Applied Geography最新文献

This study focuses on the contradiction of mobility and immobility in relation to interred human remains. While society generally embraces human mobility, once individuals pass away and are disposed of, mobility ceases to be the norm. Some counties, like Sweden, has a rigid burial legislation that prohibits the re-location of interred human remains. However, both society- and climate-related events are increasingly affecting the eternal rest of the deceased. Utilizing quantitative data on all cemeteries in Sweden, this study aims to assess and analyse the potential magnitude of future large-scale moves of human remains due to expected impacts of climate change, and to put this into a relational context of norms and laws. Results show that climate change poses an apparent risk to cemeteries in Sweden, especially in the south-west of the country, and that this is mainly caused by increased risk of landslides and erosion, as a result of expected increased precipitation. A low estimate state that by the end of this century, some 30.000 interred remains and some 146.000 living survivors will likely be affected by climate-related risks.

Nature reserves (NRs) are essential for preserving natural ecosystems, biodiversity, and ecological balance and for mediating human-land conflicts while sustaining ecosystem services (ESs). This study was conducted in China as a study area to assess the conservation effect of NRs through the intensity of human footprint (HF) impacting ESs. This study utilized a spatio-temporal geographically weighted regression model using multi-source data to assess the impact of HF on ESs across NRs at the national level. The results show that NRs greatly enhance ESs and reduce HF and that their conservation effects vary depending on the location, type, and management strategy of the NRs. The study concludes that while HF typically destroys ecosystems, some of the HF within NRs can enhance ESs. Moreover, the impacts of HF on ESs were progressively more positive over time, suggesting that conservation awareness is increasing. Findings suggest that developing targeted policies to manage HF within NRs can further improve conservation effectiveness. This study proposed a differentiated approach to optimize conservation effectiveness based on the NRs characteristics and supports policy and strategy development for the conservation and management of NRs in China.

Farmland landscape pattern (FLP) is critical in ensuring sustainable agricultural production. Amidst the challenge of increasingly fragmented FLP, accurate assessment and optimization strategies are essential. Traditional FLP assessment studies lack significance in ecological representation because they ignore landscape types and their characteristics and overlook changes in landscape details based on overall results. These factors lead to uncertain assessment outcomes. This study introduces a farmland landscape classification system based on morphological spatial pattern analysis to address this. Special attention is given to the internal core and external edge farmland landscape types, resulting in an innovative FLP assessment system being developed. The results of the Jiangsu Province reveal significant patchiness and marginalization of core farmland, particularly worsening from north to south. While recent trends show a slight improvement in the overall situation and effective perforation suppression, challenges persist with low-value FLP expansions in each agricultural zone. This study emphasizes integrating external edge farmland and overall pattern protection for optimal FLP. The improved assessment method identifies areas for scale improvement and fragmentation risks, offering valuable insights for permanent basic farmland policy. Overall, this study enriches the analytical framework of FLP from a morphological perspective, aiding in precise assessment and tailored optimization strategies.

The UN Sustainable Development Goals advocates providing training and technical assistance in developing and strengthening integrated monitoring systems to provide reliable forest resources and land use/change information needed for management planning. Several ecosystem service (ES) demand and supply assessments apply biophysical and econometric methods to evaluate ES use patterns. Decentralized participatory social assessments, however, incorporate farmers’ local knowledge and facilitate community-based management. Here, we assessed ES demand and supply in community forests using a participatory approach involving local farmers (N = 100) in Malawi. Indicators were collaboratively developed with stakeholders in intervention and control communities. We demonstrated that integrating local knowledge reveals nuances that biophysical and economic assessments may mask. ES demand outmatched supply in all study communities, as much as three times in some forests, but with variation from community to community. Demand for regulating services was higher in the intervention communities where agroecology is predominantly practiced, which farmers attributed to the knowledge about the role of forests in pollination and water and pest control on farm productivity. Differences in use patterns between communities with contrasting knowledge systems meant local knowledge influenced environmental behavior toward resource use. The study demonstrates the need for inclusive planning, assessment, and management of community forests.

This research explores the nonlinear interactions among multidimensional proximities, including geographical, cognitive, organizational, institutional, social, and technological aspects, and their impact on innovation within networks of over three million technology firms in China. Utilizing an innovative combination of web-based hyperlink and textual data analysis, supplemented by patent information, we delve into how these proximity dimensions influence corporate innovation capabilities. Our methodology integrates text-based deep learning techniques and employs the XGBoost model along with the SHapley Additive exPlanations (SHAP) algorithm and partial dependence plots to uncover the nuanced effects of proximity on innovation. The findings reveal that while geographical distance often correlates with larger cognitive and organizational proximities, underdeveloped regions exhibit stronger technological, institutional, and social proximities compared to their developed counterparts. The study further identifies social structure and technological differences as pivotal factors impacting collaborative innovation, with both positive and negative effects fluctuating alongside changes in proximity dimensions. Notably, we uncover that geographical proximity has a pronounced boundary effect on innovation, highlighting the critical role of spatial considerations in the digital age of innovation networks. This research contributes to the understanding of urban innovation dynamics and offers valuable insights for policymakers and urban planners aiming to foster innovation ecosystems.

Internships, job shadows, cooperative education programs, and other forms of experiential education can play a crucial role in students successfully transitioning from their undergraduate program to a career pathway. We collectively term these opportunities as work-related experiential activities (WREAs). While valuable, students’ access to these experiences can vary based on multiple factors, including their own socioeconomic background, access to social networks, university programs, and geographic context. Little research has been done on the last of these factors, and this paper helps fill this gap by developing a geospatial WREA opportunity index for STEM related opportunities, using census and point-of-interest data to identify census tracts with the greatest rate of WREA opportunity and attractive amenities for students. To do so, we draw on surveys and interviews across multiple college campuses in Georgia, both to identify desirable characteristics for students and to catalog the WREAs they have participated in. This index highlights disparities across college campuses, particularly between those located in metropolitan Atlanta compared to those in smaller cities in the state. This tool provides a way to quantify and visualize those differences in ways that can support investment in programs that help bridge opportunity gaps for students.

Compact urban forms are essential for sustainable development, while few studies developed multidimensional urban form compactness index at the national scale from the perspective of spatial-temporal data, limiting our understanding of urban compactness mechanisms. In this study, a multidimensional urban form compactness index was created for 296 cities in China, focusing on spatial topology, morphology, and dynamics, addressing a gap in national-scale analyses from spatial-temporal viewpoints. Key findings include: (i) In the last two decades, significant alterations have occurred in urban compactness, with cities witnessing enhancements from 2005 to 2020. There's a spatial evolution trend characterized by higher compactness in the southeast and lower in the northwest, advancing from northwest to southeast. (ii) Urban expansion elements generally undermine urban compactness, whereas agglomeration efficiency elements contribute positively. (iii) Over time, while urban expansion impacts have shown relative stability over the years, agglomeration efficiency indicators have undergone an N-shaped fluctuation. Spatially, factors associated with urban sprawl enhance compactness in western and northeastern China, while land use factors are particularly effective in the northeastern, western, and northern areas. The study emphasizes the importance of using multidimensional composite indicators for thorough understanding of urban form compactness, offering significant insights for future policy and urban management.

The relationships between various factors and child labour have been explored in the literature but, despite findings that suggest the predictive factors of child labour can vary according to context, there has been little research that has used spatial methods of analysis or attempted to estimate local relationships between covariates and the prevalence of child labour. This paper seeks to address this knowledge gap by using geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) models. Using India 2011 Census Data as a case study, the findings show that GWR and MGWR models both perform significantly better than a global regression model across the whole of India. The study also finds significant spatial non-stationarity in the relationships between child labour and its covariates, with the association between district-level child labour rates and both the Muslim population and the child sex ratio found to have opposite directions in different parts of the country. Using MGWR, it was also possible to demonstrate that different covariates interact with child labour at various spatial scales, suggesting that interventions aiming to address varying aspects of the child labour problem may need to be deployed at different administrative levels to maximise their efficacy.

Despite pursuing greening initiatives, cities might experience excessive greenery at the neighborhood level. The intension of this research is to promote ecosystem services and avoid the mantle of so-called “green urbanism”. Hence, examining the dose-response relationship is essential to understanding the intricate interplay between residential greenery quantity and landscape preference. Drawing upon preference assessment data from multiple neighborhoods with 30 typical scenes (n = 147), we employ Kaplan's landscape preference matrix (KLPM) to quantify the spatial distribution of greenery and individuals' preference assessment from the perspectives of Mystery, Coherence, Legibility, and Complexity. Results from multiple and ridge regressions indicate that the dose-response curve follows a polynomial shape, with landscape preferences reaching a threshold as the NDVI value increased from 0.35 to 0.42. Beyond the threshold, the trend of landscape preference levels tapers off and eventually plateaus. Therefore, the conclusion of our cross-sectional experiment adequately reflects the threshold effect of landscape preference toward greenery quantity. Furthermore, the weight of Mystery, Coherence, and Legibility in KLPM all showed a positive strong correlation, but the dose-response relationship cannot be fully explained by Complexity. These results inform how designers can more effectively promote optimal doses of nearby nature to circumvent worldwide overheated "Garden City” initiatives.

Revealing the effect of transit-oriented development (TOD) on housing rents is critical for supporting transportation financing and sustainable urban development. However, existing research has not thoroughly examined the effects of land use type and TOD type on housing rents, crucially lacking geospatial modelling. This study investigates the spatial effect of TOD on housing rents using multi-scale geographically weighted regression (MGWR) and the relationship of land use type and TOD type to this effect. The results show that MGWR accurately quantifies the spatial effect. Meanwhile, the important TOD variables (integrated transit index, land use entropy, overall walkability) have positive effects on housing rents, which show spatial heterogeneity. Moreover, the premium effect of TOD station areas with a smaller proportion of residential and commercial land and a larger proportion of educational and cultural facilities is higher. Furthermore, in TOD station areas where transportation supply capacity is high but urban development is lagging, land use entropy and overall walkability have a strong influence on housing rents. Based on the study's results, we offer three recommendations for implementing TOD practices into integrated transportation and land use planning. This study renews our understanding of the outcomes of TOD both perspectively and methodologically.