Applied Geography最新文献

Ecosystem services (ESs) bridge the gap between human wellbeing and ecosystem processes. Land use and land cover change (LUCC) affect ecosystem services by altering the structure and function of ecosystems. Beijing-Tianjin-Hebei (BTH), one of the most developed urban agglomerations in China, is subject to intense LUCC that affects ESs while increasing the regional ecological risk (ER). Therefore, to achieve the coordinated development of socioeconomic and ecological quality, there is an urgent need to establish a regional ecological risk assessment (ERA). ESs were introduced into the ERA to clarify their ecological significance and to compensate for the deficiencies of the traditional ERA. In this study, the ERA utilizes key ESs as endpoints to assess potential ER through a new framework by multiplying the probability of LUCC by the resultant loss of key ESs. We found that cultivated land was the most dominant outflow type and built-up land was the predominant inflow type. From 2020 to 2030, there is a greater possibility of changes in cultivated land, forest, grassland, and built-up land as well as in relatively stable water bodies and unused land. Overall, ESs show a positive trend. The overall potential ER was relatively minimal, with a significant northwestern spatially concentrated characteristic of high values. This study helps understand the potential development process of ERs and provides a scientific basis for risk management.

The urban built environment impacts human health through complex and nonlinear pathways. However, thresholds of urban built environment attributes associated with respiratory health are still relatively undetermined. Moreover, most existing studies assume the built environment to be static and only incorporate a cross-sectional approach to measuring it. In this case study examining the impact of the urban built environment on lung cancer risk in Shanghai, China, we perform a longitudinal analysis incorporating a range of environmental attributes and data spanning multiple years to tackle the synergistic effect of the urban built environment over an extended time period. We propose a novel approach combining nonlinear regressions and Geo-Detector to discern the general trend in the environment-disease association and pinpoint significant thresholds within this trend. Our findings showed that impervious land percentage, building coverage, green space coverage, and population density explained stratified heterogeneity of the respiratory health outcome by 8.7%, 21.2%, 8.1%, and 8.8%, respectively. Lung cancer incidence was significantly elevated in areas or during times with impervious surface percentage > 95%, building coverage > 25%, green space coverage < 15%, or population density > 10 thousand persons/km². These findings offer actionable insights for urban development regulation and policymaking.

Does foreign aid always contribute to economic development in recipient countries? This question has never been fully addressed. Using data on US aid to 128 countries worldwide from 2000 to 2019, this paper examines the relationship between US aid and economic growth in recipient countries, and the moderating role of institutional quality and absorptive capacity in shaping this relationship. Different types of US aid are considered, including economic aid and military aid. The results show that the relationship between economic aid and economic growth is U-shaped, while military aid has a positive linear relationship with economic growth. Moreover, we find that the institutional quality of the recipient country negatively moderates the relationship between US aid and economic growth. Additionally, the absorptive capacity of the recipient country positively moderates the relationship between economic aid and economic growth, whereas the relationship between military aid and economic growth is not affected by absorptive capacity.

Regional diversification literature has increasingly recognized the importance of diversifying into unrelated technologies. The emergence of technologies is considered the outcome of collaborative efforts, nevertheless, the role of scientific organizations is largely ignored. Especially, we know less about the impact of Industry-University-Research (IUR) collaboration on regional technological diversification. To fill in the gap, we conduct an empirical analysis based on patents from the Chinese Intellectual Patent Office over 2000–2019, in the case of China's pharmaceutical industry. The results show that: (1) Universities are pharmaceutical firms' primary collaborators, followed by research institutes, with hospitals accounting for a relatively small part. (2) There are significant differences in the knowledge bases of actors, with pharmaceutical firms more oriented to the applied field and scientific organizations, especially universities, focusing on basic research. (3) Regions with more IUR collaboration tend to diversify into unrelated technologies about pharmaceuticals, and its role is more evident for inter-regional collaboration. (4) Pharmaceutical firms engaging in IUR collaboration are more likely to diversify into unrelated technologies, while the technological diversification of scientific organizations seems to be irrelevant to IUR collaboration. Furthermore, pharmaceutical firms that collaborate with universities instead of research institutes and hospitals frequently tend to develop unrelated technologies.

Neighborhood compactness has been identified as a sustainable approach for fostering social relationships. However, existing studies have not clearly demonstrated whether neighborhood compactness in high-density cities directly influences the mental distress of community-dwelling older adults, or whether it indirectly influences mental distress through perceived accessibility to urban amenities (PA). Using a composite score of three dimensions (depressive symptoms, loneliness, and social isolation) to measure mental distress, and applying a mediation model within a cross-sectional design involving 947 older adults (aged ≥ 60) with at least mild symptoms in Hong Kong, our findings suggest an indirect pathway between neighborhood compactness, PA, and mental distress. Neighborhood compactness was positively associated with PA (B = 7.791, p < 0.001), and PA was negatively associated with mental distress (B = −0.12, p = 0.017). However, no direct impact of neighborhood compactness on mental distress was found. Moderated mediation analysis further indicated that neighborhood compactness and PA supported older females but not males. These results align with our hypothesis that (1) neighborhood compactness may not always be beneficial for older adults with mental distress in high-density cities unless compactness itself enhances PA and facility usage to support community-dwelling individuals, and (2) gender differences may result in varying interactions and perceptions of urban amenities and the built environment. To support the concept of “aging in place” in the future, urban plans aimed at enhancing neighborhood compactness and its social impacts should focus on addressing social inequality, including strategies to improve urban design, social participation, and gender-specific protocols, so that older adults can achieve better community awareness, environmental satisfaction, and facility usage, ultimately reducing mental distress.

Segregation studies based on human activity spaces have attracted increasing interest in urban geography and planning. Previously, most research employed variations in the geographical features of individuals' physical activity areas to ascertain social group segregation. A few studies have examined segregation based on one's activity space, comparing this over several years. This research conducts an empirical analysis based on people's activity space in Beijing to detect changes in segregation over time. We investigate activity space-based segregation among Beijing residents, separated into four housing categories for inner-city and suburban areas. The primary outcomes show residents living in different types of housing experience varying degrees of segregation when considering their activity spaces, which has progressed over the years. Furthermore, the findings show that the impact of changes in the built environment on the socio-spatial segregation of residents is gradually deepening, while the impact of institutional contexts such as danwei is gradually decreasing. In summary, this paper provides Beijing-based empirical evidence for this housing type differentiation and increasing segregation, which helps to enrich the understanding of activity space-based socio-spatial segregation of urban residents in China.

A growing number of young adults are choosing to live in private rental housing and sharing with unknown individuals in order to reduce their housing expenses. However, young housing sharers are generally treated as homogeneous to other renters in academic research and policy formation, leaving some of their unique housing issues unaddressed. This study examines how young housing sharers differ from their counterparts living in conventional or unshared rental housing. More specifically, we compare the spatial preferences of housing sharers to the spatial preferences of conventional housing renters, using a unique dataset of over 0.8 million private rental housing records collected in Shanghai, China. The results using a revealed-preference approach based on a hedonic pricing model demonstrate significant differences in their preference for location characteristics. Housing sharers are more willing to pay for proximity to employment centres and metro stations than conventional housing renters. Following the outbreak of Covid-19, the difference has narrowed to some extent, and housing sharers have moved further from employment centres. Rather, housing sharers are less concerned about access to public and private service amenities. The findings of this study contribute to our understanding of the recent housing tenure shift toward sharing among the younger generation and its potential impact on age-related segmentation in the housing market.

Traditional locational analysis in urban retail/business geography begins with the assumption that customers will visit retail locations that are most convenient, and that businesses that locate close to their customers’ residences or workplaces would be preferred to locations farther from those places. This assumption is problematic when applied to economic activities for which social stigma exists. In this article, we examine the influence of social stigma on the locational choices made by customers of illicit massage businesses in the Dallas-Fort Worth, Texas metropolitan area. We introduce the concept of shame buffers – zones around the places to which each customer is most deeply socially embedded, their home, workplace, and other community spaces, where the customer would not engage in stigmatized behaviors for fear of being observed and facing social shaming. We then examine the validity of the shame-buffer concept by analyzing customers' mobility patterns for both legal and illicit massage businesses in the Dallas-Fort Worth Metropolitan Area (DFW metro).

The evolution of large language models (LLMs) has already significantly influenced online health information retrieval. As these models gain more widespread use, it is important to understand their ability to contextualize responses based on spatial and geographic information. This study investigates whether LLMs can vary responses based on geographic and spatial context. Using a structured set of prompts submitted to ChatGPT, responses were analyzed to discern patterns based on prompt question and geographic identifiers included in queries. The analysis used word frequency analysis and bidirectional encoder representations from transformers (BERT) embeddings to evaluate the variation in responses concerning geographic specificity. The results provide some evidence that LLMs can generate geographically tailored responses when the query specifies such a need, thereby supporting localized information retrieval. Moreover, prompt responses exhibit an association between spatial distance and word frequency/sentence embedding differences between texts. This result suggests a nuanced representation of spatial information, which could impact user experience by providing more relevant health information based on the user's location. This study lays the groundwork for further exploration into the spatial intelligence of LLMs and their impact on the accessibility of health information online.

Enhancing neighborhood greenery quality proves to be an effective tactic in encouraging active travel among residents. From a cyclist's perspective, this study quantitatively evaluates street greening quality and its association with cycling behaviors. Utilizing shared bicycle usage data and SegNet-analyzed Baidu Street Views on Xiamen Island, we quantified comprehensive street greening quality. We then employed Spatial Design Network Analysis and a street greening quality rating scale to assess accessibility and aesthetics. Subsequently, models were developed using OLS, spatial autocorrelation, and Moran's I statistical methods, complemented by a spatial heterogeneity analysis of factors influencing shared bicycle riding behaviors through the Geographically Weighted Regression (GWR) model. Our study reveals that in arterial and commercial districts, the appeal and variety of street greening elements are more crucial than their quantity. These quality indicators exhibit a polycentric, continuous spatial distribution, aligning with the overall street layout. Beyond the visual impact of greenery on cycling behavior, factors like richness, openness, and safety of streets, along with diverse facilities, significantly influence cycling route preferences. In contrast, uniform street elements can disrupt or even discourage cycling. This research, by analyzing the relationship between street greening quality and cycling intensity, offers valuable insights for policymakers in prioritizing the transformation of streets into bike-friendly zones. Additionally, we propose a pragmatic, bottom-up approach to developing bicycle-friendly urban environments, indirectly fostering healthier travel habits among urban residents.