Applied Spatial Analysis and Policy最新文献

The pursuit of a comprehensive understanding of poverty has driven the formulation of innovative methodologies, with the multidimensional poverty index (MPI) standing as a prominent metric. But under empirical literature, role of geography concerning poverty remains under-documented; little emphasis has been placed to evaluating the pockets of poverty from geographic lens. This study employs the Alkire and Foster methodology to estimate MPI across diverse districts in Pakistan, utilizing data from the 2019-20 Pakistan Social and Living Standards Measurement (PSLM) survey. To identify spatial clusters Hot Spot Analysis is used along with bivariate mapping analysis, revealing spatial patterns of poverty and nuanced variations in MPI. Findings expose a disconcerting reality: 18% of Pakistan’s population grapples with multidimensional poverty, notably concentrated in Baluchistan and rural areas. Logistic regression analysis and Marginal Effects emphasizes the interplay of household demographics, with impoverished households showing larger dependency ratios and higher child proportions, while non-impoverished counterparts have a higher prevalence of working-age, employed, and educated individuals. The study underscores the critical need to tailor poverty alleviation strategies to diverse socio-economic and geographic contexts for effective policymaking and interventions.

Mapping species richness is a key goal of conservation research, but low data resolution and limited survey data make it challenging to accurately assess distribution patterns. In this study, the random forest (RF) and geographical random forest (GRF) models were used to construct a model of relationships between environmental factors and species richness, and high-resolution environmental data was used to downscale amphibian species distribution maps. The derived multi-scale species richness maps of 10 km, 5 km, and 1 km, revealed that the factors influencing the distribution of species richness and the locations of species richness hotspots vary with spatial scale. GRF outperformed GF in species richness map downscaling, with R² above 97% and RMSE between 0.98 and 1.29. GRF analysis shows that the spatial distribution of environmental factors affecting species distribution varies greatly, and precipitation dominates the distribution of most regions. This study suggests that machine learning algorithms can be used to downscale species richness maps. The multiscale species richness distribution map demonstrates the sensitivity of species richness patterns to spatial scales, which is crucial for macro-ecological analysis and identifying priority conservation areas. This information should be taken into account in future conservation planning.

The impact of rising housing prices on talent attraction and resulting innovation output in cities has garnered significant attention. However, most existing studies have overlooked the moderating effect of commuting distance when investigating the association between housing prices and innovation, employing various estimating methodologies. To address this research gap, this study analyzes the focused topic using mobile signaling data and relevant macro data from Shanghai City Statistical Yearbooks for the period 2015 to 2022. The empirical findings reveal an inverted U-shaped relationship between housing prices and regional innovation, indicating that as housing prices initially rise, regional innovation also rises before eventually decreasing. In the downtown area, high housing prices have a tendency to diminish innovation outcomes. Whereas the urban fringe area experiences a reverse effect. Additionally, this study reveals that commuting distance plays a significant moderating role in the relationship between housing prices and innovation. Our findings contribute to optimizing the spatial structure of urban employment and population distribution while providing valuable guidance for relevant high-tech enterprises and government departments in designing employee-oriented housing policies aligned with employment locations, thereby supporting future urban management policymaking.

Cycling is increasingly valued as a healthy active transport mode. Many cities across the world are investing in on-street bike lanes or multi-use trails to support more sustainable travel. When cycling infrastructure plans are proposed, however, local communities often express concern about loss of driveway access, on-street parking and street trees, also asserting that bike lanes will reduce their property values, termed “Bikelash” by planners. Our research examines correlations between cycling facilities and residential property values, applying space–time multi-level hedonic models in Kitchener, a growing mid-sized Canadian city. We consider three types of cycling facilities: (1) on-road bike lanes, (2) separated bike lanes, and (3) multi-use trails. The models use 2013–2018 housing transaction data and compare two types of proximity metrics: distance buffers and network distance. The results present no evidence that on-road bike lanes or multi-use trails in proximity to single-family or multi-family homes reduce property values. These findings can help planners inform the local community of the actual relationship between cycling infrastructure and property values and lower the resistance facing municipalities when making cycling infrastructure improvements.

Most studies have explored the association between transportation and urban–rural disparity. However, research focusing on the impact of transportation accessibility on these issues has been relatively scarce. This paper contributes to the literature by examining the spatially varying impacts of multiscale accessibility on urban–rural income disparity (URID) in the Qinba mountainous region (QBM) of China. The results further highlight the differing impacts of county-level, prefecture-level, and provincial-level accessibility on URID. The MGWR model confirms that the effects of multiscale accessibility on URID are spatially heterogeneous. Specifically, county-level accessibility has a significantly negative effect on URID. In contrast, the impacts of prefecture-level and provincial-level accessibility are significantly positive in narrowing the URID, leading to a “diffusion effect.” The narrowing effect of prefecture-level and provincial-level accessibility on URID is more pronounced in the eastern and northern parts of QBM, respectively. In the western mountainous areas of QBM, where most counties experience relatively low accessibility and high URID, prioritizing the expansion of connectivity between mountainous and well-developed areas, optimizing the layouts of villages and towns, and improving overall accessibility is essential. The findings suggest that the implementation of accessibility improvements and transport plans should be place-specific, considering the geographical and socio-economic contexts.

The concepts of “natural capital” and “sustainable urban development” are garnering widespread attention as the role of the environment and ecology in promoting economic development and maintaining human well-being is increasingly acknowledged. However, prevailing approaches to accounting for natural capital in sustainable cities exhibit deficiencies, with many overlooking the value associated with the natural environment, ecology, and capital stock of these cities. To rectify this issue, we propose a framework for natural capital analysis and decision-making for sustainable cities (Environment-Ecology-Economy Sustainable Development, EEE-SEEA). This framework integrates environmental, ecological, and economic perspectives, employing ArcGIS software for the visualization and analysis of sustainable cities in China. The results indicate an inverted U-shaped development trend distribution for natural capital, with ecosystem service accounting displaying a stable trend. The estimation results for urban sustainable development show a consistent annual increase with a certain level of resource dependence. On a level, natural capital accounting reached its zenith in 2010, gradually declining in 2015 and 2021, thus validating the inverted U-shaped development trend distribution. Ecosystem service accounting has demonstrated continuous development over the years, with the “Hu Huanyong line” becoming a crucial reference for distribution. The degree of sustainable development among cities is on the rise, with the central and northern regions of China exhibiting higher overall development quality. By integrating natural capital accounting and ecosystem service assessment, it becomes evident that cities in eastern and southern China still have significant room for improvement in terms of their sustainable development trajectory.

Urban growth in Indonesia is accelerating, particularly in areas with complex geomorphological features. This study examines the spatiotemporal variations of built-up area expansion in the Yogyakarta Urban Region (YUR), a rapidly urbanizing area characterized by diverse landforms and significant development pressures. Using Landsat satellite imagery (2001–2022), the study employed the Landscape Expansion Index (LEI) to classify urban expansion types and the Topographic Position Index (TPI) to analyze geomorphological characteristics. The findings reveal that edge-expansion dominated upper slopes, contributing 69%, 75%, and 79% of built-up area growth in 2001–2008, 2008–2015, and 2015–2022, respectively. Simultaneously, the outlying expansion type has steadily increased, particularly in U-shaped valleys, which grew significantly from 51.35 ha (2001–2008) to 109.28 ha (2008–2015) and 219.14 ha (2015–2022), highlighting an escalating risk of urban sprawl. These findings highlight the need for targeted urban planning policies to monitor and control growth patterns in geomorphologically sensitive areas, reducing sprawl and promoting sustainable development.

The ‘district-to-county’ policy is regarded as a counter-urbanization policy, yet its impact on economic growth is still uncertain. Utilizing the panel data from the district-level units within Yichun and the city-level units in Heilongjiang Province, this paper investigates the effects of the ‘district-to-county’ policy on the economic development at both the intra-city and inter-city levels by difference-in-differences model. The results show that the ‘district-to-county’ policy effectively spurs economic development in the reform areas within Yichun, but exhibits an inhibitory effect compared to other cities in Heilongjiang. Multiple robustness tests support these conclusions. Furthermore, the mechanism analysis reveals that this policy promots economic growth at the intra-city level by enhancing consumption and promoting agricultural development, but causes Yichun’s economic growth to lag behind other cities through consumption and investment at the inter-city level.

This study discusses the influence of China's high-speed rail (HSR) network on the urban‒rural income gap from 2003–2019. We find that China's HSR network has reduced the urban‒rural income gap since 2003, mainly by promoting industrial upgrading, industry agglomeration, and financial industry development. The results also show that the HSR network decreases the urban‒rural income gap in medium-sized cities but has nonsignificant effects on large and small cities. Additionally, the HSR network can reduce the urban‒rural income gap in cities with high betweenness centrality, whereas it has no significant effect on the urban‒rural income gap in cities with low betweenness centrality. The HSR network expands the urban‒rural income gap in provincial capital cities, whereas it narrows the gap in nonprovincial capital cities. Additionally, the HSR network reduces the urban–rural income gap more for cities with HSR stations far from the provincial capital than for cities with HSR stations close to the provincial capital. This study holds reference value for the spatial optimization of the HSR network.

Return migration, specifically the return of rural migrants from large cities to their hometowns, has emerged as a notable phenomenon in China in the early 21st century. Existing studies primarily attribute this trend to integration failure, citing factors such as hukou policies, an unequal welfare system and unaffordable housing costs. In contrast to these institutional factors, few studies have examined migrants’ psychological integration, including dimensions such as perceived social integration (PSI) and willingness for social integration (WSI), in relation to their return decisions. To address this gap, this study utilizes data obtained from a questionnaire survey of 712 migrants in Wuhan conducted in 2018, investigating the interactions between PSI, WSI and migrants’ return decisions, as well as the impacts of these perceptions across different migrant groups. Our findings reveal that migrants perceive an ‘integration risk’ when their WSI exceeds their PSI, and this perceived integration risk (PIR) is positively correlated with their return decisions. Additionally, we find that variables such as health status, migration duration, income, neighborhood composition and participation in local activities influence migrants’ return decisions through the mediation of PIR. We argue that strengthening specific, targeted integration policies related to migrants’ PIR will facilitate their settlement in host cities.