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This article uses evolutionary game theory and system dynamics methods to construct an evolutionary game model involving the government, social capital parties, and residents. It explores the optimal stable strategies and influencing factors for green renovation in old residential areas. The study finds that the optimal stable strategy for the three parties is E8(1,1,1), which means government choice incentives, social capital parties choice green renovation, and residents choice payment participation. Moreover, the choice and rate of behavioral strategies for all three parties depend on the strength of government incentives and penalties.

The urban heat island and dry island effects greatly affect people's physical and mental health, and there is almost no previous research on the actual measurement of heat island and dry island effects in specific climate zones. This article conducts experimental research on heat islands and dry islands in urban residential areas, suburbs, and water parks in mild regions, or in areas with large wetland parks, and sets reasonable building spacing. In residential area construction, natural resources such as mountains, water bodies, and wetlands should be preserved more, and residential areas should be planned around the park as much as possible. The construction of wetland parks helps to create a microenvironment and regulate the heat and moisture balance of residential areas, but the size and distance of wetland parks directly affect their contribution effect.

As global climate change intensifies and energy crises deepen, photovoltaic (PV) applications in cities are increasingly garnering attention worldwide. In this context, retrofitting existing high-density residential areas with PV applications is becoming a focus of urban low-carbon development. As the most densely populated city in Western China, Chengdu is characterized by rapid development and high energy consumption. The widespread application of photovoltaic (PV) systems could significantly alleviate its energy consumption issues. This research investigated the PV application potentials of 27 non-residential areas in high-density residential areas in Chengdu, Sichuan Province from a design perspective and proposed design recommendations for PV applications in these spaces. In addition, this study analyzed urban morphological factors affecting the PV generation potential in non-residential areas through a Pearson correlation. The key factors influencing the PV application potential in these areas were building density (BD), non-residential area perimeter-to-area ratio (NBPAR), and maximum building height (Hmax). This research aims to provide new strategies and methods for the low-carbon transformation of future urban high-density residential areas.

In order to solve the problem of extensive land use in rural residential areas and promote the construction of a new socialist countryside and farmland protection, it is important to graspe the temporal and spatial evolution of rural settlements. In this study, with Beijing as an example, the efficiencies of CLUE-S and Markov-CA models in simulating spatial temporal evolution of rural residential areas are analyzed. With 14 driving factors chosen, the land uses in Beijing in 2000 and 2005 are simulated and predicted using the two models. Grid size of 220 m × 220 m is used. The accuracies and Kappa coefficients of the simulation and prediction results are analyzed and the following conclusions are made. The core part of CLUE-S model is logistic regression, which grants it obvious advantage in capturing the trends of land use changes with more discrete distributions. Meanwhile, Markov-CA model takes neighborhood into consideration, making it relatively more advantageous in simulating and predicting changes of land uses with the character of nearest-neighbor diffusion. However, among various land uses, only urban land use has this character, the correct prediction rates of the CLUE-S model in 2000 and 2005 were 60.99% and 81.35%, respectively, while the accuracy of the Markov-CA model prediction was 51.33% and 73.68%, and it is the main reason that CLUE-S model returns better simulation and prediction results of rural residential areas for both 2000 and 2005 than Markov-CA model.

The quality of outdoor space in residential areas is of great importance to residents. However, the existing studies predominately focus on a certain types of open space. In addition, there is lack of objective quantification. In this study, a novel approach is developed in order to quantify the quality of outdoor space based on the identification of value dimensions and the classification of the open spaces. Firstly, the residential outdoor space is divided into six types of open space. Secondly, the value weights of different open spaces are calculated through Structural Equation Modeling (SEM) and Analytic Hierarchy Process (AHP) based on the data from on-site and online questionnaire survey. Finally, the approach developed in this study was tested in high intensity residential areas. Results of this study helps to better understand the quality of outdoor space in high intensity residential development, hence provides useful inputs for the future planning of such developments.

A slope with soil from soft to medium consistency is at risk of slope failure. This situation occurred in a residential area located Southwest of Jakarta. Due to heavy rainfall, a slope next to an existing road which runs alongside a river experienced slope failure. Three alternatives were considered to prevent occurrence of slope failures. The methods considered were mechanically stabilized earth retaining wall, and sheet pile with two possible positions, i.e., crest of slope or mid-slope. In this paper, the three alternatives are presented. Due to a second slope failure which occurred, sheet pile installed at the crest of the slope was chosen as it provides the quickest installation time to stabilize the slope.

The renovation problem of old residential areas is not only a city management task, but also a major engineering of benefiting the people, which is related to the people living and working in peace and contentment and the improvement of the overall image of the city. In order to improve the appearance of old residential areas in Chinese cities and the living conditions of their residents, city planners must take a scientific and structured approach to renovation. After analyzing current status of the old residential in several major Chinese cities, consulting the literature, and undertaking field investigations, this paper summarizes the main influencing factors on renovation decision-making. We propose five hypotheses, which we test using questionnaire survey data, sample analysis of these influencing factors, and a structural equation model (SEM). The results show that the degree of influence of each factor on renovation decisions ranks as technology being the most influential, followed by the economy, policy, the environment, and society. In addition, we find that there is nonzero correlation between these various factors.

Background and aim Children growing up in vulnerable circumstances have a higher risk of caries experience. Tracking the development of caries in relation to socioeconomic variables over time is essential for fair resource distribution to groups with higher caries risk and to even out inequalities in oral health. The aim was therefore to analyse the association between 6-year-olds´ caries prevalence and socioeconomic variables at family and residential area levels in 2010 and 2019 as well as potential differences in the association between 2010 and 2019. Methods The study design is an epidemiological registry-based, repeated cross-sectional study based on caries data (grouped as 0, 1–3 and > 3 dmft) for the population of 6-year-olds in 2010 ( n  = 4,408, 95% coverage) and 2019 ( n  = 5,199, 94% coverage) in a Swedish region. Multiple socioeconomic variables for the children’s families and residential areas were retrieved from official registries. Multinomial logistic regression was performed at both levels to produce models for each level and studied year. Results The variables that explained most of the association between caries and socioeconomic variables were mainly the same over the years at both levels. At the family level, these were: maternal age when having their first child (explained most of the association in both years, at 30 and 35%, respectively); maternal age when having the child in the study group; parental employment; parental and child’s migration background; maternal educational level; form of housing; and financial assistance (only 2010). At the residential area level, these were: migration background (explained most of the association both years; 82 and 52%, respectively), educational level and number of persons per household. The association between socioeconomic variables and caries was consistently stronger for severe caries (dmft > 3) than moderate (dmft 1–3). Multiple socioeconomic risk variables meant an even greater likelihood of caries. Conclusion Over the studied years, variables related to socioeconomic vulnerability continued to be associated with caries in young children growing up under socially disadvantaged circumstances. Effective efforts for families living in socially vulnerable contexts are needed to achieve good and equal oral health, as is continued follow-up to evaluate whether the goal is reached.

Accessibility is essential in land-use transport interaction frameworks. For residential location choices in particular, it has always been important at the theoretical level. At the empirical level, the place of accessibility is questioned in some works, considering other more important location characteristics, like the social environment and the neighbourhood amenities. However, this result can be caused by the measurement of accessibility. In view of the wealth of approaches, this paper examines whether different accessibility measures can lead to divergent results. Using a residential location choice model for the Lyon urban area in France, we test various accessibility indicators and we compare the results. We conclude that accessibility is an indispensable variable. Without it, the model gives inconsistent results. Complex accessibility measures give better results but simple measures are also relevant for residential location choices modelling. The choice highly depends on the objectives of the application especially if the model is to be used for simulation.

New public transport investment can improve accessibility for existing and new users of the urban transport network and this can lead to land value uplift with uplift benefits being distributed in relation to the proximity of the location of the property to the infrastructure. This paper quantifies land value uplift and its spatial distribution for accessibility to different destinations for residential properties around a new-build Liverpool Parramatta transitway for buses in a suburban area of south-west Sydney, Australia. Geographically weighted regression (GWR) is used to take account of spatial dependency in the estimation process with the results being presented in map form. Results indicate that property prices are mainly determined by the property's internal features and the neighbourhood effects, but accessibility by car and accessibility to employment along the transitway also contribute nonmarginally. The GWR local model shows that accessibility varies significantly over geographical space demonstrating the advantages of this approach.