In areas with a dry and hot climate, factors such as strong solar radiation, high temperature, low humidity, dazzling light, and dust storms can tremendously reduce people’s thermal comfort. Therefore, researchers are paying more attention to outdoor thermal comfort in urban environments as part of urban design. This study proposed an automatic workflow to optimize urban spatial forms with the aim of improvement of outdoor thermal comfort conditions, characterized by the universal thermal climate index (UTCI). A city with a dry and hot climate—Kashgar, China—is further selected as an actual case study of an urban block and Rhino & Grasshopper is the platform used to conduct simulation and optimization process with the genetic algorithm. Results showed that in summer, the proposed method can reduce the averaged UTCI from 31.17 to 27.43 °C, a decrease of about 3.74 °C, and reduce mean radiation temperature (MRT) from 43.94 to 41.29 °C, a decrease of about 2.65 °C.

A performance-driven sustainable urban design is an important step in adapting to local climates and improving outdoor comfort level. This study proposed investigating an urban layout optimization method, validated in an urban area in Shenyang City, a cold region, that comprises nine urban blocks. This study selected an urban block type and street width as optimization input indices and defined the percentage of acceptable universal thermal comfort index (UTCI) range as the objective. The genetic algorithm is applied to optimize and generate an urban block to maximize the percentage of acceptable UTCI range at urban block level and street level. When the comfort level is set as −17–20 °C, optimization can achieve 87.7% of acceptable UTCI in the urban block level and 90.3% at urban street level. To attain an urban layout with higher than 85% acceptable UTCI range, results found, in a cold region, multistory blocks are more suitable than high-rise blocks and open spaces; it would be better to place multistory blocks with high building enclosures on the north side to block cold wind.

Assessing social values attributed to ecosystem services based on the Social Values for Ecosystem Services (SolVES) model helps ecosystems to provide services sustainably, including land and forest products and non-material services. Currently, urbanization has accelerated the deterioration of rural environments, which affects the supply of social values for rural ecosystem services. How to scientifically assess the social values for ecosystem services in rural areas remains to be studied. In addition, there are significant differences in the perceptions of social value among stakeholder groups. Therefore, this study aims to provide a complete and systematic approach to identify the social value of complex and specific rural ecosystem services and to fill the gap in the research of perceived differences among stakeholder groups in rural areas. On the basis of building environmental raster datasets on a village scale, this research applies the SolVES model to evaluate social values in the Paifang rural community. Results show that aesthetic, health care, recreation, and biodiversity values are highly regarded in rural areas. The normalized difference vegetation index, the distance to rural settlements, the distance to tourist attractions, and the distance to agricultural production spaces can improve the evaluation accuracy, and the level of social values can be predicted by certain environmental variables. The spatial distribution of social values and the degree of attention paid to the biodiversity value, and the trade-off between the aesthetic and biodiversity value are the main perception differences between villagers and tourists. This research contributes to ecological construction and sustainable development in rural areas.

Due to rapid changes in urban and rural economic development, the Chinese landscape has been gradually transforming toward urbanization. Most Chinese rural villages face declining problems such as population loss, land use transformation, fragmentation and abandonment, resulting in big changes in the rural spatial morphology. To understand these urbanization challenges, this study established a multi-factor methodology and applied it to a case study of three selected typical villages in southern Jiangsu Province. From this analysis, the quantification of the rural spatial morphology and environmental status, from 2005 to 2016, was determined. The eight driving factors established considered the rural geological location, landform, and social economic status. To analyze the driving factors, a quantitative analysis using ArcGIS, Environment for Visualizing Images (ENVI), and Analytic Network Process (ANP) decision-making methods were used. The results revealed mechanisms between the changes to spatial morphology of rural villages in southern Jiangsu Province and their key driving factors. This study provides data support and a theoretical framework to guide future development and policy of rural villages of different types, which supports the sustainable development of Chinese rural villages.

The layout relationship between the public space system and the natural system of cities determines the trend of urban spatial forms. From the perspective of the integration of landscape architecture and urban design discipline, this paper generalizes three restriction/dependence relationship modes between urban public space and natural landscape layout: (1) overlapping mode, (2) separation mode, and (3) the mode of edge combination. Using Zurich, Switzerland, as a case study, this paper quantitatively explores the layout relationship between public space and natural landscape using the location quotient method. The research findings reveal an obvious layer distribution trend of Zurich urban public space and natural factors: the public space and mountain layout have a clear separation relationship. The regressive equation is PQ = −0.188lnMQ + 0.660, forming the mutually supplementary mechanism of the advantageous resources of public activities. The Zurich model shows that when a proper relationship is established among the natural system and the urban public space, human activities, and the public activity centers of the city, the new system provides significant ecological and social benefits. This finding provides an exemplary reference for urban construction in other countries.

Social equity/inequity and equal/unequal rights to the city extend beyond the distribution of urban parks and green spaces, necessitating research on equitable accessibility to encompass a broader range of public spaces. However, previous research has predominantly focused on green spaces, neglecting other types of public spaces. To address this gap, the present study takes the public space pattern of Nanjing Old City as the research object, employing the minimum distance method, the gravity potential method, and bivariate local Moran’s I to evaluate the matching relationship between the demand of socially vulnerable groups and the supply of public spaces, as well as its temporal–spatial evolution from 2010 to 2020. The results reveal spatial heterogeneity in the accessibility of public spaces for vulnerable groups at the block level, with 28.1% of the total number of blocks and 22.1% of the total area of blocks experiencing a supply–demand imbalance in 2010. From 2010 to 2020, under the rapid urban development, construction of public spaces, and the general decline in population density and proportion of vulnerable populations, the supply–demand imbalance has exacerbated the distribution of public spaces at both individual and aggregate levels. This imbalance is reflected in the deteriorated accessibility of public spaces for vulnerable groups. This study reveals the mismatches between development, population movement, and public space construction in the old city of Nanjing over the past decade, providing decision-making suggestions and foundations for the future optimization of public spaces, thereby offering an effective tool for assessing and improving the accessibility and equitable distribution of public spaces based on the needs of vulnerable groups.