This paper intends to investigate the urban spatial patterns of Hubei Province and its evolution from three different perspectives: urban nodes, urban connections and urban clusters. The research adopts nighttime ligh...This paper intends to investigate the urban spatial patterns of Hubei Province and its evolution from three different perspectives: urban nodes, urban connections and urban clusters. The research adopts nighttime light imagery of cities in Hubei Province, the viewpoint of ′point-axis-area′ in the ′point-axis system′ theory, and employs light index model, gravity model and social network analysis. The findings are as follows: 1) In terms of urban nodes, the urbanization process of Hubei has been carried out mainly on the basis of external expansion rather than internal increasing. The polarization trend of urban connection network is strengthening. 2) As for urban connections, the estimation of urban connections using light index model is capable of containing various actual flow, and the connections are getting increasingly closer. 3) In regard to urban groups, seven urban groups of varying sizes have formed. On that basis, three stable and relatively independent urban groups as the centers, namely Wuchang, Yichang and Xiangyang emerge as well. But the structures of ′Wuhan Metropolitan Area′, ′Yichang-Jingzhou-Jingmen City Group′ and ′Xiangyang-Shiyen-Suizhou City Group′, which are defined by local development strategy in Hubei Province, are different from the above three urban groups.展开更多
This article presents the findings of a study of the spheres of urban influence with regard to all cities in China(not including Hong Kong,Macao and Taiwan Province of China)in the years 1990,2000 and 2009.An optimize...This article presents the findings of a study of the spheres of urban influence with regard to all cities in China(not including Hong Kong,Macao and Taiwan Province of China)in the years 1990,2000 and 2009.An optimized gravity model with comprehensive time distance was used to carry out a detailed analysis of the spatial patterns of Chinese spheres of urban influence and the spatial characteristics of urban agglomerations.Such urban agglomerations are characterized by high density population and a developed economy,which are also considered as the national competition unit.This paper initially identifies four spatial patterns of urban agglomerations based on the spatial layout of city groups during their evolution.Some basic characteristics of urban agglomerations are outlined,including the number of cities,the size of cities and the functions of urban centers.These characteristics are examined by using statistical methods and Geographic Information System(GIS).The main findings from this research are that the development stages and structures of urban agglomerations in China vary significantly.It is also clear that the stages and evolution of spatial patterns are strongly affected and dominated by both policy and location factors.展开更多
By using digitized land use maps of Beijing in 1982, 1992 and 1997 and employing GIS spatial analysis techniques, this paper conducts an empirical study on the spatial differentiation and spatial patterns of urban lan...By using digitized land use maps of Beijing in 1982, 1992 and 1997 and employing GIS spatial analysis techniques, this paper conducts an empirical study on the spatial differentiation and spatial patterns of urban land use growth in Beijing in the period of 1982–1997. It is observed that urban land use growth in Beijing went beyond the control of urban planning, in terms of the extraordinary high growth rate and undesired spatial pattern. The rate of urban expansion after 1982, which was predominated by growth of industrial land, was extraordinary high compared to its historical period. While its growth centers have been actively shifting toward the northern part, rather than toward the southern and eastern parts as designated by the latest General Plan (1991–2010) of Beijing, its spatial pattern of urban land use growth in general was in distinct concentric sprawl, which seriously violated the General Plan of Beijing.展开更多
Negative air ions are natural components of the air we breathe Forests are the main continuous natural source of negative air ions （NAI）. The spatio-temporal patterns of negative air ions were explored in Shanghai, ...Negative air ions are natural components of the air we breathe Forests are the main continuous natural source of negative air ions （NAI）. The spatio-temporal patterns of negative air ions were explored in Shanghai, based on monthly monitoring in 15 parks from March 2009 to February 2010. In each park, sampling sites were selected in forests and open spaces. The annual variation in negative air ion concentrations （NAIC） showed peak values from June to October and minimum values from December to January. NAIC were highest in summer and autumn, intermediate in spring, and lowest in winter. During spring and summer, NAIC in open spaces were significantly higher in rural areas than those in suburban areas. However, there were no significant differences in NAIC at forest sites among seasons. For open spaces, total suspended particles （TSP） were the dominant determining factor of NAIC in sum- mer, and air temperature and air humidity were the dominant determining factors of NAIC in spring, which were tightly correlated with Shanghai＇s ongoing urbanization and its impacts on the environment. R is suggested that urbanization could induce variation in NAIC along the urban-rural gradient, but that may not change the temporal variation pattern. Fur- thermore, the effects of urbanization on NAIC were limited in non-vegetated or less-vegetated sites, such as open spaces, but not in well-vegetated areas, such as urban forests. Therefore, we suggest that urban greening, especially urban forest, has significant resistance to theeffect of urbanization on NAIC.展开更多
Based on the night light data, urban area data, and economic data of Wuhan Urban Agglomeration from 2009 to 2015, we use spatial correlation dimension, spatial self-correlation analysis and weighted standard deviation...Based on the night light data, urban area data, and economic data of Wuhan Urban Agglomeration from 2009 to 2015, we use spatial correlation dimension, spatial self-correlation analysis and weighted standard deviation ellipse to identify the general characteristics and dynamic evolution characteristics of urban spatial pattern and economic disparity pattern. The research results prove that: between 2009 and 2013, Wuhan Urban Agglomeration expanded gradually from northwest to southeast and presented the dynamic evolution features of “along the river and the road”. The spatial structure is obvious, forming the pattern of “core-periphery”. The development of Wuhan Urban Agglomeration has obvious imbalance in economic geography space, presenting the development tendency of “One prominent, stronger in the west and weaker in the east”. The contract within Wuhan Urban Agglomeration is gradually decreased. Wuhan city and its surrounding areas have stronger economic growth strength as well as the cities along The Yangtze River. However, the relative development rate of Wuhan city area is still far higher than other cities and counties.展开更多
Based on Arc GIS and SPSS Statistics,authors of this paper used the principal component analysis(PCA) and the analytic hierarchy process(AHP),and selected 6 indicators concerning population,land,and economy to study t...Based on Arc GIS and SPSS Statistics,authors of this paper used the principal component analysis(PCA) and the analytic hierarchy process(AHP),and selected 6 indicators concerning population,land,and economy to study the spatial pattern of urbanization and regional economic differences in Shandong Province,namely urban population,urban population density,construction land,area of urban districts,disposable income of residents,and added value of the tertiary industry.The development of urbanization in Shandong Province was measured by the proportion of urban population to the total population in 2000,2005,2010,and 2014 respectively.It is hoped that this paper will provide a theoretical basis for building an orderly regional spatial structure and coordinating regional urban decision-making.展开更多
Based on the population census data,this paper analyzed the influencing factors and urbanization effects of the floating population in Anhui Province using ArcGIS spatial analysis,factor analysis,multiple liner regres...Based on the population census data,this paper analyzed the influencing factors and urbanization effects of the floating population in Anhui Province using ArcGIS spatial analysis,factor analysis,multiple liner regression,and spatial autocorrelation,and reached the following conclusions:① From 2000 to 2010,the floating population in Anhui Province was concentrated in cities dotted the Huai River and the Yangtze River,and Hefei City absorbed the most inter-provincial floating population and intra-provincial floating population.② The overall economic strength had the greatest impact on attracting floating population,while the income level factor has less impact on attracting floating population.The overall economic strength and the strength of science,education,culture,and health of prefecture-level cities in Anhui Province were more attractive to the intra-provincial floating population and less attractive to the inter-provincial floating population.③ Population mobility promoted urbanization.Large cities could attract more migrants from counties.The urban population system in Anhui Province was generally developing towards the concentration of large cities,while the proportion of the county population in the total population was decreased.展开更多
This study has revealed spatial-temporal changes in Recreational Business Dis- tricts （RBDs） in Beijing and examined the relationship between the location of urban RBDs and traffic conditions, resident and tourist d...This study has revealed spatial-temporal changes in Recreational Business Dis- tricts （RBDs） in Beijing and examined the relationship between the location of urban RBDs and traffic conditions, resident and tourist density, scenic spots, and land prices. A more reasonable classification of urban RBDs （LSC, CPS, and ULA） is also proposed. Quantitative methods such as Gini Coefficient, Spatial Interpolation, Kernel Density Estimation, and Geographical Detector were employed to collect and analyze the data from three types of urban RBDs in Beijing in 1990, 2000, and 2014, respectively, and the spatial-temporal pat- terns as well as the distribution characteristics of urban RBDs were analyzed using ArcGIS software. It was concluded that （1） both the number and scale of urban RBDs in Beijing have been expanding and the trend for all types of urban RBDs in Beijing to be spatially agglom- erated is continuing; （2） the spatial-temporal evolution pattern of urban RBDs in Beijing is ＂single-core agglomeration-dual-core agglomeration-multi-core diffusion＂; and （3） urban RBDs were always located in areas with low traffic density, tourist attractions, high resident and tourist population density, and relatively high land valuations; these factors also affect the scale size of RBDs.展开更多
China has been experiencing an unprecedented urbanization process. In 2011, China＇s urban population reached 691 million with an urbanization rate of 51.27%. Urbaniza- tion level is expected to increase to 70% in Chi...China has been experiencing an unprecedented urbanization process. In 2011, China＇s urban population reached 691 million with an urbanization rate of 51.27%. Urbaniza- tion level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China＇s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its ＂one-child policy＂ gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environ- mental protection. In this paper, a top-down method is developed to project the spatial dis- tribution of China＇s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results sug- gested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities Fast Changing Populated Region （FCPR）, Low Changing Populated Region （LCPR） and Inactive Populated Region （IPR）. In the FCPR, China＇s population is projected to continue to concentrate in net immigration leading type （NILT） area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type （NELT） area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emi- gration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km^2.展开更多
In this paper,we use factor analysis to evaluate the urban comprehensive quality of each city in the Lanzhou-Xining(Lan-Xi)urban agglomeration.The time distance was obtained by using GIS spatial analysis,and the struc...In this paper,we use factor analysis to evaluate the urban comprehensive quality of each city in the Lanzhou-Xining(Lan-Xi)urban agglomeration.The time distance was obtained by using GIS spatial analysis,and the structure and pattern of the spatial network were analyzed by using the gravity model and social network analysis method.The results show that:1)The scale effect of the Lan-Xi urban agglomeration is gradually emerging,and it is gradually forming the urban agglomeration with Lanzhou and Xining as the core,the Lan-Xi high-speed railway as the axis,and a high-dense connection.2)Lanzhou and Xining are at the core of the Lan-Xi urban agglomeration,which has a strong attraction and spreads to neighboring cities.3)In the network structure of the Lan-Xi urban agglomeration,Lanzhou,Baiyin,Gaolan,Yuzhong,Yongdeng,Dingxi,Lintao,Xining,Ledu,Huangzhong,Ping’an,Minhe and Datong are located in the network core position,which have the superiority position and lead to the entire regional communication enhancement and the regional integration development.4)This urban agglomeration has significant subgroups,eight tertiary subgroups and four secondary subgroup;the tertiary subgroups which compose secondary subgroup have a close connection and mutually influence each other.5)The Lanzhou Metropolitan Area and the Xining Metropolitan Area have an important impact on the surrounding cities,and the peripheral cities are basically controlled by the central city.The Dingxi subgroup,Lintao-Linxia subgroup,Gonghe subgroup have more structural holes than the subgroups within the Lanzhou Metropolitan Area and the Xining Metropolitan Area,so the peripheral cities of these subgroups have relatively less connection with surrounding cities.展开更多
The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly ...The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of China’s social economy. However, the existing research on the RCUED lacks the fine depiction of the county-level administrative units.Using 2000 and 2010 census data and the statistical analysis method, we uncovered the evolution characteristics of China’s urbanization and economic development and conducted a quantitative identification for the RCUED with improved methods using the quadrant map approach. In addition, we investigated the spatial correlation effect of the RCUED using the spatial autocorrelation analysis method. The results were as follows: 1) In general, a high degree of matching exists between China’s urbanization and economic development at the county level at the significance level of 0.01. The correlation coefficients between China’s urbanization and economic development in2000 and 2010 were 0.608 and 0.603, respectively. 2) A significant regional difference exists in the RCUED at the county level. Based on a comparative analysis of 2276 county units in China in the two years, we found that county units can be categorized as under-urbanized, basic coordination and over-urbanized in various areas. No situation was observed where urbanization seriously lagged behind the economic development level, so the levels of urbanization and economic development appear to be basically coordinated,and the coordination state may be gradually optimized over time. 3) Over time, the spatial dependency of the RCUED has weakened and the spatial heterogeneity has increased. Northeast China has always been an area characterized by over-urbanization. The number of county units classified as under-urbanized has begun to decline in eastern coastal urban agglomeration areas, while counties rich in resources have transformed from having point-shaped over-urbanization to plane-shaped under-urbanization along the northern border,and the number of over-urbanized county units has increased in the middle reaches of the Yangtze River. 4)’Lag-lag’ type and ’advance-advance’ type accounted for 68% of all counties in China, and these counties were shown to have obvious spatial differentiation characteristics.展开更多
Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot disti...Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ＇population, land use and time （daytime or night）＇ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows： （1） The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. （2） Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. （3） The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.展开更多
The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic ...The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis （SFA） in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt （YREB） and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of ad- ditional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a ＂bar-like＂ distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran＇s / within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association （LISA） statistic has enabled us to quantify characteristics of ＂small agglomeration and large dispersion＂. Thus, ＂high- high＂ （H-H） agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by ＂low-low＂ （L-L） patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.展开更多
The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study ...The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.展开更多
Impervious surfaces are the result of urbanization that can be explicitly quantified, managed and controlled at each stage of land development. It is a very useful environmental indicator that can be used to measure t...Impervious surfaces are the result of urbanization that can be explicitly quantified, managed and controlled at each stage of land development. It is a very useful environmental indicator that can be used to measure the impacts of urbanization on surface runoff, water quality, air quality, biodiversity and rnicroclimate. Therefore, accurate estimation of impervious surfaces is critical for urban environmental monitoring, land management, decision-making and urban planning. Many approaches have been developed to estimate surface imperviousness, using remotely sensed data with various spatial resolutions. However, few studies, have investigated the effects of spatial resolution on estimating surface imperviousness. We compare medium-resolution Landsat data with high-resolution SPOT images to quantify the imperviousness in Beijing, China. The results indicated that the overall 91% accuracy of estimates of imperviousness based on TM data was considerably higher than the 81% accuracy of the SPOT data. The higher resolution SPOT data did not always predict the imperviousness of the land better than the TM data. At the whole city level, the TM data better predicts the percentage cover of impervious surfaces. At the sub-city level, however, the ring belts from the central core to the urban-rural peripheral, the SPOT data may better predict the imperviousness. These results highlighted the need to combine multiple resolution data to quantify the percentage of imperviousness, as higher resolution data do not necessarily lead to more accurate estimates. The methodology and results in this study can be utilized to identify the most suitable remote sensing data to quickly and efficiently extract the pattern of the impervious land, which could provide the base for further study on many related urban environmental problems.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41001100,41371183)Humanities and Social Sciences Foundation of Ministry of Education in China(No.15YJCZH174)+1 种基金Humanities Sciences Foundation of Ministry of Hubei Province(No.15YJCZH174)Fundamental Research Funds for the Central Universities(No.CCNU15A06069,CCNU15ZD001)
文摘This paper intends to investigate the urban spatial patterns of Hubei Province and its evolution from three different perspectives: urban nodes, urban connections and urban clusters. The research adopts nighttime light imagery of cities in Hubei Province, the viewpoint of ′point-axis-area′ in the ′point-axis system′ theory, and employs light index model, gravity model and social network analysis. The findings are as follows: 1) In terms of urban nodes, the urbanization process of Hubei has been carried out mainly on the basis of external expansion rather than internal increasing. The polarization trend of urban connection network is strengthening. 2) As for urban connections, the estimation of urban connections using light index model is capable of containing various actual flow, and the connections are getting increasingly closer. 3) In regard to urban groups, seven urban groups of varying sizes have formed. On that basis, three stable and relatively independent urban groups as the centers, namely Wuchang, Yichang and Xiangyang emerge as well. But the structures of ′Wuhan Metropolitan Area′, ′Yichang-Jingzhou-Jingmen City Group′ and ′Xiangyang-Shiyen-Suizhou City Group′, which are defined by local development strategy in Hubei Province, are different from the above three urban groups.
基金Under the auspices of National Natural Science Foundation of China(No.40901088,41271174)
文摘This article presents the findings of a study of the spheres of urban influence with regard to all cities in China(not including Hong Kong,Macao and Taiwan Province of China)in the years 1990,2000 and 2009.An optimized gravity model with comprehensive time distance was used to carry out a detailed analysis of the spatial patterns of Chinese spheres of urban influence and the spatial characteristics of urban agglomerations.Such urban agglomerations are characterized by high density population and a developed economy,which are also considered as the national competition unit.This paper initially identifies four spatial patterns of urban agglomerations based on the spatial layout of city groups during their evolution.Some basic characteristics of urban agglomerations are outlined,including the number of cities,the size of cities and the functions of urban centers.These characteristics are examined by using statistical methods and Geographic Information System(GIS).The main findings from this research are that the development stages and structures of urban agglomerations in China vary significantly.It is also clear that the stages and evolution of spatial patterns are strongly affected and dominated by both policy and location factors.
基金The Knowledge Innovation Project of CAS, No.KZCX2-310-01, No.KZCX2-307 National Natural Science Foundation of China, No. 40101010
文摘By using digitized land use maps of Beijing in 1982, 1992 and 1997 and employing GIS spatial analysis techniques, this paper conducts an empirical study on the spatial differentiation and spatial patterns of urban land use growth in Beijing in the period of 1982–1997. It is observed that urban land use growth in Beijing went beyond the control of urban planning, in terms of the extraordinary high growth rate and undesired spatial pattern. The rate of urban expansion after 1982, which was predominated by growth of industrial land, was extraordinary high compared to its historical period. While its growth centers have been actively shifting toward the northern part, rather than toward the southern and eastern parts as designated by the latest General Plan (1991–2010) of Beijing, its spatial pattern of urban land use growth in general was in distinct concentric sprawl, which seriously violated the General Plan of Beijing.
基金supported by the National Natural Science Foundation of China(No.40971041)
文摘Negative air ions are natural components of the air we breathe Forests are the main continuous natural source of negative air ions （NAI）. The spatio-temporal patterns of negative air ions were explored in Shanghai, based on monthly monitoring in 15 parks from March 2009 to February 2010. In each park, sampling sites were selected in forests and open spaces. The annual variation in negative air ion concentrations （NAIC） showed peak values from June to October and minimum values from December to January. NAIC were highest in summer and autumn, intermediate in spring, and lowest in winter. During spring and summer, NAIC in open spaces were significantly higher in rural areas than those in suburban areas. However, there were no significant differences in NAIC at forest sites among seasons. For open spaces, total suspended particles （TSP） were the dominant determining factor of NAIC in sum- mer, and air temperature and air humidity were the dominant determining factors of NAIC in spring, which were tightly correlated with Shanghai＇s ongoing urbanization and its impacts on the environment. R is suggested that urbanization could induce variation in NAIC along the urban-rural gradient, but that may not change the temporal variation pattern. Fur- thermore, the effects of urbanization on NAIC were limited in non-vegetated or less-vegetated sites, such as open spaces, but not in well-vegetated areas, such as urban forests. Therefore, we suggest that urban greening, especially urban forest, has significant resistance to theeffect of urbanization on NAIC.
文摘Based on the night light data, urban area data, and economic data of Wuhan Urban Agglomeration from 2009 to 2015, we use spatial correlation dimension, spatial self-correlation analysis and weighted standard deviation ellipse to identify the general characteristics and dynamic evolution characteristics of urban spatial pattern and economic disparity pattern. The research results prove that: between 2009 and 2013, Wuhan Urban Agglomeration expanded gradually from northwest to southeast and presented the dynamic evolution features of “along the river and the road”. The spatial structure is obvious, forming the pattern of “core-periphery”. The development of Wuhan Urban Agglomeration has obvious imbalance in economic geography space, presenting the development tendency of “One prominent, stronger in the west and weaker in the east”. The contract within Wuhan Urban Agglomeration is gradually decreased. Wuhan city and its surrounding areas have stronger economic growth strength as well as the cities along The Yangtze River. However, the relative development rate of Wuhan city area is still far higher than other cities and counties.
基金Sponsored by Research Project of Binzhou University(BZXYL1501)
文摘Based on Arc GIS and SPSS Statistics,authors of this paper used the principal component analysis(PCA) and the analytic hierarchy process(AHP),and selected 6 indicators concerning population,land,and economy to study the spatial pattern of urbanization and regional economic differences in Shandong Province,namely urban population,urban population density,construction land,area of urban districts,disposable income of residents,and added value of the tertiary industry.The development of urbanization in Shandong Province was measured by the proportion of urban population to the total population in 2000,2005,2010,and 2014 respectively.It is hoped that this paper will provide a theoretical basis for building an orderly regional spatial structure and coordinating regional urban decision-making.
文摘Based on the population census data,this paper analyzed the influencing factors and urbanization effects of the floating population in Anhui Province using ArcGIS spatial analysis,factor analysis,multiple liner regression,and spatial autocorrelation,and reached the following conclusions:① From 2000 to 2010,the floating population in Anhui Province was concentrated in cities dotted the Huai River and the Yangtze River,and Hefei City absorbed the most inter-provincial floating population and intra-provincial floating population.② The overall economic strength had the greatest impact on attracting floating population,while the income level factor has less impact on attracting floating population.The overall economic strength and the strength of science,education,culture,and health of prefecture-level cities in Anhui Province were more attractive to the intra-provincial floating population and less attractive to the inter-provincial floating population.③ Population mobility promoted urbanization.Large cities could attract more migrants from counties.The urban population system in Anhui Province was generally developing towards the concentration of large cities,while the proportion of the county population in the total population was decreased.
基金Foundation： National Natural Science Foundation of China, No.41071110
文摘This study has revealed spatial-temporal changes in Recreational Business Dis- tricts （RBDs） in Beijing and examined the relationship between the location of urban RBDs and traffic conditions, resident and tourist density, scenic spots, and land prices. A more reasonable classification of urban RBDs （LSC, CPS, and ULA） is also proposed. Quantitative methods such as Gini Coefficient, Spatial Interpolation, Kernel Density Estimation, and Geographical Detector were employed to collect and analyze the data from three types of urban RBDs in Beijing in 1990, 2000, and 2014, respectively, and the spatial-temporal pat- terns as well as the distribution characteristics of urban RBDs were analyzed using ArcGIS software. It was concluded that （1） both the number and scale of urban RBDs in Beijing have been expanding and the trend for all types of urban RBDs in Beijing to be spatially agglom- erated is continuing; （2） the spatial-temporal evolution pattern of urban RBDs in Beijing is ＂single-core agglomeration-dual-core agglomeration-multi-core diffusion＂; and （3） urban RBDs were always located in areas with low traffic density, tourist attractions, high resident and tourist population density, and relatively high land valuations; these factors also affect the scale size of RBDs.
基金Key Program of the National Natural Science Foundation of China, No.71433008 Key Research Program of the Chinese Academy of Sciences, No.KZZD-EW-06-04+2 种基金 National Natural Science Foundation of China, No.41271174 National Key Technology R＆D Program, No.2012BAI32B06 Beijing Planning of Philosophy and Social Science, No. 13CSC011
文摘China has been experiencing an unprecedented urbanization process. In 2011, China＇s urban population reached 691 million with an urbanization rate of 51.27%. Urbaniza- tion level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China＇s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its ＂one-child policy＂ gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environ- mental protection. In this paper, a top-down method is developed to project the spatial dis- tribution of China＇s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results sug- gested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities Fast Changing Populated Region （FCPR）, Low Changing Populated Region （LCPR） and Inactive Populated Region （IPR）. In the FCPR, China＇s population is projected to continue to concentrate in net immigration leading type （NILT） area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type （NELT） area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emi- gration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km^2.
基金Under the auspices of National Natural Science Foundation of China(No.41771130)
文摘In this paper,we use factor analysis to evaluate the urban comprehensive quality of each city in the Lanzhou-Xining(Lan-Xi)urban agglomeration.The time distance was obtained by using GIS spatial analysis,and the structure and pattern of the spatial network were analyzed by using the gravity model and social network analysis method.The results show that:1)The scale effect of the Lan-Xi urban agglomeration is gradually emerging,and it is gradually forming the urban agglomeration with Lanzhou and Xining as the core,the Lan-Xi high-speed railway as the axis,and a high-dense connection.2)Lanzhou and Xining are at the core of the Lan-Xi urban agglomeration,which has a strong attraction and spreads to neighboring cities.3)In the network structure of the Lan-Xi urban agglomeration,Lanzhou,Baiyin,Gaolan,Yuzhong,Yongdeng,Dingxi,Lintao,Xining,Ledu,Huangzhong,Ping’an,Minhe and Datong are located in the network core position,which have the superiority position and lead to the entire regional communication enhancement and the regional integration development.4)This urban agglomeration has significant subgroups,eight tertiary subgroups and four secondary subgroup;the tertiary subgroups which compose secondary subgroup have a close connection and mutually influence each other.5)The Lanzhou Metropolitan Area and the Xining Metropolitan Area have an important impact on the surrounding cities,and the peripheral cities are basically controlled by the central city.The Dingxi subgroup,Lintao-Linxia subgroup,Gonghe subgroup have more structural holes than the subgroups within the Lanzhou Metropolitan Area and the Xining Metropolitan Area,so the peripheral cities of these subgroups have relatively less connection with surrounding cities.
基金Under the auspices of the Strategic Priority Research Program of Chinese Academy of Sciences,Pan-Third Pole Environment Study for a Green Silk Road(Pan-TPE)(No.XDA20040400)
文摘The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of China’s social economy. However, the existing research on the RCUED lacks the fine depiction of the county-level administrative units.Using 2000 and 2010 census data and the statistical analysis method, we uncovered the evolution characteristics of China’s urbanization and economic development and conducted a quantitative identification for the RCUED with improved methods using the quadrant map approach. In addition, we investigated the spatial correlation effect of the RCUED using the spatial autocorrelation analysis method. The results were as follows: 1) In general, a high degree of matching exists between China’s urbanization and economic development at the county level at the significance level of 0.01. The correlation coefficients between China’s urbanization and economic development in2000 and 2010 were 0.608 and 0.603, respectively. 2) A significant regional difference exists in the RCUED at the county level. Based on a comparative analysis of 2276 county units in China in the two years, we found that county units can be categorized as under-urbanized, basic coordination and over-urbanized in various areas. No situation was observed where urbanization seriously lagged behind the economic development level, so the levels of urbanization and economic development appear to be basically coordinated,and the coordination state may be gradually optimized over time. 3) Over time, the spatial dependency of the RCUED has weakened and the spatial heterogeneity has increased. Northeast China has always been an area characterized by over-urbanization. The number of county units classified as under-urbanized has begun to decline in eastern coastal urban agglomeration areas, while counties rich in resources have transformed from having point-shaped over-urbanization to plane-shaped under-urbanization along the northern border,and the number of over-urbanized county units has increased in the middle reaches of the Yangtze River. 4)’Lag-lag’ type and ’advance-advance’ type accounted for 68% of all counties in China, and these counties were shown to have obvious spatial differentiation characteristics.
基金National Natural Science Foundation of China, No.41271174 National Science and Technology Support Program, No.2012BAI32B07
文摘Urban population during the daytime and at night and their spatial distribution are important bases for planning urban infrastructure, public services and disaster relief. As current population statistics cannot distinguish urban population during the daytime from that at night, existed research in this field are quite limited. This paper tries to advance studies at this aspect by establishing a relationship model for the three components of ＇population, land use and time （daytime or night）＇ to explore the temporal and spatial characteristics of different types of population, which is aimed to estimate urban population during the daytime and at night and to analyze their spatial characteristics at grid scale. Furthermore, an empirical case study has been carried out at the Haidian District in Beijing, China to test the model. The results are as follows： （1） The spatial structure of urban population during the daytime is significantly different from that at night. The spatial distribution of urban population during the daytime is more extensive and more agglomerated that that at night. （2） Several types of spatial coupling relationship between population during the daytime and that at night have been identified, such as sandwich mode, symmetry mode, convergence mode and single mode, etc. （3） The spatial distribution of daytime and nighttime population also reflects certain factors during the development of China, such as the distribution of old residential areas, the construction of new industrial districts, and the differences between urban and rural areas, which can provide reference points for studies in this field and other regional research.
基金National Natural Science Foundation of China,No.41501593,No.41601592National Program on Key Research Project,No.2016YFA0602500
文摘The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis （SFA） in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt （YREB） and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of ad- ditional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a ＂bar-like＂ distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran＇s / within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association （LISA） statistic has enabled us to quantify characteristics of ＂small agglomeration and large dispersion＂. Thus, ＂high- high＂ （H-H） agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by ＂low-low＂ （L-L） patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.
文摘The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.
基金supported by the National Basic Research Program (973) of China (No. 2008CB418104)the Major Programs of the Chinese Academy of Sciences (No. KZCX1-YW-14-4-1)the National Natural Science Foundation of China (No. 40901265)
文摘Impervious surfaces are the result of urbanization that can be explicitly quantified, managed and controlled at each stage of land development. It is a very useful environmental indicator that can be used to measure the impacts of urbanization on surface runoff, water quality, air quality, biodiversity and rnicroclimate. Therefore, accurate estimation of impervious surfaces is critical for urban environmental monitoring, land management, decision-making and urban planning. Many approaches have been developed to estimate surface imperviousness, using remotely sensed data with various spatial resolutions. However, few studies, have investigated the effects of spatial resolution on estimating surface imperviousness. We compare medium-resolution Landsat data with high-resolution SPOT images to quantify the imperviousness in Beijing, China. The results indicated that the overall 91% accuracy of estimates of imperviousness based on TM data was considerably higher than the 81% accuracy of the SPOT data. The higher resolution SPOT data did not always predict the imperviousness of the land better than the TM data. At the whole city level, the TM data better predicts the percentage cover of impervious surfaces. At the sub-city level, however, the ring belts from the central core to the urban-rural peripheral, the SPOT data may better predict the imperviousness. These results highlighted the need to combine multiple resolution data to quantify the percentage of imperviousness, as higher resolution data do not necessarily lead to more accurate estimates. The methodology and results in this study can be utilized to identify the most suitable remote sensing data to quickly and efficiently extract the pattern of the impervious land, which could provide the base for further study on many related urban environmental problems.
