Pub Date : 2024-10-13DOI: 10.1016/j.apgeog.2024.103435
Yangyan Lin , Xibao Xu , Yan Tan , Minkun Chen
Investigating supply-demand matching and scale effects on ecosystem services (ESs) helps define ecological management zoning objectives and informs policy and further research. This study constructs a framework to clarify the “static-dynamic status” of ES supply-demand matching. With China's Taihu Lake Basin (TLB) as our case study, we focused on three ESs in the water–energy–food nexus: water yield (WY), carbon sequestration (CS), and food provision (FP). By analyzing spatiotemporal variations and scale effects on supply–demand matching, we optimized the ecological management zoning. Over 2000–2020, we found decreases in CS supply and WY demand, but growing supply and demand for the other ESs. The supply–demand ratio declined for FP and CS, but increased for WY. Spatial mismatch at 30 m grid scale may disappear at sub-watershed and county scales. Four ecological management bundles were identified: city bundle (18.20% of TLB), ecological control bundle (26.62%), integrated ecological conservation bundle (20.31%), and WY–FP synergy bundle (34.87%). New theories and methods developed in this study for identifying ecological management zones through integrating both static and dynamic supply and demand relationships along with their matching status are broadly applicable, providing a valuable scientific reference for ecosystem management and policy formulation in a range of geographical settings.
{"title":"Multi-scalar assessment of ecosystem-services supply and demand for establishing ecological management zoning","authors":"Yangyan Lin , Xibao Xu , Yan Tan , Minkun Chen","doi":"10.1016/j.apgeog.2024.103435","DOIUrl":"10.1016/j.apgeog.2024.103435","url":null,"abstract":"<div><div>Investigating supply-demand matching and scale effects on ecosystem services (ESs) helps define ecological management zoning objectives and informs policy and further research. This study constructs a framework to clarify the “static-dynamic status” of ES supply-demand matching. With China's Taihu Lake Basin (TLB) as our case study, we focused on three ESs in the water–energy–food nexus: water yield (WY), carbon sequestration (CS), and food provision (FP). By analyzing spatiotemporal variations and scale effects on supply–demand matching, we optimized the ecological management zoning. Over 2000–2020, we found decreases in CS supply and WY demand, but growing supply and demand for the other ESs. The supply–demand ratio declined for FP and CS, but increased for WY. Spatial mismatch at 30 m grid scale may disappear at sub-watershed and county scales. Four ecological management bundles were identified: city bundle (18.20% of TLB), ecological control bundle (26.62%), integrated ecological conservation bundle (20.31%), and WY–FP synergy bundle (34.87%). New theories and methods developed in this study for identifying ecological management zones through integrating both static and dynamic supply and demand relationships along with their matching status are broadly applicable, providing a valuable scientific reference for ecosystem management and policy formulation in a range of geographical settings.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103435"},"PeriodicalIF":4.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-13DOI: 10.1016/j.apgeog.2024.103436
Jiabei Zhou , Shuang Gao , Shaojian Wang
Carbon emissions present a significant climate challenge for China. As a major source of these emissions, reducing transportation-related carbon output is essential to achieving the country's dual carbon goals. In this context, high-speed rail (HSR) emerges as a green, low-carbon alternative with an increasingly significant role in reducing carbon emissions. This paper explores the impact of HSR station construction on carbon emissions using data from 248 prefecture-level cities from 2003 to 2019, treating the construction as a quasi-natural experiment. Employing a spatial DID model, the research investigates how HSR construction affects carbon emission intensity within the region and in neighboring areas. It also considers socioeconomic factors to understand their mediating roles. The findings reveal that HSR construction significantly reduces regional carbon emissions over time, with long-term and gradually increasing effects. Spatially, HSR also has substantial spillover effects in reducing carbon emissions in adjacent regions. Numerically, HSR reduces carbon emissions by an average of 1.7% in the local region and 2.3% in the surrounding areas. The mechanism analysis indicates that the carbon reduction benefits of HSR stem from a complex interplay of multiple factors, with each selected factor playing a partial mediating role. Notably, the concentration of human capital and the flow of innovation are crucial pathways for regional carbon reduction. However, despite HSR's promotion of industrial structure upgrades and substitution of traditional transportation, these factors have not yet significantly contributed to carbon reduction under current conditions. These results underscore the critical position of HSR in carbon reduction and provide a theoretical foundation for future HSR planning and sustainable development policy formulation.
{"title":"Impact and mechanisms of high-speed rail construction on carbon emissions: A quasi-natural experiment in China","authors":"Jiabei Zhou , Shuang Gao , Shaojian Wang","doi":"10.1016/j.apgeog.2024.103436","DOIUrl":"10.1016/j.apgeog.2024.103436","url":null,"abstract":"<div><div>Carbon emissions present a significant climate challenge for China. As a major source of these emissions, reducing transportation-related carbon output is essential to achieving the country's dual carbon goals. In this context, high-speed rail (HSR) emerges as a green, low-carbon alternative with an increasingly significant role in reducing carbon emissions. This paper explores the impact of HSR station construction on carbon emissions using data from 248 prefecture-level cities from 2003 to 2019, treating the construction as a quasi-natural experiment. Employing a spatial DID model, the research investigates how HSR construction affects carbon emission intensity within the region and in neighboring areas. It also considers socioeconomic factors to understand their mediating roles. The findings reveal that HSR construction significantly reduces regional carbon emissions over time, with long-term and gradually increasing effects. Spatially, HSR also has substantial spillover effects in reducing carbon emissions in adjacent regions. Numerically, HSR reduces carbon emissions by an average of 1.7% in the local region and 2.3% in the surrounding areas. The mechanism analysis indicates that the carbon reduction benefits of HSR stem from a complex interplay of multiple factors, with each selected factor playing a partial mediating role. Notably, the concentration of human capital and the flow of innovation are crucial pathways for regional carbon reduction. However, despite HSR's promotion of industrial structure upgrades and substitution of traditional transportation, these factors have not yet significantly contributed to carbon reduction under current conditions. These results underscore the critical position of HSR in carbon reduction and provide a theoretical foundation for future HSR planning and sustainable development policy formulation.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103436"},"PeriodicalIF":4.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.apgeog.2024.103434
Munazza Fatima , Ömer Ünsal
Diarrhoea is the second most common cause of death among children under five worldwide. About 90 percent of diarrhoeal diseases occur in South Asia and sub-Saharan countries. In Pakistan, it causes almost 53,000 children to die every year. Against this background, this study aimed to analyze the geographical variations in the socio-economic and climatic determinants of under-five diarrhoea cases in districts of Pakistan. We used Generalized Linear Regression (GLR) and Multiscale Geographically Weighted Regression (MGWR) to explore the spatial variation of diarrhoea and its associated determinants. The MGWR model with 10 independent variables outperforms the GLR model (R2 = 0.72) with an adjusted R2 of 0.86. The local accuracy of the MGWR model increases from southwest to northeast. Furthermore among ten selected regressors, significant geographic diversity was found in the determinants of diarrhoea, including altitude, temperature, fever, ARI, and sanitation practices. These insights demand the need for targeted public health interventions, such as immunization campaigns, improved sanitation, and access to clean water and nutritional supplements, poverty eradication, especially in rural and high-risk regions. Future research should employ longitudinal designs and advanced spatial modeling to evaluate the impact of strategies and inform evidence-based policies to reduce the burden of childhood diarrhoea in Pakistan.
{"title":"Geospatial analysis of diarrhoea determinants among children under five in Pakistan using Multiscale Geographically Weighted Regression (MGWR)","authors":"Munazza Fatima , Ömer Ünsal","doi":"10.1016/j.apgeog.2024.103434","DOIUrl":"10.1016/j.apgeog.2024.103434","url":null,"abstract":"<div><div>Diarrhoea is the second most common cause of death among children under five worldwide. About 90 percent of diarrhoeal diseases occur in South Asia and sub-Saharan countries. In Pakistan, it causes almost 53,000 children to die every year. Against this background, this study aimed to analyze the geographical variations in the socio-economic and climatic determinants of under-five diarrhoea cases in districts of Pakistan. We used Generalized Linear Regression (GLR) and Multiscale Geographically Weighted Regression (MGWR) to explore the spatial variation of diarrhoea and its associated determinants. The MGWR model with 10 independent variables outperforms the GLR model (R2 = 0.72) with an adjusted R2 of 0.86. The local accuracy of the MGWR model increases from southwest to northeast. Furthermore among ten selected regressors, significant geographic diversity was found in the determinants of diarrhoea, including altitude, temperature, fever, ARI, and sanitation practices. These insights demand the need for targeted public health interventions, such as immunization campaigns, improved sanitation, and access to clean water and nutritional supplements, poverty eradication, especially in rural and high-risk regions. Future research should employ longitudinal designs and advanced spatial modeling to evaluate the impact of strategies and inform evidence-based policies to reduce the burden of childhood diarrhoea in Pakistan.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103434"},"PeriodicalIF":4.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-07DOI: 10.1016/j.apgeog.2024.103433
Hongchao Xu , Peng Zeng , Fengyun Sun , Hongyu Zhao , Yue Che
Global warming has increased extreme weather events. While the impact of cold waves on humans remains significant, corresponding research is limited. Therefore, the cold exposure risk in residential and working areas of Changchun, China, during a cold wave event was investigated, and geographically weighted regression analysis was used to study the exposure disparities among cold-sensitive populations. Significant differences in cold exposure risk were found between residential and working areas. Cold exposure levels increased with the degree of urbanization. In the first ring, the CEI for residential areas reached 1.82, and for working areas, it was 1.85, indicating the highest exposure risk. Peripheral areas (fourth ring) exhibited much lower exposure risks. In residential areas, low-rent housing residents and women had overexposure rates of 98% and 62%, respectively. In working areas, workers without toilet facilities and unemployed individuals had overexposure rates of 21% and 39%, respectively. These findings highlight the disparities in cold exposure among different regions and social groups during cold waves, providing crucial scientific evidence for urban planning and public health policy development.
{"title":"Population exposure disparities between residential and working areas during a cold wave event in Changchun, China","authors":"Hongchao Xu , Peng Zeng , Fengyun Sun , Hongyu Zhao , Yue Che","doi":"10.1016/j.apgeog.2024.103433","DOIUrl":"10.1016/j.apgeog.2024.103433","url":null,"abstract":"<div><div>Global warming has increased extreme weather events. While the impact of cold waves on humans remains significant, corresponding research is limited. Therefore, the cold exposure risk in residential and working areas of Changchun, China, during a cold wave event was investigated, and geographically weighted regression analysis was used to study the exposure disparities among cold-sensitive populations. Significant differences in cold exposure risk were found between residential and working areas. Cold exposure levels increased with the degree of urbanization. In the first ring, the CEI for residential areas reached 1.82, and for working areas, it was 1.85, indicating the highest exposure risk. Peripheral areas (fourth ring) exhibited much lower exposure risks. In residential areas, low-rent housing residents and women had overexposure rates of 98% and 62%, respectively. In working areas, workers without toilet facilities and unemployed individuals had overexposure rates of 21% and 39%, respectively. These findings highlight the disparities in cold exposure among different regions and social groups during cold waves, providing crucial scientific evidence for urban planning and public health policy development.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103433"},"PeriodicalIF":4.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-05DOI: 10.1016/j.apgeog.2024.103430
De Tong , Yueer Dai , Yue Shen
Most developed megacities have experienced poly-centralization and suburbanization, leading to job-housing mismatches and negative outcomes such as increased commuting distances and frequencies. Recognizing the scarcity of structural analysis concerning the attractiveness of commuting's geographic endpoints, this study examines the diverse impact of the built environment at living and working locations on commuting flows, considering various supply-demand masses and distance levels. Utilizing a Gradient Boosting Decision Tree (GBDT) model, the study highlights the importance of job-housing ratio, POI diversity, and subway station proximity in employment locations, while informal area rates and subway proximity remain significant in residential locations. A three-dimensional analysis further indicates that achieving a perfect job-housing balance in megacities remains a dream, with each area presenting unique challenges requiring tailored solutions beyond a one-size-fits-all approach. Potential policies, such as planning large residential areas in the inner suburbs and upgrading convenient infrastructure in the outer suburbs, are proposed. Furthermore, with the uncovered distinct interaction effects of built environment on commuting behavior across various masses and distances, common perceptions related to mixed-use land and the role of informal settlement, are critically challenged. This extends our understanding of sustainable urban system design and provides references for planning policies.
{"title":"Commuting behaviors response to living and working built environment: Dissecting interaction effects from varied supply and demand masses","authors":"De Tong , Yueer Dai , Yue Shen","doi":"10.1016/j.apgeog.2024.103430","DOIUrl":"10.1016/j.apgeog.2024.103430","url":null,"abstract":"<div><div>Most developed megacities have experienced poly-centralization and suburbanization, leading to job-housing mismatches and negative outcomes such as increased commuting distances and frequencies. Recognizing the scarcity of structural analysis concerning the attractiveness of commuting's geographic endpoints, this study examines the diverse impact of the built environment at living and working locations on commuting flows, considering various supply-demand masses and distance levels. Utilizing a Gradient Boosting Decision Tree (GBDT) model, the study highlights the importance of job-housing ratio, POI diversity, and subway station proximity in employment locations, while informal area rates and subway proximity remain significant in residential locations. A three-dimensional analysis further indicates that achieving a perfect job-housing balance in megacities remains a dream, with each area presenting unique challenges requiring tailored solutions beyond a one-size-fits-all approach. Potential policies, such as planning large residential areas in the inner suburbs and upgrading convenient infrastructure in the outer suburbs, are proposed. Furthermore, with the uncovered distinct interaction effects of built environment on commuting behavior across various masses and distances, common perceptions related to mixed-use land and the role of informal settlement, are critically challenged. This extends our understanding of sustainable urban system design and provides references for planning policies.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103430"},"PeriodicalIF":4.0,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-05DOI: 10.1016/j.apgeog.2024.103428
Lingli Mou , Heping Li , Yuxuan Rao
As transitional territories where urban and rural functions interpenetrate, suburban areas have multiple values such as recreation, ecology, agriculture and landscape. Promoting their benign development is the key to realizing global sustainable development of urban and rural areas. Planning control is based on precisely defining the spatial extent of suburban areas, and understanding suburban area differentiation and its driving forces scientifically is a key component in raising the bar for focused planning. However, there are currently few research on fine-scale quantitative identification of suburban regions because of their spatial complexity, ambiguous boundaries, and structural dynamic features. Based on this, this paper develops a multi-dimensional identification index system for suburban areas by using multi-source big data and remote sensing information technology, employs the random forest model and the K-Medoids clustering algorithm, identifies the distribution of suburban areas and their subdivided types, analyzes spatial differentiation characteristics, and conducts empirical research using Chengdu City as an example. The findings demonstrate that: (1) The majority of suburban areas in Chengdu City are concentrated in groups or belts surrounding the urban centers of various districts and counties, and the higher the functional class of a district or county, the denser the distribution of suburban areas. (2)The distribution pattern of suburban areas in Chengdu basically conforms to its planned urban hierarchy system.(3)Urban-oriented, suburban-interacted and rural-oriented suburban areas have their own characteristics in land use level, economic development and regional population characteristics.(4)Regional openness, government behavior, social development and geographical location are the core driving factors of spatial differentiation of suburban areas in Chengdu, and the interaction between urban and rural systems, the flow of social resources and the transformation of development models are the spatial mapping dimensions that affect its differentiation.(5)Chengdu can draw up detailed regulatory planning of suburban units to standardize and guide the overall development of suburban areas. In support of the global sustainable development goals, this study offers a methodology for precisely and impartially defining suburban areas, assisting in the implementation of integrated urban-rural development globally.
{"title":"Identification and Spatial Characterization of suburban areas in Chengdu","authors":"Lingli Mou , Heping Li , Yuxuan Rao","doi":"10.1016/j.apgeog.2024.103428","DOIUrl":"10.1016/j.apgeog.2024.103428","url":null,"abstract":"<div><div>As transitional territories where urban and rural functions interpenetrate, suburban areas have multiple values such as recreation, ecology, agriculture and landscape. Promoting their benign development is the key to realizing global sustainable development of urban and rural areas. Planning control is based on precisely defining the spatial extent of suburban areas, and understanding suburban area differentiation and its driving forces scientifically is a key component in raising the bar for focused planning. However, there are currently few research on fine-scale quantitative identification of suburban regions because of their spatial complexity, ambiguous boundaries, and structural dynamic features. Based on this, this paper develops a multi-dimensional identification index system for suburban areas by using multi-source big data and remote sensing information technology, employs the random forest model and the K-Medoids clustering algorithm, identifies the distribution of suburban areas and their subdivided types, analyzes spatial differentiation characteristics, and conducts empirical research using Chengdu City as an example. The findings demonstrate that: (1) The majority of suburban areas in Chengdu City are concentrated in groups or belts surrounding the urban centers of various districts and counties, and the higher the functional class of a district or county, the denser the distribution of suburban areas. (2)The distribution pattern of suburban areas in Chengdu basically conforms to its planned urban hierarchy system.(3)Urban-oriented, suburban-interacted and rural-oriented suburban areas have their own characteristics in land use level, economic development and regional population characteristics.(4)Regional openness, government behavior, social development and geographical location are the core driving factors of spatial differentiation of suburban areas in Chengdu, and the interaction between urban and rural systems, the flow of social resources and the transformation of development models are the spatial mapping dimensions that affect its differentiation.(5)Chengdu can draw up detailed regulatory planning of suburban units to standardize and guide the overall development of suburban areas. In support of the global sustainable development goals, this study offers a methodology for precisely and impartially defining suburban areas, assisting in the implementation of integrated urban-rural development globally.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103428"},"PeriodicalIF":4.0,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-04DOI: 10.1016/j.apgeog.2024.103429
Helena H. Rong , Lance Freeman
This study uses the Open Streets Program in New York City as a natural experiment to test the effects of change in street use on foot traffic changes during COVID-19. In a two-stage-least-squares (2SLS) design, the Open Streets Program is used as an instrumental variable to isolate the exogenous effect of expanded streets for pedestrians on foot traffic patterns. We then estimate a difference-in-differences model that compares the change in foot traffic to public points-of-interests (POI) in neighborhoods that are part of the Open Streets Program with those that are not “before and after” the start of the city-wide program, in addition to other controls such as street types and weather characteristics to help reduce the error variance of the regression. We find that the Open Streets Program helped increase pedestrian activity at a neighborhood level, even when controlling for street types and other confounding temporal factors such as precipitation and temperature.
{"title":"The impact of the built environment on human mobility patterns during Covid-19: A study of New York City's Open Streets Program","authors":"Helena H. Rong , Lance Freeman","doi":"10.1016/j.apgeog.2024.103429","DOIUrl":"10.1016/j.apgeog.2024.103429","url":null,"abstract":"<div><div>This study uses the Open Streets Program in New York City as a natural experiment to test the effects of change in street use on foot traffic changes during COVID-19. In a two-stage-least-squares (2SLS) design, the Open Streets Program is used as an instrumental variable to isolate the exogenous effect of expanded streets for pedestrians on foot traffic patterns. We then estimate a difference-in-differences model that compares the change in foot traffic to public points-of-interests (POI) in neighborhoods that are part of the Open Streets Program with those that are not “before and after” the start of the city-wide program, in addition to other controls such as street types and weather characteristics to help reduce the error variance of the regression. We find that the Open Streets Program helped increase pedestrian activity at a neighborhood level, even when controlling for street types and other confounding temporal factors such as precipitation and temperature.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103429"},"PeriodicalIF":4.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-04DOI: 10.1016/j.apgeog.2024.103422
Yuanshuo Xu , Jiahe Liang , Yan Wu
This paper contributes two mechanisms through which asymmetric fiscal decentralization drives local government borrowing: ‘fiscal hunger’ (borrowing to address budgetary fiscal gaps, leverage land resources, and pay off existing loans) and ‘competition game’ (borrowing to compete for bond issuance and state funds). Analyzing a dataset of 290 Chinese cities from 2006 to 2015, we find local government borrowing is driven by both fiscal hunger and inter-city competition. Borrowing is not confined to the growth-oriented purpose. Our Geographically Weighted Panel Regression uncovers the spatial patterns of two borrowing mechanisms, in which borrowing in less-developed regions is predominantly driven by fiscal hunger, while developed coastal regions actively engage in inter-city competition through borrowing. These dynamics may aggravate fiscal disparities among Chinese cities.
{"title":"Drivers of local government borrowing in China: Fiscal hunger and competition game under asymmetric decentralization","authors":"Yuanshuo Xu , Jiahe Liang , Yan Wu","doi":"10.1016/j.apgeog.2024.103422","DOIUrl":"10.1016/j.apgeog.2024.103422","url":null,"abstract":"<div><div>This paper contributes two mechanisms through which asymmetric fiscal decentralization drives local government borrowing: ‘fiscal hunger’ (borrowing to address budgetary fiscal gaps, leverage land resources, and pay off existing loans) and ‘competition game’ (borrowing to compete for bond issuance and state funds). Analyzing a dataset of 290 Chinese cities from 2006 to 2015, we find local government borrowing is driven by both fiscal hunger and inter-city competition. Borrowing is not confined to the growth-oriented purpose. Our Geographically Weighted Panel Regression uncovers the spatial patterns of two borrowing mechanisms, in which borrowing in less-developed regions is predominantly driven by fiscal hunger, while developed coastal regions actively engage in inter-city competition through borrowing. These dynamics may aggravate fiscal disparities among Chinese cities.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103422"},"PeriodicalIF":4.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-02DOI: 10.1016/j.apgeog.2024.103425
Hao Chao , Minghui Xu , Scarlett T. Jin , Hui Kong
Existing studies on urban renewal have primarily focused on the final effects of urban redevelopment, while often overlooked the social costs incurred during the temporary displacement phase. This gap is significant, as many residents must vacate their homes for an average of 3–5 years during Shantytown redevelopment, which brings about challenges of renting houses and the associated negative impacts on their well-being before returning to their resettled homes. Therefore, this study focuses on examining the temporary residence arising during Shantytown redevelopment while awaiting resettlement. We selected Heze city as our case study area, which has been through China's most intensive redevelopment between 2016 and 2018 that affected about 1.2 million population. A structured community survey was conducted, and 1035 valid samples were collected. We then applied spatiotemporal analysis and the Random Forest model to examine stability, direction, and distance of temporary residence mobility, along with its influencing factors. Findings reveal that 92.4% of households move just once or twice during the temporary phase, indicating the preference for stable residence. Regarding moving direction, households seek life service centers rather than city centers, and prefer familiar community environments. Furthermore, 74.8% of households resettled within 2.5 km of their original residence, indicating a preference for nearby temporary housing. The built environment emerged as the most critical factor influencing the mobility, followed by family socioeconomic status, while housing costs, surprisingly, having the minimal impact. This study highlights the importance of considering the interim social costs in urban renewal projects and provides valuable insights for housing market regulation and urban planning to mitigate these effects.
{"title":"Understanding temporary residential mobility during urban renewal: Insights from a structured community survey and machine learning analysis","authors":"Hao Chao , Minghui Xu , Scarlett T. Jin , Hui Kong","doi":"10.1016/j.apgeog.2024.103425","DOIUrl":"10.1016/j.apgeog.2024.103425","url":null,"abstract":"<div><div>Existing studies on urban renewal have primarily focused on the final effects of urban redevelopment, while often overlooked the social costs incurred during the temporary displacement phase. This gap is significant, as many residents must vacate their homes for an average of 3–5 years during Shantytown redevelopment, which brings about challenges of renting houses and the associated negative impacts on their well-being before returning to their resettled homes. Therefore, this study focuses on examining the temporary residence arising during Shantytown redevelopment while awaiting resettlement. We selected Heze city as our case study area, which has been through China's most intensive redevelopment between 2016 and 2018 that affected about 1.2 million population. A structured community survey was conducted, and 1035 valid samples were collected. We then applied spatiotemporal analysis and the Random Forest model to examine stability, direction, and distance of temporary residence mobility, along with its influencing factors. Findings reveal that 92.4% of households move just once or twice during the temporary phase, indicating the preference for stable residence. Regarding moving direction, households seek life service centers rather than city centers, and prefer familiar community environments. Furthermore, 74.8% of households resettled within 2.5 km of their original residence, indicating a preference for nearby temporary housing. The built environment emerged as the most critical factor influencing the mobility, followed by family socioeconomic status, while housing costs, surprisingly, having the minimal impact. This study highlights the importance of considering the interim social costs in urban renewal projects and provides valuable insights for housing market regulation and urban planning to mitigate these effects.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103425"},"PeriodicalIF":4.0,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.apgeog.2024.103424
A. Kelly , P. Tschakert , C. Lawrence , P. Horwitz , C. Bourgault , N. Ellis
Substantial research exists on attachments people have to places and the phenomena and objects they value. However, insights on how values vary between different locations and across demographics and how place attachment differs between rural and urban areas are more limited. These understandings are needed to design meaningful adaptation strategies for people and communities at risk from climate change. This study examines attachment to place and things people value in eight communities in Western Australia, using a survey with 403 participants. Results showed that residents across the rural communities shared similar values, but that the values of urban communities were differentiated socioeconomically. Contrary to our hypothesis, place attachment was not stronger among the rural compared to the urban sites. The findings point to the importance of incorporating place-based, lived values and needs, particularly from less affluent residents, into inclusive adaptation planning.
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