The increasing demand of humankind has caused a large number of land use changes, which pose a direct or indirect threat to the environment while promoting economic growth. The lack of risk-oriented land use changes may increase the disaster risk in the region. Therefore, how to study the relationship between land use change and disaster risk deserves attention. In this study, a research framework with quantitative relationship between land use change and disaster risk was constructed from the perspective of efficiency. The framework integrated land use change, disaster losses and environment variable (runoff increment) into a three-stage data envelopment analysis (DEA) assessment model to dynamically evaluate the impact of land use changes on disasters. The main conclusions include: (I) after the influence of runoff increment and random error was excluded, the overall risk score of counties and cities in Taiwan is 0.643, which represents a relatively high level, indicating that land use changes have caused high disaster risk; and (II) the vulnerability of land development in each county and city can be obtained through the comprehensive score of disaster risk the amount of unused input. The results of this study can help government agencies to rank various types of land development and then determine the acceptable risk level and incorporate disaster risk into land development.

The continuous change process in the impact of differences in public transport accessibility has not been explained specifically in previous studies. This study reveals that the interaction between two continuous explanatory variables has a significant impact on the explained variable in the hedonic model. The study takes the accessibility variable in the house price model as an instance, dividing the accessibility variable of the residential community into two parts. The first part is the rail accessibility defined by the Euclidean distance from the residential community to the nearest rail transportation station. The second part is the road accessibility defined by two Space Syntax indicators, connectivity and carrying capacity, according to the spatial pattern of the road network. As demonstrated by the spatial interactive regression model, this research finds that road connectivity has a significant regulating effect on the impact of the distance to the closest rail station on house prices based on the empirical evidence from Fuzhou, China.

With the acceleration of climate change and urbanisation, Chinese cities are facing increasingly severe flood risks. To address this challenge, China began implementing its sponge city policy in 2013, leveraging low-impact development, green infrastructure construction, and integrated water resource management to enhance urban resilience to floods and improve water security. This study utilises the Web of Science database as a reference, retrieving 201 relevant literature sources. From these, 61 studies closely related to China’s sponge city policy and urban flood management were selected. CiteSpace was employed to conduct keyword co-occurrence and temporal evolution analyses, comprehensively outlining the research hotspots and developmental trajectory of this field. The results indicate that research content has gradually shifted from early engineering-based flood control models to multi-objective, interdisciplinary comprehensive management, encompassing flood risk assessment, policy implementation mechanisms, integration of green infrastructure, and economic feasibility analysis. Based on this, this paper constructs an analytical framework incorporating technical, environmental, institutional, and social dimensions to integrate existing research findings, while identifying gaps in cross-scale coordination, smart management, and public participation. The research conclusions can provide valuable references for future policy optimisation and urban sustainable development.

At present, the evaluation of the comprehensive performance of urban office buildings remains an area of significant discussion. This research aims to optimize the building performance of office buildings in the hot summer and warm winter (HSWW) region, focusing on three key aspects: energy use intensity (EUI), useful daylight illuminance (UDI), and percentage of thermal comfort (PTC). The study employs the Hyperparameter Optimization (Hyperopt)-Categorical Boosting (CatBoost)-Strength Pareto Evolutionary Algorithm 2 (SPEA2) multi-objective optimization method, generating 3,000 datasets via Latin Hypercube Sampling (LHS). Building performance parameters are simulated using the Ladybug and Honeybee models, and energy consumption and comfort levels are predicted using the CatBoost model. Subsequently, Hyperopt is used to optimize hyperparameters, and the SPEA2 algorithm is applied to identify Pareto optimal solutions. The results indicate that Hyperopt-CatBoost demonstrates excellent predictive performance, with R² values of 0.996, 0.954, and 0.985 for energy consumption, lighting, and thermal comfort, respectively. By using the SPEA2 multi-objective optimization (MOO) algorithm to optimize design parameters, energy consumption is reduced by 29.61%, lighting efficiency improves by 59.61%, and comfort increases by 37.69% compared to the original design. This study provides a systematic optimization plan and data support for energy-saving design, improving comfort, and enhancing lighting efficiency for office building renovation in urban villages.

The distinct cultural environment of various regions leads to unique consumer preferences for building facades, including the colours and materials that are used for the exteriors of condominium buildings. Understanding these preferences holds significant industry reference value for urban planning authorities and residential development companies. However, the colour and material aesthetic preferences of consumers for building facades have not received much research attention. To fill this gap, this study empirically investigates these preferences within the cultural context of Fuzhou, China. Using house prices as a reference perspective and econometric methods as research tools, this study explores the specific aesthetic preferences of urban consumer groups and compares the preferences of groups with different levels of consumption. The results confirm the existence of specific consumer preferences for building facade colours and materials and a close connection among the variations in these preferences and various combinations of facade colours and materials. Different quantities and types of materials can lead to distinct preferences for the quantities and features of facade colours. Apart from providing precise professional insights for urban planning authorities and residential developers, this study also offers a feasible conceptual reference for future studies to be conducted in other regions.

Urban densification intensifies the heat island effect, threatening ecological security. Green spaces, as crucial spatial elements in regulating the urban thermal environment, remain poorly understood in terms of their morphological characteristics and regulatory mechanisms, with a lack of systematic quantification and recognition of diurnal variations. This study, focusing on Shanghai’s main urban area, constructs physiological, physical, and morphological variables of green spaces based on high-resolution remote sensing data and the MSPA landscape morphology analysis framework. By integrating machine learning models with the SHAP interpretation algorithm, it analyses the influence mechanism of green spaces on Land Surface Temperature (LST) and its non-linear characteristics from the perspective of diurnal variation. The results indicate the following: (1) Green spaces exhibit pronounced diurnal variation in LST influence. Daytime cooling is primarily driven by vegetation cover, vegetation activity, and surface albedo through evapotranspiration and shading; night-time cooling depends on soil moisture and green space spatial structure and is achieved via thermal storage-radiative heat dissipation and cold air transport. (2) Green space indicators exhibit pronounced nonlinearity and threshold effects on LST. Optimal cooling efficiency occurs under moderate vegetation activity and moderate humidity conditions, whereas extreme high humidity or high vegetation activity may induce heat retention effects. (3) Day–night thermal regulation mechanisms differ markedly. Daytime cooling primarily depends on vegetation transpiration and shading to suppress surface warming; night-time cooling is dominated by soil thermal storage release, longwave radiation dissipation, and ventilation transport, enabling cold air to diffuse across the city and establishing a stable, three-dimensional nocturnal cooling effect. This study systematically reveals the distinct diurnal cooling mechanisms of high-density urban green spaces, providing theoretical support for refined urban thermal environment management.