Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently so...Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.展开更多
This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of glo...This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.展开更多
Vulnerability is a new field and analytical tool in the study of urban safety. Analysis and assessment of vulnerability provide a new basis for urban planning. This study constructed a quantitative index system for as...Vulnerability is a new field and analytical tool in the study of urban safety. Analysis and assessment of vulnerability provide a new basis for urban planning. This study constructed a quantitative index system for assessing vulnerability, based on the city′s sensitivity and emergency response capacity. City size, density, and spatial form influence a city′s sensitivity to crises and risks, to which vulnerability is positively related. Levels of socio-economic development, infrastructures, and emergency management contribute to a city′s emergency response capacity, with which vulnerability is inversely associated. Vulnerability of 19 large Chinese cities was assessed. Harbin and Shenzhen demonstrated the highest and lowest vulnerability among 19 cities, while Beijing, Shanghai and Guangzhou ranked the 5th, the 9th and the 12th. Spatially, northern cities tended to be more vulnerable than southern cities. And the differences in vulnerability among cities were explored based on cities′ physical geography conditions, level of socioeconomic development, infrastructures, regional status, history of disaster, history of urban planning and development, government policies, etc.展开更多
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 we...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.展开更多
基金supported by the National Natural Science Foundation for Distinguished Young Scholar of China (Grant No.40225004)
文摘Popular regional inequality indexes such as variation coefficient and Gini coefficient can only reveal overall inequality, and have limited ability in revealing spatial dependence or spatial agglomeration. Recently some methods of exploratory spatial data analysis such as spatial autocorrelation have provided effective tools to analyze spatial agglomeration and cluster, which can reveal the pattern of regional inequality. This article attempts to use spatial autocorrelation at county level to get refined spatial pattern of regional disparity in Chinese northeast economic region over 2000-2006 (2001 absent). The result indicates that the basic trend of regional economy is an increasing concentration of growth among counties in northeast economic region, and there are two geographical clusters of poorer counties including the counties in western Liaoning Province and adjacent counties in Inner Mongolia, poorer counties of Heihe, Qiqihar and Suihua in Heilongjiang Province. This article also reveals that we can use the methods of exploratory spatial data analysis as the supplementary analysis methods in regional economic analysis.
文摘This paper summarizes a few spatial statistical analysis methods for to measuring spatial autocorrelation and spatial association, discusses the criteria for the identification of spatial association by the use of global Moran Coefficient, Local Moran and Local Geary. Furthermore, a user-friendly statistical module, combining spatial statistical analysis methods with GIS visual techniques, is developed in Arcview using Avenue. An example is also given to show the usefulness of this module in identifying and quantifying the underlying spatial association patterns between economic units.
基金Under the auspices of National Natural Science Foundation of China (No. 40635030)
文摘Vulnerability is a new field and analytical tool in the study of urban safety. Analysis and assessment of vulnerability provide a new basis for urban planning. This study constructed a quantitative index system for assessing vulnerability, based on the city′s sensitivity and emergency response capacity. City size, density, and spatial form influence a city′s sensitivity to crises and risks, to which vulnerability is positively related. Levels of socio-economic development, infrastructures, and emergency management contribute to a city′s emergency response capacity, with which vulnerability is inversely associated. Vulnerability of 19 large Chinese cities was assessed. Harbin and Shenzhen demonstrated the highest and lowest vulnerability among 19 cities, while Beijing, Shanghai and Guangzhou ranked the 5th, the 9th and the 12th. Spatially, northern cities tended to be more vulnerable than southern cities. And the differences in vulnerability among cities were explored based on cities′ physical geography conditions, level of socioeconomic development, infrastructures, regional status, history of disaster, history of urban planning and development, government policies, etc.
基金Under the auspices of Key Research Program of Chinese Academic of Science(No.KZZD-EW-06-03,KSZD-EW-Z-021-03)Advantage Discipline Project of Hainan Normal University(No.305010048)+2 种基金Key Discipline Project of Hainan(No.3050107048)National Natural Science Foundation of China(No.41201160,41329001)Natural Science Foundation of Hainan Province(No.414189)
文摘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.
