Applied Spatial Analysis and Policy最新文献

In temperate continental climate zones with hot summers and significant diurnal temperature differences, the park green space construction is an effective way to increase park visitor comfort and mitigate urban daytime high temperatures. In this experiment, 42 plant configurationss were selected and classified into 12 configuration typesbased on three indicators of the underlying surface, tree species, and canopy density in 6 parks in Yinchuan, Wuzhong and Zhongwei cities of Ningxia, China, in the summer of 2019 and 2020.The air temperature of the sample plots (8:00 ~ 18:00) was measured with a Kestrel NK5500 weather station, and the daily air temperature variation pattern of each typical plant configuration was analyzed, the cooling effect of the 12 configuration types and its controlling factors were revealed based on the air temperature difference (park air temperature—weather station air temperature). There was a significant negative correlation between canopy density and the cooling effect of green lands(P < 0.05,the same below), but the underlying surface and tree species configuration of the green lands could not contributed to the cooling effect. The park green lands with ≥ 40% canopy density had a significant cooling effect compared with hard-paved park areas during the daytime (8:00–18:00). The average daytime temperature of green areas with 40–60% canopy density decreased by about 0.5 °C, and those with > 60% canopy density decreased by 1.1–1.5 °C. In the daytime, the cooling effect of green areas was stable from 8:00 to 12:00 and from 12:00 to 15:00, when the degree of canopy density reached 50% and 40% and above, respectively. And from 15:00 to 18:00, all plant configurations (including grass) had a cooling effect, and the overall cooling effect increased with the process of canopy density.This study provides guidance for the risk management of summer high temperatures and the planning of public green space construction based on cooling effects in cities of continental climate zones.

The spatial relationship between violent crime and alcohol outlets is well documented. Yet, it is unclear whether on- or off-premises alcohol outlets have greater effects on violent crime and whether this varies by interpersonal crimes and off-premises outlet subtype. This study addresses this gap by using both Routine Activities and Social Disorganization Theories. Using census block groups (n = 1,126) in the Bronx, NY, spatial access methods were used to measure violent crimes from 2018 to 2020 (n = 28,587) and alcohol outlets from 2020 (n = 1,984). Social disorganization measures consisting of various socioeconomic factors and accessibility factors were included. Five models were estimated using a Spatial Lag regression model. A positive direct, indirect, and total effect was observed for liquor, grocery, and drug stores on total violent crime exposure, but on-premise alcohol outlets was not related. Specific types of off-premises alcohol outlets were associated with various violent crimes, with liquor and grocery stores consistently related across all models. On-premises alcohol outlets were not associated with violent crime with the exception of assaults.

Compared to developed regions, the development of industrial parks in underdeveloped areas has certain particularities. However, existing researches do not give a clear answer to the relationship between industrial parks and county economic development in underdeveloped areas. This article analyzes the relationship, heterogeneous effects, and pathways between industrial park construction and county-level economic growth in Gansu Province based on the DID model. It was found that industrial parks have a positive promoting effect on underdeveloped areas. And as time goes on, the promotion effect becomes more apparent. Secondly, the development of industrial parks in underdeveloped areas is still in its early stages and their scale is generally small, which means that industrial parks have a lower impact on the economies of counties with higher economic scales. At the same time, compared to provincial-level parks, national level parks have a lower impact on the economies of major counties. However, for developed regions, the development of industrial parks is relatively mature, and their impact on economic growth has shown a positive relationship consistent with the economic scale. In addition, industrial parks in underdeveloped areas mainly act on county-level economic development through capital agglomeration, but the agglomeration effect of human resources is not significant. Industrial parks in developed regions play a significant role in gathering capital, human resources, and other aspects.

Globally, road crashes impose massive burdens, and understanding the complex factors influencing crash patterns requires advanced analytical methods. This study reviews 20 years of published literature on geospatial crash analysis to chart key innovations shaping this critical field. The analysis reveals a progression from fundamental mapping approaches towards integrative predictive modelling and dynamic risk monitoring leveraging diverse data sources. While crash records and road networks remain core datasets, aerial imagery, social media, weather, infrastructure attributes, and traffic data have become increasingly incorporated. Techniques have evolved from hotspot analysis to sophisticated machine learning algorithms automating crash prediction and factor analysis. Research objectives now emphasize not just pattern identification but predictive risk modelling, and there is an increased focus on prevention through improved emergency response, infrastructure enhancements, and targeted countermeasures. Interactive 3D visualizations and virtual reality applications are enhancing geospatial communication and decision-making. As geospatial innovations and data integration accelerate, this continuously advancing field holds tremendous potential to guide proactive evidence-based road safety planning. However, validating analysis approaches and assessing geographic transferability remain critical research needs. By synthesizing two decades of developments, this study provides key perspectives to harness geospatial technology innovations and unlock new frontiers in data-driven road crash prevention worldwide.

The UK residential sector is energy inefficient and has an overwhelming reliance on natural gas as a heating source. For the UK to meet its 2050 net zero obligations, the sector will need to go through a process of decarbonisation. Previous studies acknowledge the spatial disparities of household energy consumption, but have neglected how consumption varies over time. This paper advances such shortcomings via a sequence and clustering analysis to identify common gas consumption trajectories within neighbourhoods in England and Wales between 2010 and 2020. Four clusters are identified: “Very High to High Consumption”; “High to Medium Consumption”; “Medium to Low Consumption” and “Low to Very Low Consumption”. The clusters were contextualised using spatial datasets representing the socio-economic and built environment. Across all clusters, the proportion of energy inefficient dwellings were high, but there was a trend of high consumption associated with lower proportions of energy efficient dwellings. The results provide useful insight to policy makers and practitioners about where best to target electrification and retrofitting measures to facilitate a cleaner and more equitable residential sector. Policy targeting of areas with continual high gas consumption will accelerate the decarbonisation process, whilst targeting areas who continually under consume will likely enhance household health and well-being.

The establishment of an accurate early warning and intervention mechanism for re-poverty (i.e., returning to poverty) is a valuable tool for consolidating the achievements of the Chinese government in poverty alleviation and the effective connection with rural revitalization since completing the task of eliminating absolute poverty. The occurrence of the re-poverty phenomenon is closely related to the vulnerability characteristics of the subject. This paper constructs a vulnerability to re-poverty analysis framework that integrate regional and household perspectives based on "capital-capacity-welfare". Zherong County was selected as the case study where the vulnerability assessment model and GeoDetector were adopted to undertake an early warning and Interactive detection analysis respectively. The results show that: (1) The degree of vulnerability to re-poverty of most townships and households in Zherong County is relatively low after the withdrawal of absolute poverty; (2) At the regional level, among 9 townships of Zherong county, the social welfare is more vulnerable than geographical capital and economic capacity, and the degree of vulnerability to re-poverty of Fuxi and Zhayang are relatively high, with warning level III; (3) Among the 737 low-income households registered, 98.4% of them aligned with warning level I and II, only 1.6% of them aligned with warning level III. However, households' livelihood capital vulnerability is generally relatively high, and the improvement of household self-development motivation is still insufficient; (4) Household vulnerability to re-poverty is influenced by both regional and household factors, and the interaction between the two factors can enhance each other's explanatory power to HVRI. We divided the risk into four types and proposed corresponding policy implications based on the coupling of regional and household vulnerability to re-poverty early warning.

As the aged population increases, the health of seniors (aged 60 years and over) is particularly important for the development of a healthy China, which makes it important to assess the health determinants for the elderly. This study aims to estimate the effect and pathway of microgeographic environment on the seniors’ health and physical activities, and further investigate the urban–rural disparity in the relationship between the seniors’ health and geographic environment. We collected data on 7155 elderly (≥ 60 years) from the Household Health Survey database of the Hebei Provincial Health Planning Commission, China. The geographic environment data, based on different radius buffers of respondents’ residence, were collected from Baidu Maps. The green space data were obtained from the dataset provided by National Ecosystem Science Data Center, National Science & Technology Infrastructure of China. A series of multilevel generalized structural equation models were employed to examine the disparities in the effects of geographic environment on the seniors’ health and physical activities. Built environment has significant direct and indirect effects on the health of the urban elderly, while its indirect effect on the rural elderly is significant. Green space is significantly and positively associated with the seniors’ health, whereas its indirect effect is insignificant in rural areas. Environmental pollution has a negative correlation with seniors’ health, and it also significantly restricts seniors from participating in outdoor physical activities. Physical activity has a significantly beneficial effect and a significant mediating effect on the health of seniors in both urban and rural area. The socioeconomic attributes, such as income, education and age, are significantly associated with the health of urban and rural elderly. The study finds that built environment, green space, environmental pollution and physical activities are crucial factors influencing the seniors’ health, but there is significant urban–rural disparity in the health effects. The findings provide policy implications for the government to develop healthy neighborhoods and cities.

Since 1971, the decennial censuses of England and Wales have underpinned the construction of various local level deprivation measures. Many policy-related and academic studies have used deprivation scores calculated cross-sectionally to identify geographical areas in need of regeneration and to explain spatial variations in health outcomes. However, such an approach masks the sometimes very distinct challenges faced in areas with different deprivation histories. There is, therefore, a need to consider the deprivation trajectories of areas over a long time run. This can then enable, for example: monitoring the effects of industry closure; assessing the impacts of area-based planning initiatives; and determining whether a change in the level of deprivation leads to changes in health outcomes. It can also be used to consider what interventions may be linked with positive changes and which could then possibly be implemented elsewhere. Here we extend previous work to cover a 50-year period using input variables relating to employment, housing, and car accessibility, from the six censuses from 1971 to 2021. We identify areas of persistent (dis-)advantage, those areas which have improved their deprivation situation, and those places where the situation has worsened. We cross-classify the changing deprivation measurements with the Office for National Statistics (ONS) Supergroups area classification to thereby determine how different types of area are faring. On average, areas are less deprived in 2021 than in 1971. However, the trajectories of the input variables and of overall deprivation are not linear. The earlier decades are distinctive in rapid falls in non-home ownership and lack of car access but rises and falls in unemployment. The more recent decades have seen rises in non-home ownership and household overcrowding. Geographically, there has been a shift from a widespread level of deprivation, including in more rural areas in 1971, to being more concentrated in urban areas in the 21st Century.

With the arrival of the Fourth Industrial Revolution, digital changes have occurred in various areas, such as production, circulation, and exchange, triggering efficiency and quality changes in the entire economic system and bringing new opportunities for China’s energy conservation and carbon reduction policies. Based on the panel data of 30 provinces in China from 2006 to 2020, this paper uses ArcGIS software and the Moran index method to analyze the spatial distribution characteristics and agglomeration effects of the digital economy and carbon emissions and uses the spatial Durbin model to analyze the impact mechanism of the digital economy on carbon emissions. The results show that the development of the digital economy can significantly suppress provincial carbon emissions, and the carbon reduction effect of the digital economy has a significant positive spatial spillover effect. The digital economy can reduce carbon emissions by promoting technological innovation and optimizing the industrial structure. However, the carbon emission reduction effect of energy structure optimization is uncertain due to energy rebound effects. The digital economy has a suppressive effect on carbon emissions in both the eastern and western regions, while the development of the digital economy in the central region increases carbon emissions due to factors such as the “resource curse”, income effects and energy rebound effects. Digital economy development plays an inhibitory role in the carbon emissions of regions, with the greater the digital economy level, the more significant the inhibitory effect. Based on the above results, corresponding suggestions are proposed to strengthen the development of the digital economy and promote carbon reduction.