Does regional integration improve economic resilience? Evidence from urban agglomerations in China

Understanding seasonal contributions of urban morphology to thermal environment based on boosted regression tree approach

The growth of the digital economy has created new forms of inequality of opportunity. This paper studies whether the development of the digital economy expands the income gap between urban and rural areas from theoretical and empirical. The research based on the panel data of 202 cities from 2011 to 2019 in China shows that: (1) Although the digital economy can promote the improvement of both urban and rural absolute income levels, it has a greater positive impact on urban residents’ income levels than on rural residents’, resulting in a widening of the urban-rural income gap. (2) The analysis of the action mechanism reveals that employment in the information service industry and the depth of digital finance use are two crucial mechanisms for the digital economy to widen the income gap between urban and rural areas. (3) The spatial Durbin model(SDM) and the spatial error model(SEM) based on three spatial weight matrices show that the impact of the digital economy on the urban-rural income gap is also characterized by spatial spillover, and the development of the digital economy will also have a negative impact on the urban-rural income gap in neighboring regions as well. (4) The main conclusions still hold after the robustness of quasi-natural experiments based on the strategy of "Broadband China" and the selection of historical data as instrumental variables. This research is helpful to understand the effects, mechanisms and spatial characteristics of digital economy on urban-rural income gap.

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Digital economy development and the urban-rural income gap: Evidence from Chinese cities

Economic spatial structure of China's urban agglomerations: Regional differences, distribution dynamics, and convergence

Modelling built-up land expansion probability using the integrated fuzzy logic and coupling coordination degree model.

Morphological and functional polycentric structure assessment of megacity: An integrated approach with spatial distribution and interaction

Global climate change presents considerable heating risks to cities, necessitating the assessment of heat vulnerability characteristics in urban areas for the advancement of human settlements and socioeconomic progress. Nevertheless, there has been a lack of extensive research regarding heat vulnerability when considering local climate zones (LCZs). In this study, we utilized data from multiple sources to construct a model for evaluating heat vulnerability along three dimensions: Exposure, Sensitivity, and Adaptability. We analyzed the spatial characteristics of heat vulnerability in the LCZs and employed a linear weighted multi-objective optimization method to reconfigure the LCZs and mitigate the Urban Heat Vulnerability Index (HVI). The findings revealed that (1) The spatial characteristics of exposure and sensitivity were similar, with high values observed in the city center and low values at the periphery. Adaptability exhibited a high–low–high pattern from the center to the edge due to the combined influence of the economy and natural factors. (2) The HVI of the built environment (building LCZ) surpassed that of the natural environment (natural LCZ) within the research area. Specifically, compact high-rise buildings (LCZ1) and compact midrise buildings (LCZ2) accounted for over 90% of the area with extremely high and high HVI values, necessitating immediate optimization efforts. (3) By considering the area and population size of the research area, we achieved an optimal heat vulnerability plan by increasing the areas of LCZ4 and LCZA while reducing the areas of LCZ8 and LCZ1, among others. Therefore, the overall HVI of the study area decreased from 49,034.67 to 41,772.37, representing a reduction of 14.81 %. This study presents an innovative approach to mitigating urban heat vulnerability, providing valuable planning references and scientific guidance to assist cities in addressing high-temperature risks. 

Optimal allocation of local climate zones based on heat vulnerability perspective

The escalation of greenhouse gas emissions has led to a continuous rise in land surface temperature (LST). Studies have highlighted the substantial influence of urban morphology on LST; however, the impact of different dimensional indicators and their gradient effects remain unexplored. Selecting the urban area of Shenyang as a case, we chose various indicators representing different dimensions. By employing XGBoost for regression analysis, we aimed to explore the effects of urban 2-D and 3-D morphology on seasonal LST and its gradient effect. The following results were obtained: 1) the spatial pattern of LST in spring and winter in Shenyang was higher in the suburbs than in the center; 2) the correlation patterns of the indicators in spring and winter were similar, except for the proportion of woodland and grass, digital elevation model, and sky view factor, which exhibited opposing trends in summer and autumn; 3) vegetation and construction had the highest influence on LST in the 2-D index, followed by building forms and natural landscapes in the 3-D urban morphology; and 4) the influence of each indicator varied significantly across different gradients. Among all the indicators, the landscape index, social development, building forms, and skyscape had the highest impacts on urban areas. Vegetation and built-up areas had a greater influence on suburban areas. The findings of this study can assist in adjusting urban morphology and provide valuable recommendations for targeted improvements in thermal environments, thereby contributing to urban sustainable development.

XGBoost-Based Analysis of the Relationship between Urban 2D/3D Morphology and Seasonal Gradient Land Surface Temperature

Spatial–temporal differentiation and influencing factors of marine fishery carbon emission efficiency in China

Several studies have demonstrated that the urban heat island (UHI) impact is significantly influenced by changes in urban land cover (LC). In this study, we examined the dynamic change in LC in Shijiazhuang city and its impact on UHI intensity using multisource data, including landsat and LC data. The results showed that 1) the 15-year span exhibited a substantial growth in built-up area from 14.541% to 19.718%, whereas cropland and grassland dropped by 3.342% and 3.625%, respectively. 2) The mean land surface temperature (LST) in the study area increased significantly. From a point-to-plane distribution, the high-temperature zone (>32 °C) grew, and the direction of growth was consistent with urbanization. 3) The average temperature of the barren areas was the highest, followed by the built-up areas. 4) The normalized difference vegetation index and LST have a strong negative association, showing that LST rises with vegetation loss. Our research results provide a scientific basis for deeper understanding of the mechanisms underlying UHI creation, as well as for developing logical land use strategies and evaluating the effects of urbanization on local climates.

Dynamic changes in land cover and its effect on urban heat islands

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