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AbstractConcerns about opportunistic behaviors by governments and their failure to recognize local needs are significant issues with place-based policies. In China’s aid program targeted at Xinjiang, rather than solely relying on fiscal transfers and centralized decision-making, there was encouragement for the involvement of state-owned enterprises and direct cooperation between aid providers and recipients. While these arrangements have helped the program succeed in addressing concerns related to place-based policies and have contributed to economic growth in recipient areas, there are potential negative impacts on the local environment, leading to what is termed as a pollution heaven scenario. Analyzing of data from 72 ethnic cities in China using a difference-in-differences approach, we demonstrate that the program resulted in notable increases in local GDP and PM2.5 concentrations, accompanied by expansion of polluting industries. This study is pertinent to ongoing discussions in place-based policy research and offers policy insights both domestically and internationally. [ABSTRACT FROM AUTHOR]

China's rapid urbanization drive, marked by extensive urban renewal projects, necessitates a meticulous examination of their transformational impact on the human settlement environment (HSE) across urban landscapes. This study investigates the impact of China's urban renewal progress on the spatial–temporal changes in the HSE from 2009 to 2019, using data from 40 prefecture-level cities in the Yangtze River Delta. Our findings reveal an overall positive relationship between the spatio–temporal evolution of urban renewal and the HSE, suggesting that urban renewal projects have had a beneficial impact, particularly following the announcement of China's New Urbanization policy in 2014. However, the extent of this positive impact varied among different areas, with more significant improvements observed in core cities and economically developed areas. Additionally, our study uncovered significant variations in how urban renewal influenced the HSE over time. We found that the primary influencing factor shifted from material renewal to industrial renewal. These findings offer valuable insights for improving the HSE during urban renewal processes, both in China and other regions undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

During the past two decades discussions on urban shrinkage have been increasing in intensity, mainly due to the irresistible trends of migration, economic transformation, and the so-called "siphon effect" of large and mega cities. Yet, very few studies have tried to understand urban shrinkage from the perspective of local microscopic unit evolution. This study develops a novel model for simultaneous simulation of expansion and shrinkage (MSSES) of urban built-up areas. Starting from a microscopic basis, our MSSES can simulate both the processes and the states that lead to spatial expansion or shrinkage. A MaxEnt model is further used to investigate the driving factors of microspatial changes and compute the probabilities of shrinkage (or expansion) of urban built-up areas. Finally, it simulates the explicit layout of the spatial distribution of shrinkage (or expansion) patches with the help of a sorting cellular automata (CA) model. The validity of MSSES is verified using multisourced data from the Wuhan agglomeration, China. We show that (1) MSSES can more accurately simulate urban expansion or shrinkage than the currently widely used neighborhood-based Logistic-CA (NL-CA) and (2) MSSES has advantage in solving the commonly seen problem of "diffusion-coalescence," especially for the simulation of outlying expansion. Against the context of the Wuhan metropolitan area, we also found that overall the shrinkage trend is slowing down significantly, presenting three types of shrinkage at city-scale: remote shrinkage, peripheral shrinkage, and international shrinkage. Our study has contributions to the body of knowledge as well as practical implications for urban management and improving the sustainable development of urban areas in both China and abroad. The city we live in may be experiencing a situation where expansion and shrinkage are happening simultaneously. Hence, the simulation and prediction of temporal and spatial changes in urban expansion and shrinkage hold great importance in formulating urban policies. In this study, we propose a model capable of simultaneously predicting urban growth and shrinkage, and apply this model to the urban morphological changes in the Wuhan metropolitan area from 2000 to 2035. The simulation results demonstrate the effectiveness of this model in predicting the locations of urban expansion and contraction in advance. Furthermore, we discovered that the overall shrinkage trend is projected to significantly decelerate in the future. These findings offer support for intervention in urban planning, guiding the development of urban spaces and advancing the scientific aspects of urban planning. [ABSTRACT FROM AUTHOR]

Chinese cities are experiencing urban shrinkage due to demographic, environmental, economic, and political changes. However, urban form is another reason for urban shrinkage. This study first identified the shrinking of 293 cities in China based on the values of the change in brightness extracted from multi-year nighttime light data. Next, the characteristics of construction land morphology from 2019 were analyzed using landscape pattern analysis. Finally, the impact of urban form on urban shrinkage was explored using Geodetector. The results show that: (1) In total, 293 cities experienced different degrees of shrinkage. Regions with severe shrinkage were concentrated in the underdeveloped provinces, and autonomous central and western regions of China; moreover, (2) All factors of urban form significantly affected urban shrinkage. The largest q-values were found in patch density (0.144) and urban area (0.133), indicating that the degree of construction land fragmentation and urban area scale affected urban shrinkage the most; and (3) The interaction effects of pairwise factors were mutually or nonlinearly enhanced. The influence of urban form and socio-economic factors was stronger than that of socio-economic factors alone. This shows that the coupling of urban form and socio-economic factors strengthens the impact of urban form on urban shrinkage. [ABSTRACT FROM AUTHOR]

Geographic accessibility plays a key role in health care inequality but remains insufficiently investigated in China, primarily due to the lack of accurate, broad-coverage data on supply and demand. In this paper, we employ an innovative approach to local supply-and-demand conditions to (1) reveal the status quo of the distribution of health care provision and (2) examine whether individual households from communities with different housing prices can acquire equal and adequate quality health care services within and across 361 cities in China. Our findings support previous conclusions that quality hospitals are concentrated in cities with high administrative rankings and developmental levels. However, after accounting for the population size an "accessible" hospital serves, we discern "pro-poor" inequality in accessibility to care (denoted as GAPSD) and that GAPSD decreases along with increases in administrative rankings of cities and in community ratings. This paper is significant for both research and policy-making. Our approach successfully reveals an "unexpected" pattern of health care inequality that has not been reported before, and our findings provide a nationwide, detailed benchmark that facilitates the assessment of health and urban policies, as well as associated policy-making. [ABSTRACT FROM AUTHOR]

This paper adopts a novel approach of Support Vector Machine (SVM) to forecast residential housing prices. as one type of machine learning algorithm, the proposed SVM encompasses a larger set of variables that are recognized as price-influencing and meanwhile enables recognizing the geographical pattern of housing price dynamics. The analytical framework consists of two steps. The first step is to identify the supporting vectors (SVs) to price variances using the stepwise multi-regression approach; and then it is to forecast the housing price variances by employing the SVs identified by the first step as well as other variables postulated by the hedonic price theory, where the housing prices in Taipei City are empirically examined to verify the designed framework. Results computed by nonparametric estimation confirm that the prediction power of using SVM in housing price forecasting is of high accuracy. Further studies are suggested to extract the geographical weights using kernel density estimates to reflect price responses to local quantiles of hedonic attributes. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has put labor-intensive industries at risk, among which the construction industry is a typical one. Practitioners in the construction industry are facing high probabilities of COVID-19 transmission, while their knowledge, attitudes, and practices (KAP) are critical to the prevention of virus spread. This study seeks to investigate the KAP of construction industry practitioners in China through an online questionnaire survey conducted from 15 to 30 June 2020. A total of 702 effective responses were received and analyzed. The results revealed that: (1) although an overwhelming percentage of respondents had the correct knowledge about COVID-19, there were significant respondents (15% of all) who were unsure or wrong about the human-to-human transmission of the virus; (2) practitioners generally showed an optimistic attitude about winning the battle against the COVID-19 pandemic and were satisfied with the governments' contingency measures; (3) practitioners tended to actively take preventive measures, although checking body temperature, wearing face masks, and keeping safe social distance still needs to be reinforced. This research is among the first to identify the KAP of construction industry practitioners toward the COVID-19 pandemic in China. Results presented here have implications for enhancing strategies to reduce and prevent COVID-19 spread in the construction industry., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zheng, Chen and Ma.)