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.
{"title":"Place attachment and lived values in Western Australian communities","authors":"A. Kelly , P. Tschakert , C. Lawrence , P. Horwitz , C. Bourgault , N. Ellis","doi":"10.1016/j.apgeog.2024.103424","DOIUrl":"10.1016/j.apgeog.2024.103424","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103424"},"PeriodicalIF":4.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Local food self-sufficiency is a feasible path to make up for supply chain dependence caused by food system globalization. However, despite policies advocating food localization, China's current trends, such as the imbalance between food supply and nutritional demand and the mismatch between production space and consumption space, gradually restrict the sustainability of food security. This study analyzes China's local food security from 2000 to 2020 around the multi-dimensionality of supply, acquisition, and demand. Results show that regional differentiation of China's staple food self-sufficiency has become more significant. As a result, food supply capacity in rapidly urbanizing areas has weakened, and mountainous and underdeveloped areas are difficult to be self-sufficient. Fortunately, staple foods in China are highly accessible, and urban with a population of less than 50,000 have the best food transportation security. Overall, aging and scale management greatly affect China's food system, which currently can resist sudden natural disasters. In the future, decision-makers should focus on urban resources integration and rural land consolidation and realize sustainable food system transition by optimizing the local supply-demand structure through central planning based on popular science and healthy diet structure.
{"title":"Exploring China's food security evolution from a local perspective","authors":"Xinyuan Liang , Xiaobin Jin , Yue Dou , Fei Meng , Yinkang Zhou","doi":"10.1016/j.apgeog.2024.103427","DOIUrl":"10.1016/j.apgeog.2024.103427","url":null,"abstract":"<div><div>Local food self-sufficiency is a feasible path to make up for supply chain dependence caused by food system globalization. However, despite policies advocating food localization, China's current trends, such as the imbalance between food supply and nutritional demand and the mismatch between production space and consumption space, gradually restrict the sustainability of food security. This study analyzes China's local food security from 2000 to 2020 around the multi-dimensionality of supply, acquisition, and demand. Results show that regional differentiation of China's staple food self-sufficiency has become more significant. As a result, food supply capacity in rapidly urbanizing areas has weakened, and mountainous and underdeveloped areas are difficult to be self-sufficient. Fortunately, staple foods in China are highly accessible, and urban with a population of less than 50,000 have the best food transportation security. Overall, aging and scale management greatly affect China's food system, which currently can resist sudden natural disasters. In the future, decision-makers should focus on urban resources integration and rural land consolidation and realize sustainable food system transition by optimizing the local supply-demand structure through central planning based on popular science and healthy diet structure.</div></div>","PeriodicalId":48396,"journal":{"name":"Applied Geography","volume":"172 ","pages":"Article 103427"},"PeriodicalIF":4.0,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142322294","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}
Uncovering the association between built environment (BE) attributes and community park visits by considering potential nonlinear effects can inform more effective spatial policies. This study utilizes real-time population visitation big data to depict the spatial variances in community park visits in the case city of Shenzhen. An explainable machine learning method incorporating random forest and Shapley Additive exPlanations (SHAP) is applied to reveal the relative importance of BE attributes and to examine the nonlinear associations and interaction effects on park visits. The results confirm the decisive roles of park size and walking-based street connectivity on associating with visits, with threshold points at 2 hm2for park size and 0.3 for network warp. The revealed interaction between park size and surrounding BE attributes benefits defining the optimal scale by considering surrounding attributes of both attraction and demand factors. Based on the findings, we further discuss the possible patterns of threshold effects and interaction effects rooted in the examined nonlinearity. The findings guide policy makers in adopting smarter and more effective strategies to improve community park visits.
通过考虑潜在的非线性效应来揭示建筑环境（BE）属性与社区公园访问量之间的关联，可以为制定更有效的空间政策提供依据。本研究利用实时人口访问大数据来描述深圳社区公园访问量的空间差异。研究采用随机森林和 Shapley Additive exPlanations（SHAP）相结合的可解释机器学习方法来揭示 BE 属性的相对重要性，并检验公园访问量的非线性关联和交互效应。研究结果证实，公园面积和步行街的连通性对公园访问量具有决定性作用，公园面积的阈值为 2 hm2，网络翘曲的阈值为 0.3。所揭示的公园规模与周边 BE 属性之间的相互作用有利于通过考虑吸引力和需求因素的周边属性来确定最佳规模。根据研究结果，我们进一步讨论了所研究的非线性中可能存在的阈值效应和交互效应模式。研究结果将指导政策制定者采取更明智、更有效的策略来提高社区公园的访问量。
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