County-level industrial development and structure upgrade is one of the most important issues of revitaliz- ing old industrial base of China. After the cluster analysis on GDP per capita and GDP per area of each count...County-level industrial development and structure upgrade is one of the most important issues of revitaliz- ing old industrial base of China. After the cluster analysis on GDP per capita and GDP per area of each county in Liaoning Province, this paper finds the similarity of population size, land use intensity, and economic development of each county. Location quotient reflects the specialization intensity of industries in each county, and it also reflects the spatial differences of county-level industrial development. Economic development level is higher in the southeast than in the northwest of Liaoning, and the industry driving effect on county-level economy is apparent. The main influenc- ing factors include location, industrial foundation and economic system reform, capital input level, knowledge and technology dissemination, conditions of domestic and overseas markets, population and labor force transfer. Industri- alization is an important approach to urbanization for the counties in Liaoning Province. The proportion of agriculture is much higher in the northwest than in the southeast of Liaoning, so it will be take longer time for counties in the northwest of Liaoning to make industrialization, urbanization and modernization.展开更多
Urban environmental quality research is crucial,as cities become competitive centers concentrating human talent,industrial activity,and financial resources,contributing significantly to national economies.Municipal an...Urban environmental quality research is crucial,as cities become competitive centers concentrating human talent,industrial activity,and financial resources,contributing significantly to national economies.Municipal and government priorities include retaining residents,preventing skilled worker outflow,and meeting the evolving needs of urban populations.The study presents the development and application of a scenario-based spatial analysis tool for assessing urban environmental quality at a detailed spatial scale within the city of Novosibirsk.Using advanced geoinformatics,GIS techniques,and an expert knowledge base,the tool integrates diverse thematic data layers with user-defined scenarios to compute and visualize the Scenario-based Urban Environment Quality Index across 87,905 standardized unit areas.The methodology incorporates comprehensive criteria aligned with existing urban planning frameworks and includes demographic targeting to address the city’s heterogeneous population.Validation against expert evaluations demonstrates high accuracy and consistency,while dynamicmodeling capabilities facilitate monitoring the effects of planned urban development initiatives.This approach bridges a critical gap in urban planning by providing granular,data-driven insights that reflect residents’real needs and spatial inequalities.The tool greatly benefits municipal authorities by enabling evidence-based prioritization of interventions,fostering inclusive and sustainable urban growth,and enhancing transparency and participatory governance.Its implementation as a no-code/low-code QGIS plugin ensures wide accessibility and practical application in strategic urban development,marking a significant advancement in urban environment quality assessment science and practice.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. 40501019)the Knowledge Innovation Key Orientation Program of Chinese Academy of Sciences (No. KZCX2-YW-321-04)
文摘County-level industrial development and structure upgrade is one of the most important issues of revitaliz- ing old industrial base of China. After the cluster analysis on GDP per capita and GDP per area of each county in Liaoning Province, this paper finds the similarity of population size, land use intensity, and economic development of each county. Location quotient reflects the specialization intensity of industries in each county, and it also reflects the spatial differences of county-level industrial development. Economic development level is higher in the southeast than in the northwest of Liaoning, and the industry driving effect on county-level economy is apparent. The main influenc- ing factors include location, industrial foundation and economic system reform, capital input level, knowledge and technology dissemination, conditions of domestic and overseas markets, population and labor force transfer. Industri- alization is an important approach to urbanization for the counties in Liaoning Province. The proportion of agriculture is much higher in the northwest than in the southeast of Liaoning, so it will be take longer time for counties in the northwest of Liaoning to make industrialization, urbanization and modernization.
基金funded by theMinistry of Science and Higher Education of Russia,R&D project number FEFS-2026-0003.
文摘Urban environmental quality research is crucial,as cities become competitive centers concentrating human talent,industrial activity,and financial resources,contributing significantly to national economies.Municipal and government priorities include retaining residents,preventing skilled worker outflow,and meeting the evolving needs of urban populations.The study presents the development and application of a scenario-based spatial analysis tool for assessing urban environmental quality at a detailed spatial scale within the city of Novosibirsk.Using advanced geoinformatics,GIS techniques,and an expert knowledge base,the tool integrates diverse thematic data layers with user-defined scenarios to compute and visualize the Scenario-based Urban Environment Quality Index across 87,905 standardized unit areas.The methodology incorporates comprehensive criteria aligned with existing urban planning frameworks and includes demographic targeting to address the city’s heterogeneous population.Validation against expert evaluations demonstrates high accuracy and consistency,while dynamicmodeling capabilities facilitate monitoring the effects of planned urban development initiatives.This approach bridges a critical gap in urban planning by providing granular,data-driven insights that reflect residents’real needs and spatial inequalities.The tool greatly benefits municipal authorities by enabling evidence-based prioritization of interventions,fostering inclusive and sustainable urban growth,and enhancing transparency and participatory governance.Its implementation as a no-code/low-code QGIS plugin ensures wide accessibility and practical application in strategic urban development,marking a significant advancement in urban environment quality assessment science and practice.
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.
