Urban sprawl is a critical challenge in the urban development trajectory of developing countries,necessitating precise measurement,trend projection,and strategic management to achieve sustainable urban growth.This stu...Urban sprawl is a critical challenge in the urban development trajectory of developing countries,necessitating precise measurement,trend projection,and strategic management to achieve sustainable urban growth.This study focuses on the Yangtze River Economic Belt(YREB)as a case region and introduces a comprehensive evaluation framework that incorporates multidimensional factors and addresses the scale effects of urban sprawl.We emphasize the value of a systematic geographical approach by quantifying urban sprawl through simulated scenarios and analyzing its driving factors.We constructed an innovative urban sprawl index(USI)to assess the degree of sprawl within the YREB.This assessment integrates two geographic models with an artificial neural network algorithm,enabling simulation of urban sprawl trends under two future scenarios for 2035.Additionally,two analytical methods were employed to identify the key driving mechanisms of urban sprawl in the region.Findings indicate a strong correlation between urban scale and the extent of urban sprawl:larger urban areas exhibit more pronounced sprawl,with agglomeration and morphological transformations identified as primary contributors to urban sprawl.The study further reveals an intricate association between urban sprawl and the compactness of urban internal structures.While both development scenarios offer distinct advantages,the Coordinated Development Scenario is projected to foster a more balanced urban expansion.The robustness of the evaluation framework was enhanced through simulation and an in-depth analysis of internal mechanisms,bolstering confidence in its applicability.We advocate for the adoption and continued refinement of this framework as a tool for promoting balanced urban growth.The strategic recommendations provided herein are vital for mitigating multi-scale urban sprawl,advancing economic development,and improving residents’quality of life across cities in the YREB.展开更多
The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis ...The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis （SBM-DEA） has been widely used in energy efficiency and environmental efficiency analyses in recent years. Based on this model, data from 316 cities were examined and a category method was employed involving three different sorting techniques to empirically evaluate the efficiency of urban water re- source utilization in China between 2000 and 2012. The overall efficiency （OE） of urban water resource utilization in China was initially low, but has improved over the past decade. The scale efficiency （SE） was higher than the pure technological efficiency （PTE）; PTE is a major determining factor of OE, and has had an increasingly significant effect. The efficiency of water resource utilization varied ac- cording to the region, urban scale, and economic function. The OE score for the eastern China was higher than for the rest of the region, and the OE score for the western China was higher than for the central China. The OE score for urban water resource utilization has improved with urban expansion, except in the case of small cities. The SE showed an inverted U-shaped＇ trend with increasing urban expansion. The OE of urban water utilization in comprehensive functional cities was greater than in economic specialization cities, and was greater in heavy industry specialization cities than in other specialization cities. This study contributes to the field of urban water resource management by examining variations in efficiency with urban ~ezle展开更多
The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the externa...The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.展开更多
Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules fo...Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population.To date,only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters.Using multiple urban-sensed and human-sensed data,this study proposes a thorough framework for quantifying the scaling laws in a city.To begin,urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data.To demonstrate the spatiotemporal variability of urban mobility,various network-based mobility measures are proposed.Following that,three different features of urban mobility laws are exposed,explaining spatial agglomeration,spatial hierarchical structures,and the temporal growth process.The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data.Applying this framework to the case study of Shenzhen,China revealed(a)spatial travel heterogeneity,hierarchical spatial structures,and mobility growth,and(b)not only a robust sub-linear relationship between infrastructure volume and population,but also a sub-linear relationship for socioeconomic activity.The identified scaling laws,both in terms of mobility measures and urban indicators,provide a multi-faceted portrait of the spatio-temporal variations of urban settings,allowing us to better understand intra-urban developments and,consequently,provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future.展开更多
The “Monitoring City Walls” research project by the University of Pisa approaches planned conservation as a process that pursues an in-depth understanding of historic city walls and their surroundings to define a sy...The “Monitoring City Walls” research project by the University of Pisa approaches planned conservation as a process that pursues an in-depth understanding of historic city walls and their surroundings to define a system of effective risk prevention. This multidisciplinary research adopts monitoring strategies and technologies at the large scale and in relationship to natural and urban conditions. The underlying logic frames the conservation of these historic fortifications within the more general mitigation of risks generated by context. The research aims to develop an innovative approach to monitoring ancient defensive structures in historical towns. The integrated use of advanced technologies allows for the control and, most importantly, advance identification of possible risks. These new technologies, in particular satellite interferometry, make it possible to improve and increase the operational capacity of monitoring processes by facilitating the acquisition and investigation of data relative to the system defined by ancient city walls and their surroundings. These technologies also represent a cost-effective tool for managing the important transition from the observation and study of individual monuments to the monitoring of large monumental complexes or even entire historical centers.展开更多
In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas emissions.Occupant behavior has drawn increasing research interests due to...In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas emissions.Occupant behavior has drawn increasing research interests due to its impacts on the building energy consumption.However,occupant behavior study at urban scale remains a challenge,and very limited studies have been conducted.As an effort to couple big data analysis with human mobility modeling,this study has explored urban scale human mobility utilizing three months Global Positioning System(GPS)data of 93,o00 users at Phoenix Metropolitan Area.This research extracted stay points from raw data,and identified users'home,work,and other locations by Density-Based Spatial Clustering algorithm.Then,daily mobility patterns were constructed using different types of locations.We propose a novel approach to predict urban scale daily human mobility patterns with 12-hour prediction horizon,using Long Short-Term Memory(LSTM)neural network model.Results shows the developed models achieved around 85%average accuracy and about 86%mean precision.The developed models can be further applied to analyze urban scale occupant behavior,building energy demand and flexibility,and contributed to urban planning.展开更多
Current approaches for simulating the energy performance of buildings on a large scale are limited by numerous assumptions and simplifications,which can lead to inaccurate estimations.While new tools and procedures ar...Current approaches for simulating the energy performance of buildings on a large scale are limited by numerous assumptions and simplifications,which can lead to inaccurate estimations.While new tools and procedures are emerging to improve accuracy,there remains a need for more user-friendly methods.This study proposes a new tool based on online maps to create the geometry of districts in a simple way.The tool also enables an automatic evaluation of all buildings through dynamic hourly simulations,using a building simulation software and allowing to consider different weather conditions.To illustrate the procedure,a district at risk of energy poverty in Seville(Spain)is modeled,where hourly temperature data for a whole year are available to demonstrate the need for building improvements.The tool is used to evaluate the energy demands of the district under several retrofitting alternatives,and free-floating simulations are also performed to evaluate the improvement of thermal comfort without air-conditioning systems.The aim is not to discuss the actual values for this particular case,but rather to identify the correct direction for large-scale studies,so as to make them more easily conducted.Overall,it may be concluded that the results provided by comprehensive tools,such as the one proposed in this study,enable easy yet accurate evaluations of buildings on a large scale with significant time savings,as well as the identification of locations where retrofitting interventions would have the greatest impact.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.U24A20580)National Natural Science Foundation of China(Grant No.42171298)+1 种基金Natural Science Foundation of Chongqing,China(Grant No.CSTB2023NSCQLZX0009)Philosophy and Social Science Major Project of Chongqing Municipal Education Commission(Grant No.24SKZDZX04).
文摘Urban sprawl is a critical challenge in the urban development trajectory of developing countries,necessitating precise measurement,trend projection,and strategic management to achieve sustainable urban growth.This study focuses on the Yangtze River Economic Belt(YREB)as a case region and introduces a comprehensive evaluation framework that incorporates multidimensional factors and addresses the scale effects of urban sprawl.We emphasize the value of a systematic geographical approach by quantifying urban sprawl through simulated scenarios and analyzing its driving factors.We constructed an innovative urban sprawl index(USI)to assess the degree of sprawl within the YREB.This assessment integrates two geographic models with an artificial neural network algorithm,enabling simulation of urban sprawl trends under two future scenarios for 2035.Additionally,two analytical methods were employed to identify the key driving mechanisms of urban sprawl in the region.Findings indicate a strong correlation between urban scale and the extent of urban sprawl:larger urban areas exhibit more pronounced sprawl,with agglomeration and morphological transformations identified as primary contributors to urban sprawl.The study further reveals an intricate association between urban sprawl and the compactness of urban internal structures.While both development scenarios offer distinct advantages,the Coordinated Development Scenario is projected to foster a more balanced urban expansion.The robustness of the evaluation framework was enhanced through simulation and an in-depth analysis of internal mechanisms,bolstering confidence in its applicability.We advocate for the adoption and continued refinement of this framework as a tool for promoting balanced urban growth.The strategic recommendations provided herein are vital for mitigating multi-scale urban sprawl,advancing economic development,and improving residents’quality of life across cities in the YREB.
基金Key Research Program of Chinese Academy of Sciences(No.KZZD-EW-06-03-03)
文摘The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis （SBM-DEA） has been widely used in energy efficiency and environmental efficiency analyses in recent years. Based on this model, data from 316 cities were examined and a category method was employed involving three different sorting techniques to empirically evaluate the efficiency of urban water re- source utilization in China between 2000 and 2012. The overall efficiency （OE） of urban water resource utilization in China was initially low, but has improved over the past decade. The scale efficiency （SE） was higher than the pure technological efficiency （PTE）; PTE is a major determining factor of OE, and has had an increasingly significant effect. The efficiency of water resource utilization varied ac- cording to the region, urban scale, and economic function. The OE score for the eastern China was higher than for the rest of the region, and the OE score for the western China was higher than for the central China. The OE score for urban water resource utilization has improved with urban expansion, except in the case of small cities. The SE showed an inverted U-shaped＇ trend with increasing urban expansion. The OE of urban water utilization in comprehensive functional cities was greater than in economic specialization cities, and was greater in heavy industry specialization cities than in other specialization cities. This study contributes to the field of urban water resource management by examining variations in efficiency with urban ~ezle
基金National Natural Science Foundation of China,No.42371222,No.41971167Fundamental Scientific Research Funds of Central China Normal University,No.CCNU24ZZ120,No.CCNU22JC026。
文摘The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.
基金supported by the National Natural Science Foundation of China[grant numbers 42001393,42071360,71961137003 and 42101472]the Basic Research Program of Shenzhen Science and Technology Innovation Committee[grant number JCYJ20220530152817039]+1 种基金the Natural Science Foundation of Guangdong Province[grant number 2019A1515011049]the Key Laboratory of National Geographic Census and Monitoring,MNR[grant number 2020NGCMZD02].
文摘Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population,infrastructure,and socioeconomic activities.Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with population.To date,only limited research has empirically explored the scaling relations between variables of urban mobility in mega-cities at an intra-urban scale of a few meters.Using multiple urban-sensed and human-sensed data,this study proposes a thorough framework for quantifying the scaling laws in a city.To begin,urban mobility networks are built by aggregating population flows using large-scale mobile phone tracking data.To demonstrate the spatiotemporal variability of urban mobility,various network-based mobility measures are proposed.Following that,three different features of urban mobility laws are exposed,explaining spatial agglomeration,spatial hierarchical structures,and the temporal growth process.The scaling correlations between urban indicators pertaining to socioeconomic features and infrastructure and a mobility-population measure are then quantified using multi-sourced urban-sensed data.Applying this framework to the case study of Shenzhen,China revealed(a)spatial travel heterogeneity,hierarchical spatial structures,and mobility growth,and(b)not only a robust sub-linear relationship between infrastructure volume and population,but also a sub-linear relationship for socioeconomic activity.The identified scaling laws,both in terms of mobility measures and urban indicators,provide a multi-faceted portrait of the spatio-temporal variations of urban settings,allowing us to better understand intra-urban developments and,consequently,provide critical policy evaluations and suggestions for improving intra-urban efficiency in the future.
基金Thanks to Jacinto E.Canivell Garcia De Paredes,Emilio Jose Mascort Albea and Rocio Romero Hernandez at the University of Seville for the support provided in defining the digital mapping instruments.
文摘The “Monitoring City Walls” research project by the University of Pisa approaches planned conservation as a process that pursues an in-depth understanding of historic city walls and their surroundings to define a system of effective risk prevention. This multidisciplinary research adopts monitoring strategies and technologies at the large scale and in relationship to natural and urban conditions. The underlying logic frames the conservation of these historic fortifications within the more general mitigation of risks generated by context. The research aims to develop an innovative approach to monitoring ancient defensive structures in historical towns. The integrated use of advanced technologies allows for the control and, most importantly, advance identification of possible risks. These new technologies, in particular satellite interferometry, make it possible to improve and increase the operational capacity of monitoring processes by facilitating the acquisition and investigation of data relative to the system defined by ancient city walls and their surroundings. These technologies also represent a cost-effective tool for managing the important transition from the observation and study of individual monuments to the monitoring of large monumental complexes or even entire historical centers.
基金supported by the U.S.National Science Foundation(Award No.1949372 and No.2125775)in part supported through computational resources provided by Syracuse University.
文摘In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas emissions.Occupant behavior has drawn increasing research interests due to its impacts on the building energy consumption.However,occupant behavior study at urban scale remains a challenge,and very limited studies have been conducted.As an effort to couple big data analysis with human mobility modeling,this study has explored urban scale human mobility utilizing three months Global Positioning System(GPS)data of 93,o00 users at Phoenix Metropolitan Area.This research extracted stay points from raw data,and identified users'home,work,and other locations by Density-Based Spatial Clustering algorithm.Then,daily mobility patterns were constructed using different types of locations.We propose a novel approach to predict urban scale daily human mobility patterns with 12-hour prediction horizon,using Long Short-Term Memory(LSTM)neural network model.Results shows the developed models achieved around 85%average accuracy and about 86%mean precision.The developed models can be further applied to analyze urban scale occupant behavior,building energy demand and flexibility,and contributed to urban planning.
基金The Spanish government funded this study under the projects“LADERA-Large-scale Assessment of plus-energy Districts through Escalation and Replicability in Andalusia”(Grant number US-1380863)and“Constancy-Resilient urbanisation methodologies and natural conditioning using imaginative nature-based solutions and cultural heritage to recover the street life”(Grant number:PID2020-118972RB-I00)funded by MCIN/AEI/10.13039/501100011033Also,this study has been co-financed by the European Regional Development Funds(ERDF).
文摘Current approaches for simulating the energy performance of buildings on a large scale are limited by numerous assumptions and simplifications,which can lead to inaccurate estimations.While new tools and procedures are emerging to improve accuracy,there remains a need for more user-friendly methods.This study proposes a new tool based on online maps to create the geometry of districts in a simple way.The tool also enables an automatic evaluation of all buildings through dynamic hourly simulations,using a building simulation software and allowing to consider different weather conditions.To illustrate the procedure,a district at risk of energy poverty in Seville(Spain)is modeled,where hourly temperature data for a whole year are available to demonstrate the need for building improvements.The tool is used to evaluate the energy demands of the district under several retrofitting alternatives,and free-floating simulations are also performed to evaluate the improvement of thermal comfort without air-conditioning systems.The aim is not to discuss the actual values for this particular case,but rather to identify the correct direction for large-scale studies,so as to make them more easily conducted.Overall,it may be concluded that the results provided by comprehensive tools,such as the one proposed in this study,enable easy yet accurate evaluations of buildings on a large scale with significant time savings,as well as the identification of locations where retrofitting interventions would have the greatest impact.
