographical regionalization map of China, as well as its corresponding meteorological and geological datasets. Then, the rules for regionalization were obtained hierarchically for each natural domain, each temperature zone, and each humidity region. Owing to differences in zonal differentiation, the rule extraction sequence for the eastern monsoon zone and Tibetan Alpine zone was temperature zone first followed by humidity region, with the reverse order being applied for the northwest arid/semi-arid zone. Results show that the extracted indicators were similar to those of the existing (expert-produced) regionalization scheme but more comprehensive. The primary indicator for defining temperature zones was the ≥10°C growing season, and the secondary indicators were the January and July mean temperatures. The primary and secondary indicators for identifying humid regions were aridity index and precipitation, respectively. Eco-geographical regions were mapped over China using these rules and the gridded indicators. Both the temperature zones and humidity regions mapped by the rules show ≥85% consistency with the existing regionalization, which is higher than values for mapping by the commonly used simplified method that uses the classification of one indicator. This study demonstrates that the proposed rough set method can establish eco-geographical regionalization that is quantitative and repeatable and able to dynamically updated.
Eco-geographical regionalization involves dividing land into regions by considering both intra-regional consistency and inter-regional disparity and is based on the pattern of differentiation of eco-geographical elements. Owing to the complexity of the land surface, and the limitation of data and appropriate methods, regions in China have hitherto been mapped manually, meaning that the process of mapping was non-repeatable. To make the regionalization technique repeatable, this study aimed to extract and quantify the expert knowledge of regionalization using an automated method. The rough set method was adopted to extract rules of regionalization based on the existing eco-geographical regionalization map of China, as well as its corresponding meteorological and geological datasets. Then, the rules for regionalization were obtained hierarchically for each natural domain, each temperature zone, and each humidity region. Owing to differences in zonal differentiation, the rule extraction sequence for the eastern monsoon zone and Tibetan Alpine zone was temperature zone first followed by humidity region, with the reverse order being applied for the northwest arid/semi-arid zone. Results show that the extracted indicators were similar to those of the existing (expert-produced) regionalization scheme but more comprehensive. The primary indicator for defining temperature zones was the ≥10°C growing season, and the secondary indicators were the January and July mean temperatures. The primary and secondary indicators for identifying humid regions were aridity index and precipitation, respectively. Eco-geographical regions were mapped over China using these rules and the gridded indicators. Both the temperature zones and humidity regions mapped by the rules show ≥85% consistency with the existing regionalization, which is higher than values for mapping by the commonly used simplified method that uses the classification of one indicator. This study demonstrates that the proposed rough set method can establish eco-geographical regionalization that is quantitative and repeatable and able to dynamically updated.
Determinants of Adaptation to Climate Change: A Case Study of Rice Farmers in Western Province, Iran
2022, 32(1): 110-126.
doi: 10.1007/s11769-021-1246-0
摘要:
The decisions made by agricultural households to adjust to climate change (CC) in Iran are not well known. This study is intended to investigate the influence of perceptions and socioeconomic, institutional features on farmers’ adaptation decisions about CC, which constitute the hypothetical statements of the study. We undertook a survey of 200 farm householders from 31 villages of Ilam Province, situated in the western Iran, as randomly selected. The result discloses that the proposed discriminant model matches the dataset well, with a strong effect size of partial eta-squared\begin{document}$ ({\eta }^{2} $\end{document} ![]()
![]()
The decisions made by agricultural households to adjust to climate change (CC) in Iran are not well known. This study is intended to investigate the influence of perceptions and socioeconomic, institutional features on farmers’ adaptation decisions about CC, which constitute the hypothetical statements of the study. We undertook a survey of 200 farm householders from 31 villages of Ilam Province, situated in the western Iran, as randomly selected. The result discloses that the proposed discriminant model matches the dataset well, with a strong effect size of partial eta-squared
2022, 32(1): 127-141.
doi: 10.1007/s11769-021-1250-4
摘要:
Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system, we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue. The resulting model, the ‘Humidity calibrated Drought Condition Index’ (HcDCI) was applied for the years 2001 to 2019 in form of a case study to Weihai County, Shandong Province in East China. Design and development are based on a linear combination of the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Rainfall Condition Index (RCI) using multi-source satellite data to create a basic Drought Condition Index (DCI). VCI and TCI were derived from MODIS (Moderate Resolution Imaging Spectroradiometer) data, while precipitation is taken from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) data. For reasons of accuracy, the decisive coefficients were determined by the relative humidity of soils at depth of 10–20 cm of particular areas collected by an agrometeorological ground station. The correlation between DCI and soil humidity was optimized with the factors of 0.53, 0.33, and 0.14 for VCI, TCI, and RCI, respectively. The model revealed, light agricultural droughts from 2003 to 2013 and in 2018, while more severe droughts occurred in 2001 and 2002, 2014–2017, and 2019. The droughts were most severe in January, March, and December, and our findings coincide with historical records. The average temperature during 2012–2019 is 1°C higher than that during the period 2001–2011 and the average precipitation during 2014–2019 is 192.77 mm less than that during 2008–2013. The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities. The model thus, demonstrates its capability to reveal drought periods in detail, its transferability to other regions and its usefulness to take future measures.
Inspired by recent significant agricultural yield losses in the eastern China and a missing operational monitoring system, we developed a comprehensive drought monitoring model to better understand the impact of individual key factors contributing to this issue. The resulting model, the ‘Humidity calibrated Drought Condition Index’ (HcDCI) was applied for the years 2001 to 2019 in form of a case study to Weihai County, Shandong Province in East China. Design and development are based on a linear combination of the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Rainfall Condition Index (RCI) using multi-source satellite data to create a basic Drought Condition Index (DCI). VCI and TCI were derived from MODIS (Moderate Resolution Imaging Spectroradiometer) data, while precipitation is taken from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) data. For reasons of accuracy, the decisive coefficients were determined by the relative humidity of soils at depth of 10–20 cm of particular areas collected by an agrometeorological ground station. The correlation between DCI and soil humidity was optimized with the factors of 0.53, 0.33, and 0.14 for VCI, TCI, and RCI, respectively. The model revealed, light agricultural droughts from 2003 to 2013 and in 2018, while more severe droughts occurred in 2001 and 2002, 2014–2017, and 2019. The droughts were most severe in January, March, and December, and our findings coincide with historical records. The average temperature during 2012–2019 is 1°C higher than that during the period 2001–2011 and the average precipitation during 2014–2019 is 192.77 mm less than that during 2008–2013. The spatio-temporal accuracy of the HcDCI model was positively validated by correlation with agricultural crop yield quantities. The model thus, demonstrates its capability to reveal drought periods in detail, its transferability to other regions and its usefulness to take future measures.
2022, 32(1): 142-154.
doi: 10.1007/s11769-022-1260-x
摘要:
Carex tussock plays an important role in supporting biodiversity and carbon sequestration of wetland ecosystems, while it is highly threatened by climate change and anthropogenic activities. Therefore, identifying the potential distribution patterns of Carex tussocks wetland is vital for their targeted conservation and restoration. The current and future (2050s and 2070s) potential habitats distribution of Carex tussocks in Northeast China were predicted using a Maximum Entropy (Maxent) model based on 68 current data of Carex tussock distributions and three groups of environmental variables (bioclimate, topography, soil properties). Results show that isothermality, seasonal precipitation variability and altitude are important factors that determine the distribution of Carex tussock. The high suitable habitat of Carex tussock is about 5.7 × 104 km2 and mainly distributed in the Sanjiang Plain, Songnen Plain, Changbai Mountains and Da Hinggan Mountains. The area of stable habitats of Carex tussock is significantly higher than the lost and expanded habitats in the future climate scenarios, and the unsuitable habitats mainly occur in Da Hinggan Mountains, Xiao Hinggan Mountains and Changbai Mountains. Overall, Carex tussock wetlands at high altitude and high latitude are more sensitive to climate change, and more attention should be invested in high latitude and high altitude areas.
Carex tussock plays an important role in supporting biodiversity and carbon sequestration of wetland ecosystems, while it is highly threatened by climate change and anthropogenic activities. Therefore, identifying the potential distribution patterns of Carex tussocks wetland is vital for their targeted conservation and restoration. The current and future (2050s and 2070s) potential habitats distribution of Carex tussocks in Northeast China were predicted using a Maximum Entropy (Maxent) model based on 68 current data of Carex tussock distributions and three groups of environmental variables (bioclimate, topography, soil properties). Results show that isothermality, seasonal precipitation variability and altitude are important factors that determine the distribution of Carex tussock. The high suitable habitat of Carex tussock is about 5.7 × 104 km2 and mainly distributed in the Sanjiang Plain, Songnen Plain, Changbai Mountains and Da Hinggan Mountains. The area of stable habitats of Carex tussock is significantly higher than the lost and expanded habitats in the future climate scenarios, and the unsuitable habitats mainly occur in Da Hinggan Mountains, Xiao Hinggan Mountains and Changbai Mountains. Overall, Carex tussock wetlands at high altitude and high latitude are more sensitive to climate change, and more attention should be invested in high latitude and high altitude areas.
2022, 32(1): 155-173.
doi: 10.1007/s11769-021-1249-x
摘要:
The Tibetan Plateau (TP) is one of the most sensitive areas and is more susceptible to climate change than other regions in China. The TP also experiences extremely frequent light precipitation events compared to precipitation of other intensities. However, the definition, influencing factors, and characteristics of light precipitation in the TP have not been accurately explained. This study investigated the variation characteristics of light precipitation with intensities (Pre) of 0.1–10.0 mm/d based on climate data from 53 meteorological stations over the central and eastern TP from 1961 to 2019. For detailed analysis, light precipitation events were classified into five grades: G1 [0.1–2.0 mm/d), G2 [2.0–4.0 mm/d), G3 [4.0–6.0 mm/d), G4 [6.0–8.0 mm/d), and G5 [8.0–10.0 mm/d). The results showed that both the amount of precipitation and number of precipitation days had increased significantly at rates of 4.0–6.0 mm/10 yr and 2.0–4.0 d/10 yr, respectively, and most precipitation events were of low intensity (0.1 ≤ Pre < 2.0 mm/d). Light precipitation events mainly occurred in the southeast of the study area, and it showed an increasing trend from the northwest to the southeast . Abrupt changes in light precipitation primarily occurred in the 1980s. A comprehensive time series analysis using the Mann-Kendall test and Morlet wavelet was performed to characterize the abrupt changes and cycles of light precipitation. During the study period, the main periods of light precipitation corresponded to the 6 yr cycle, with obvious periodic oscillation characteristics, and this cycle coexisted with cycles of other scales. Significant correlations were observed between the amount of light precipitation and temperature over the study area. The findings will enhance our understanding of changes in light precipitation in the TP and provide Scientific basis for the definition of light precipitation in the future.
The Tibetan Plateau (TP) is one of the most sensitive areas and is more susceptible to climate change than other regions in China. The TP also experiences extremely frequent light precipitation events compared to precipitation of other intensities. However, the definition, influencing factors, and characteristics of light precipitation in the TP have not been accurately explained. This study investigated the variation characteristics of light precipitation with intensities (Pre) of 0.1–10.0 mm/d based on climate data from 53 meteorological stations over the central and eastern TP from 1961 to 2019. For detailed analysis, light precipitation events were classified into five grades: G1 [0.1–2.0 mm/d), G2 [2.0–4.0 mm/d), G3 [4.0–6.0 mm/d), G4 [6.0–8.0 mm/d), and G5 [8.0–10.0 mm/d). The results showed that both the amount of precipitation and number of precipitation days had increased significantly at rates of 4.0–6.0 mm/10 yr and 2.0–4.0 d/10 yr, respectively, and most precipitation events were of low intensity (0.1 ≤ Pre < 2.0 mm/d). Light precipitation events mainly occurred in the southeast of the study area, and it showed an increasing trend from the northwest to the southeast . Abrupt changes in light precipitation primarily occurred in the 1980s. A comprehensive time series analysis using the Mann-Kendall test and Morlet wavelet was performed to characterize the abrupt changes and cycles of light precipitation. During the study period, the main periods of light precipitation corresponded to the 6 yr cycle, with obvious periodic oscillation characteristics, and this cycle coexisted with cycles of other scales. Significant correlations were observed between the amount of light precipitation and temperature over the study area. The findings will enhance our understanding of changes in light precipitation in the TP and provide Scientific basis for the definition of light precipitation in the future.
2022, 32(1): 174-188.
doi: 10.1007/s11769-021-1252-2
摘要:
Climate change and human interference play significant roles on dynamic of water body abundance, and drive related hydrological, biochemical and social/economic processes. Documenting and monitoring surface water area with high resolution multi-temporal satellite imagery provide new perspective to evaluate the dynamics of surface water area, especially in continental and global scale. In this study, based on the Landsat images from 1980s to 2015, we surveyed the spatial and temporal variation of surface water area, including rivers, lakes and reservoirs, in 10-yr temporal slice across China. Furthermore, the driving forces of the variation has been identified to reveal the interaction of water bodies and the changing environment. The results show that, the water surface area expanded over all three decades with strong spatial and temporal difference, despite the drier and warmer climate background; although lakes comprise the largest portion of the surface water area, the highest contributor of surface water expansion was new constructed reservoir located in the densely populated region; climatic parameters alteration, like precipitation and temperature, resulted in the water surface expansion in the northwestern basin by growing water input linked with rain and glacier melting; in the rest part of China, rise of water surface area was predominately attributed to human relocation of water resource, which yielded more new water storage area than the disappeared water body caused by less precipitation and stronger evapotranspiration. The conclusions highlight the integrative water resource management, especially in water conservation and restoration.
Climate change and human interference play significant roles on dynamic of water body abundance, and drive related hydrological, biochemical and social/economic processes. Documenting and monitoring surface water area with high resolution multi-temporal satellite imagery provide new perspective to evaluate the dynamics of surface water area, especially in continental and global scale. In this study, based on the Landsat images from 1980s to 2015, we surveyed the spatial and temporal variation of surface water area, including rivers, lakes and reservoirs, in 10-yr temporal slice across China. Furthermore, the driving forces of the variation has been identified to reveal the interaction of water bodies and the changing environment. The results show that, the water surface area expanded over all three decades with strong spatial and temporal difference, despite the drier and warmer climate background; although lakes comprise the largest portion of the surface water area, the highest contributor of surface water expansion was new constructed reservoir located in the densely populated region; climatic parameters alteration, like precipitation and temperature, resulted in the water surface expansion in the northwestern basin by growing water input linked with rain and glacier melting; in the rest part of China, rise of water surface area was predominately attributed to human relocation of water resource, which yielded more new water storage area than the disappeared water body caused by less precipitation and stronger evapotranspiration. The conclusions highlight the integrative water resource management, especially in water conservation and restoration.
2022, 32(1): 16-30.
doi: 10.1007/s11769-022-1256-6
摘要:
As the leading urban agglomeration in China, the Yangtze River Delta (YRD) is experiencing a factor-driven to innovation-driven transition. However, the dynamics of regional innovation growth are not yet fully understood. This paper combines the complex network methodology with spatial econometrics to disentangle the contributions of innovation endowments, innovation network flows, and innovation network positions to regional innovation growth, as well as their spatial spillover effects. The primary findings suggest that regional innovation growth results from the networked agglomeration economies, which is shaped by the interactions between agglomeration factors and network factors. Specifically, agglomeration factors play a fundamental role in regional innovation growth. In contrast, network factors, such as the network flows and network positions, may contribute to new path creation by promoting access to external innovation resources. Additionally, the institutional factors show multiplexity in fostering regional innovation patterns. Such findings indicate that the YRD region should shift the innovation growth pattern from competitive involution to mutually beneficial cooperation to reduce regional disparities. In this regard, the institutional capacity of organizing network flows and fostering reciprocal inter-city partnerships has become increasingly critical for promoting sustainable innovation and regional development.
As the leading urban agglomeration in China, the Yangtze River Delta (YRD) is experiencing a factor-driven to innovation-driven transition. However, the dynamics of regional innovation growth are not yet fully understood. This paper combines the complex network methodology with spatial econometrics to disentangle the contributions of innovation endowments, innovation network flows, and innovation network positions to regional innovation growth, as well as their spatial spillover effects. The primary findings suggest that regional innovation growth results from the networked agglomeration economies, which is shaped by the interactions between agglomeration factors and network factors. Specifically, agglomeration factors play a fundamental role in regional innovation growth. In contrast, network factors, such as the network flows and network positions, may contribute to new path creation by promoting access to external innovation resources. Additionally, the institutional factors show multiplexity in fostering regional innovation patterns. Such findings indicate that the YRD region should shift the innovation growth pattern from competitive involution to mutually beneficial cooperation to reduce regional disparities. In this regard, the institutional capacity of organizing network flows and fostering reciprocal inter-city partnerships has become increasingly critical for promoting sustainable innovation and regional development.
2022, 32(1): 64-78.
doi: 10.1007/s11769-021-1253-1
摘要:
Taking the system philosophy of human-earth relationship as the theoretical axis, and under the three-dimensional goals of economic growth, social development, and protection of the ecological environment, this paper constructs the supporting system of China’s economic development. On this basis, guided by the basic principles of system theory and system dynamics, and combined with the theories of other related disciplines, we constructed an economic geography-system dynamics (EG-SD) integrated forecasting model to simulate and quantitatively forecast China’s economic growth in the medium and long term. China’s economic growth will be affected by quantifiable and unquantifiable factors. If the main unquantifiable factors are not taken into account in the simulation and prediction of China’s economic growth in the medium and long term, the accuracy and objectivity of the prediction results will be diminished. Therefore, based on situation analysis (Strengths, Weaknesses, Opportunities, and Threats, SWOT), we combined scenario analysis with the Delphi method, and established a qualitative prediction simulation model (referred to as the S-D compound prediction model) to make up for the shortcomings associated with quantitative simulation predictions. EG-SD and S-D are organically combined to construct a simulation and prediction paradigm of China’s economic growth in the medium and long term. This paradigm not only realizes the integration of various forecasting methods and the combination of qualitative and quantitative measures, but also realizes the organic combination of unquantifiable and quantifiable elements by innovatively introducing fuzzy simulation of system dynamics, which renders the simulation and prediction results more objective and accurate.
Taking the system philosophy of human-earth relationship as the theoretical axis, and under the three-dimensional goals of economic growth, social development, and protection of the ecological environment, this paper constructs the supporting system of China’s economic development. On this basis, guided by the basic principles of system theory and system dynamics, and combined with the theories of other related disciplines, we constructed an economic geography-system dynamics (EG-SD) integrated forecasting model to simulate and quantitatively forecast China’s economic growth in the medium and long term. China’s economic growth will be affected by quantifiable and unquantifiable factors. If the main unquantifiable factors are not taken into account in the simulation and prediction of China’s economic growth in the medium and long term, the accuracy and objectivity of the prediction results will be diminished. Therefore, based on situation analysis (Strengths, Weaknesses, Opportunities, and Threats, SWOT), we combined scenario analysis with the Delphi method, and established a qualitative prediction simulation model (referred to as the S-D compound prediction model) to make up for the shortcomings associated with quantitative simulation predictions. EG-SD and S-D are organically combined to construct a simulation and prediction paradigm of China’s economic growth in the medium and long term. This paradigm not only realizes the integration of various forecasting methods and the combination of qualitative and quantitative measures, but also realizes the organic combination of unquantifiable and quantifiable elements by innovatively introducing fuzzy simulation of system dynamics, which renders the simulation and prediction results more objective and accurate.
Email
RSS