2016 Vol. 26, No. 5
Display Method:
2016, 26(5): 577-588.
doi: 10.1007/s11769-015-0792-8
Abstract:
A large number of studies have been conducted to find a better fit for city rank-size distributions in different countries. Many theoretical curves have been proposed, but no consensus has been reached. This study argues for the importance of examining city rank-size distribution across different city size scales. In addition to focusing on macro patterns, this study examines the micro patterns of city rank-size distributions in China. A moving window method is developed to detect rank-size distributions of cities in different sizes incrementally. The results show that micro patterns of the actual city rank-size distributions in China are much more complex than those suggested by the three theoretical distributions examined (Pareto, quadratic, and q-exponential distributions). City size distributions present persistent discontinuities. Large cities are more evenly distributed than small cities and than that predicted by Zipf's law. In addition, the trend is becoming more pronounced over time. Medium-sized cities became evenly distributed first and then unevenly distributed thereafter. The rank-size distributions of small cities are relatively consistent. While the three theoretical distributions examined in this study all have the ability to detect the overall dynamics of city rank-size distributions, the actual macro distribution may be composed of a combination of the three theoretical distributions.
A large number of studies have been conducted to find a better fit for city rank-size distributions in different countries. Many theoretical curves have been proposed, but no consensus has been reached. This study argues for the importance of examining city rank-size distribution across different city size scales. In addition to focusing on macro patterns, this study examines the micro patterns of city rank-size distributions in China. A moving window method is developed to detect rank-size distributions of cities in different sizes incrementally. The results show that micro patterns of the actual city rank-size distributions in China are much more complex than those suggested by the three theoretical distributions examined (Pareto, quadratic, and q-exponential distributions). City size distributions present persistent discontinuities. Large cities are more evenly distributed than small cities and than that predicted by Zipf's law. In addition, the trend is becoming more pronounced over time. Medium-sized cities became evenly distributed first and then unevenly distributed thereafter. The rank-size distributions of small cities are relatively consistent. While the three theoretical distributions examined in this study all have the ability to detect the overall dynamics of city rank-size distributions, the actual macro distribution may be composed of a combination of the three theoretical distributions.
2016, 26(5): 599-608.
doi: 10.1007/s11769-015-0793-7
Abstract:
During the reform era, Chinese cities witnessed dramatic institutional transformation and spatial restructuring in general and profound change of commuting patterns in particular. Using household surveys collected in Guangzhou, China, in 2001, 2005 and 2010, excess commuting measurements are estimated. Excess commuting shows an overall trend of increasing during 1990-1999, and then declining during 2000-2010. We argue that deepening marketization of the jobs and housing sectors has induced spatial separation of jobs and housing. In other words, institutional transition and urban spatial restructuring are underpinning the changes of commuting patterns in Chinese cities. Excess commuting has strong relationship with individual socio-demographic status, which is by and large due to the increasing flexibilities of jobs and housing location choices enjoyed by urban residents. The findings call for considerations on balancing jobs-housing in making public policies relevant to urban development in general, and land use and transportation in particular.
During the reform era, Chinese cities witnessed dramatic institutional transformation and spatial restructuring in general and profound change of commuting patterns in particular. Using household surveys collected in Guangzhou, China, in 2001, 2005 and 2010, excess commuting measurements are estimated. Excess commuting shows an overall trend of increasing during 1990-1999, and then declining during 2000-2010. We argue that deepening marketization of the jobs and housing sectors has induced spatial separation of jobs and housing. In other words, institutional transition and urban spatial restructuring are underpinning the changes of commuting patterns in Chinese cities. Excess commuting has strong relationship with individual socio-demographic status, which is by and large due to the increasing flexibilities of jobs and housing location choices enjoyed by urban residents. The findings call for considerations on balancing jobs-housing in making public policies relevant to urban development in general, and land use and transportation in particular.
2016, 26(5): 609-622.
doi: 10.1007/s11769-016-0817-y
Abstract:
Recently, the desiccation effect of the North Atlantic Oscillation (NAO) is found to be positively correlated with violent conflict in pre-industrial Europe, with agricultural shrinkage and its subsequent economic shocks to be their causal link. However, it remains unexplored whether the correlation persists if the study period is extended backward in time, a different definition of violent conflict is applied, or the relationship is examined at lower geographic levels. In this study, we based on 835 internal disturbance incidents in Europe during 1049-1800 to conduct long-temporal and multi-scalar examination on the NAO-conflict nexus.‘Time-series’and‘panel data’disaggregation approaches, together with Granger Causality, Multiple Regression, and Survival Analyses were applied to verify the nexus quantitatively. Results show that the positive NAO-conflict correlation was significant at the continent and physiographic zone levels. During the positive NAO phases, the annual probability of internal disturbance outbreak increased by 70.0% in the southern Europe and the Mediterranean, a zone most affected by the NAO-induced desiccation effect. Yet, the NAO-conflict correlation was rather inconsistent when it was downscaled to the sub-regional level. Moreover, the NAO-conflict correlation was inflated under the time-series approach, while the panel data approach demonstrated the region-specific nature of the NAO forcing more clearly. The associated implications in examining climate-conflict nexus are discussed. Our findings may be crucial in examining violent conflict in the northwestern Africa, a highly agricultural region affected by the NAO.
Recently, the desiccation effect of the North Atlantic Oscillation (NAO) is found to be positively correlated with violent conflict in pre-industrial Europe, with agricultural shrinkage and its subsequent economic shocks to be their causal link. However, it remains unexplored whether the correlation persists if the study period is extended backward in time, a different definition of violent conflict is applied, or the relationship is examined at lower geographic levels. In this study, we based on 835 internal disturbance incidents in Europe during 1049-1800 to conduct long-temporal and multi-scalar examination on the NAO-conflict nexus.‘Time-series’and‘panel data’disaggregation approaches, together with Granger Causality, Multiple Regression, and Survival Analyses were applied to verify the nexus quantitatively. Results show that the positive NAO-conflict correlation was significant at the continent and physiographic zone levels. During the positive NAO phases, the annual probability of internal disturbance outbreak increased by 70.0% in the southern Europe and the Mediterranean, a zone most affected by the NAO-induced desiccation effect. Yet, the NAO-conflict correlation was rather inconsistent when it was downscaled to the sub-regional level. Moreover, the NAO-conflict correlation was inflated under the time-series approach, while the panel data approach demonstrated the region-specific nature of the NAO forcing more clearly. The associated implications in examining climate-conflict nexus are discussed. Our findings may be crucial in examining violent conflict in the northwestern Africa, a highly agricultural region affected by the NAO.
2016, 26(5): 623-637.
doi: 10.1007/s11769-016-0827-9
Abstract:
Quality of life (QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ‘establishing overall well-off society’. Northeast China is one of the most import old industrial bases in China, however, the industrial structure of heavy chemical industry and the development mode of ‘production first, living last’ have leaded to series of social problems, which have also become a serious bottleneck to social stability and economic sustainable development. Through applying the methods of BP neural network, exploratory spatial data analysis (ESDA) and spatial regression model, this paper examines the space-time dynamics of QOL of the residents in Northeast China. We first investigate the indexes of QOL of the residents and then use ESDA methods to visualize its space-time relationship. We have found a spatial agglomeration of QOL of the residents in middle-southern Liaoning Province, central Jilin Province and Harbin-Qiqihar-Daqing area of Heilongjiang Province. Two third of the counties are low-low spatial correlation, and the correlative type of about 60% of the prefecture level areas keeps stable, indicating QOL of the residents in Northeast China shows a certain character of path dependence or spatial locked. We have also found that economic strength and development levels of service industry have positive and obvious effect on QOL of the residents, while the effect of such indexes as the social service level and the proportion of the tertiary industries are less.
Quality of life (QOL) is a hotspot issue that has attracted increasing attention from the Chinese Government and scholars, it is also a vital issue that should be addressed during the cause of ‘establishing overall well-off society’. Northeast China is one of the most import old industrial bases in China, however, the industrial structure of heavy chemical industry and the development mode of ‘production first, living last’ have leaded to series of social problems, which have also become a serious bottleneck to social stability and economic sustainable development. Through applying the methods of BP neural network, exploratory spatial data analysis (ESDA) and spatial regression model, this paper examines the space-time dynamics of QOL of the residents in Northeast China. We first investigate the indexes of QOL of the residents and then use ESDA methods to visualize its space-time relationship. We have found a spatial agglomeration of QOL of the residents in middle-southern Liaoning Province, central Jilin Province and Harbin-Qiqihar-Daqing area of Heilongjiang Province. Two third of the counties are low-low spatial correlation, and the correlative type of about 60% of the prefecture level areas keeps stable, indicating QOL of the residents in Northeast China shows a certain character of path dependence or spatial locked. We have also found that economic strength and development levels of service industry have positive and obvious effect on QOL of the residents, while the effect of such indexes as the social service level and the proportion of the tertiary industries are less.
2016, 26(5): 638-655.
doi: 10.1007/s11769-016-0821-2
Abstract:
Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation (RSSE) using an improved technique for order preference by similarity to ideal solution (TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.
Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation (RSSE) using an improved technique for order preference by similarity to ideal solution (TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.
2016, 26(5): 656-669.
doi: 10.1007/s11769-016-0823-0
Abstract:
This paper constructed a carbon emission identity based on five factors: industrial activity, industrial structure, energy intensity, energy mix and carbon emission parameter, and analyzed manufacturing carbon emission trends in Jilin Province at subdivided industrial level through Log-Mean Divisia Index (LMDI) method. Results showed that manufacturing carbon emissions of Jilin Province increased 1.304×107 t by 66% between 2004 and 2010. However, 2012 was a remarkable year in which carbon emissions decreased compared with 2011, the first fall since 2004. Industrial activity was the most important factor for the increase of carbon emissions, while energy intensity had the greatest impact on inhibiting carbon emission growth. Despite the impact of industrial structure on carbon emissions fluctuated, its overall trend inhibited carbon emission growth. Further, influences of industrial structure became gradually stronger and surpassed energy intensity in the period 2009-2010. These results conclude that reducing energy intensity is still the main way for carbon emission reduction in Jilin Province, but industrial structure can not be ignored and it has great potential. Based on the analyses, the way of manufacturing industrial structure adjustment for Jilin Province is put forward.
This paper constructed a carbon emission identity based on five factors: industrial activity, industrial structure, energy intensity, energy mix and carbon emission parameter, and analyzed manufacturing carbon emission trends in Jilin Province at subdivided industrial level through Log-Mean Divisia Index (LMDI) method. Results showed that manufacturing carbon emissions of Jilin Province increased 1.304×107 t by 66% between 2004 and 2010. However, 2012 was a remarkable year in which carbon emissions decreased compared with 2011, the first fall since 2004. Industrial activity was the most important factor for the increase of carbon emissions, while energy intensity had the greatest impact on inhibiting carbon emission growth. Despite the impact of industrial structure on carbon emissions fluctuated, its overall trend inhibited carbon emission growth. Further, influences of industrial structure became gradually stronger and surpassed energy intensity in the period 2009-2010. These results conclude that reducing energy intensity is still the main way for carbon emission reduction in Jilin Province, but industrial structure can not be ignored and it has great potential. Based on the analyses, the way of manufacturing industrial structure adjustment for Jilin Province is put forward.
2016, 26(5): 670-678.
doi: 10.1007/s11769-015-0736-3
Abstract:
Studying the relationship between climate factors and soil organic carbon (SOC) is vitally important. However, how SOC responses to climate (temperature and precipitation) at cohesive extents is poorly studied. Two transects of approximately the same length (transect P and transect T) were selected to examine the variation of SOC content in relation to mean annual temperature (MAT) and mean annual precipitation (MAP). The coefficients of partial correlation between SOC density and MAT (Rt) and MAP (Rp) were determined to quantify the relationships between SOC density and the two climate factors. The results indicated that for transect T, Rt was statistically significant once the extent level was greater than or equal to two fundamental extent units, while for transect P, Rp showed statistical significance only at extent levels which were greater than two fundamental extent units. At the same extent levels but in different transects, Rts exhibited no zonal difference, but Rps did once the extent level was greater than two fundamental extent units. Therefore, to study the relationship between SOC density and different climate factors, different minimum extent levels should be examined. The results of this paper could deepen the understanding of the impacts that SOC pool has on terrestrial ecosystem and global carbon cycling.
Studying the relationship between climate factors and soil organic carbon (SOC) is vitally important. However, how SOC responses to climate (temperature and precipitation) at cohesive extents is poorly studied. Two transects of approximately the same length (transect P and transect T) were selected to examine the variation of SOC content in relation to mean annual temperature (MAT) and mean annual precipitation (MAP). The coefficients of partial correlation between SOC density and MAT (Rt) and MAP (Rp) were determined to quantify the relationships between SOC density and the two climate factors. The results indicated that for transect T, Rt was statistically significant once the extent level was greater than or equal to two fundamental extent units, while for transect P, Rp showed statistical significance only at extent levels which were greater than two fundamental extent units. At the same extent levels but in different transects, Rts exhibited no zonal difference, but Rps did once the extent level was greater than two fundamental extent units. Therefore, to study the relationship between SOC density and different climate factors, different minimum extent levels should be examined. The results of this paper could deepen the understanding of the impacts that SOC pool has on terrestrial ecosystem and global carbon cycling.
2016, 26(5): 679-686.
doi: 10.1007/s11769-016-0828-8
Abstract:
As a key factor limiting primary productivity in marine ecosystem, dissolved iron (DFe) export from fluvial systems has increased recently. There is particular concern about discharges of DFe during extreme flooding, when they are thought to increase considerably. An extreme flood event that caused inundation of extensive areas of Far Eastern Russia and Northeastern China occurred in the basin of the Amur River during summer and autumn 2013. During this event, water samples were collected in the middle reaches of the Amur River and the lower reaches at Khabarovsk City and analyzed for DFe concentrations and other aquatic parameters. The results show that the average DFe concentrations in the middle reaches of the Amur River (right bank) and at Khabarovsk were 1.11 mg/L and 0.32 mg/L, respectively, during the extreme flood in 2013. The total discharge of DFe during the flood event was 6.25×104 t. The high discharge of DFe during the flood reflects the elevated discharge of the river, hydrologically connected riparian wetlands, vast quantities of terrestrial runoff, and flood discharges from the Zeya and Bureya reservoirs. These results show that long-term monitoring is needed to identify and assess the impacts of DFe transport on the downstream reaches, estuarine area, and coastal ecosystems of the Amur River.
As a key factor limiting primary productivity in marine ecosystem, dissolved iron (DFe) export from fluvial systems has increased recently. There is particular concern about discharges of DFe during extreme flooding, when they are thought to increase considerably. An extreme flood event that caused inundation of extensive areas of Far Eastern Russia and Northeastern China occurred in the basin of the Amur River during summer and autumn 2013. During this event, water samples were collected in the middle reaches of the Amur River and the lower reaches at Khabarovsk City and analyzed for DFe concentrations and other aquatic parameters. The results show that the average DFe concentrations in the middle reaches of the Amur River (right bank) and at Khabarovsk were 1.11 mg/L and 0.32 mg/L, respectively, during the extreme flood in 2013. The total discharge of DFe during the flood event was 6.25×104 t. The high discharge of DFe during the flood reflects the elevated discharge of the river, hydrologically connected riparian wetlands, vast quantities of terrestrial runoff, and flood discharges from the Zeya and Bureya reservoirs. These results show that long-term monitoring is needed to identify and assess the impacts of DFe transport on the downstream reaches, estuarine area, and coastal ecosystems of the Amur River.
2016, 26(5): 687-702.
doi: 10.1007/s11769-016-0820-3
Abstract:
The Thornthwaite moisture index, an index of the supply of water (precipitation) in an area relative to the climatic demand for water (poten-tial evapotranspiration), was used to examine the spatial and temporal variation of drought and to verify the influence of environmental factors on the drought in the Hengduan Mountains, China. Results indicate that the Thornthwaite moisture index in the Hengduan Moun-tains had been increasing since 1960 with a rate of 0.1938/yr. Annual Thornthwaite moisture index in Hengduan Mountains was between -97.47 and 67.43 and the spatial heterogeneity was obvious in different seasons. Thornthwaite moisture index was high in the north and low in the south, and the monsoon rainfall had a significant impact on its spatial distribution. The tendency rate of Thornthwaite moisture index variation varied in different seasons, and the increasing trends in spring were greater than that in summer and autumn. However, the Thornthwaite moisture index decreased in winter. Thornthwaite moisture index increased greatly in the north and there was a small growth in the south of Hengduan Mountains. The increase of precipitation and decrease of evaporation lead to the increase of Thornthwaite mois-ture index. Thornthwaite moisture index has strong correlation with vegetation coverage. It can be seen that the correlation between Nor-malized Difference Vegetation Index (NDVI) and Thornthwaite moisture index was positive in spring and summer, but negative in autumn and winter. Correlation between Thornthwaite moisture index and relative soil relative moisture content was positive in spring, summer and autumn, but negative in winter. The typical mountainous terrain affect the distribution of temperature, precipitation, wind speed and other meteorological factors in this region, and then affect the spatial distribution of Thornthwaite moisture index. The unique ridge-gorge terrain caused the continuity of water-heat distribution from the north to south, and the water-heat was stronger than that from the east to west part, and thus determined the spatial distribution of Thornthwaite moisture index. The drought in the Hengduan Mountains area is mainly due to the unstable South Asian monsoon rainfall time.
The Thornthwaite moisture index, an index of the supply of water (precipitation) in an area relative to the climatic demand for water (poten-tial evapotranspiration), was used to examine the spatial and temporal variation of drought and to verify the influence of environmental factors on the drought in the Hengduan Mountains, China. Results indicate that the Thornthwaite moisture index in the Hengduan Moun-tains had been increasing since 1960 with a rate of 0.1938/yr. Annual Thornthwaite moisture index in Hengduan Mountains was between -97.47 and 67.43 and the spatial heterogeneity was obvious in different seasons. Thornthwaite moisture index was high in the north and low in the south, and the monsoon rainfall had a significant impact on its spatial distribution. The tendency rate of Thornthwaite moisture index variation varied in different seasons, and the increasing trends in spring were greater than that in summer and autumn. However, the Thornthwaite moisture index decreased in winter. Thornthwaite moisture index increased greatly in the north and there was a small growth in the south of Hengduan Mountains. The increase of precipitation and decrease of evaporation lead to the increase of Thornthwaite mois-ture index. Thornthwaite moisture index has strong correlation with vegetation coverage. It can be seen that the correlation between Nor-malized Difference Vegetation Index (NDVI) and Thornthwaite moisture index was positive in spring and summer, but negative in autumn and winter. Correlation between Thornthwaite moisture index and relative soil relative moisture content was positive in spring, summer and autumn, but negative in winter. The typical mountainous terrain affect the distribution of temperature, precipitation, wind speed and other meteorological factors in this region, and then affect the spatial distribution of Thornthwaite moisture index. The unique ridge-gorge terrain caused the continuity of water-heat distribution from the north to south, and the water-heat was stronger than that from the east to west part, and thus determined the spatial distribution of Thornthwaite moisture index. The drought in the Hengduan Mountains area is mainly due to the unstable South Asian monsoon rainfall time.
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