The Grand Canal of China, as a traffic artery in ancient China, has exerted profound influence on the development of the cities, towns and rural settlements along it. Now, with China’s rapid urbanization, numerous settlements along the canal are confronted with problems like slow cognition of the cultural heritage, loss of the local culture and damage of historical relics. Hence, research on the protection and updating of the settlement space along the canal is in urgent need. This paper, targeting the settlement space along the Grand Canal Tianjin Section, adopts such research methods as the Historical GIS analytical method, the kernel density estimation method and the average nearest-neighbor method to quantitatively analyze the evolution stage and distribution characteristics of the settlement space along the Grand Canal Tianjin Section from the perspective of cultural relics to reveal the in-situ rules of evolution of the settlement space. The research result indicates that the spatial-temporal evolution of the settlement space can be divided into five such periods of the settlements along the canal as the pre-canal period, the rudimentary period, the development period, the mature period and the transformation period. Each period features different cultural relics and settlement distribution patterns. The research shows that the natural geographical environment, the grain transportation projects and management systems, the wasteland opening, grain growing and military defense policies, the agricultural, commercial and economic growth and the migration and folk culture are the influencing factors of the spatial evolution of the settlement space along the Grand Canal Tianjin Section.

During the development and evolution of settlements, space morphology created unique local cultural features and played an important role in guiding rural planning in the context of new-type urban development. The in situ characteristics of the space morphology of the ancient historical and cultural towns along the Grand Canal of China reflect the prints of the local culture and history over thousands of years and integrate modern life and the cultural memories of the citizens there. Using Yangliuqing Town, a famous historical and cultural town, as an example, this study quantitatively analyzes the in situ characteristics of the space morphology. It applies the UAV 3D model, POI data, actual site measurements, and other data to establish detailed models of the streets and lanes, quantifies the in situ characteristics of the space morphology of the streets and lanes in terms of space organizational characteristics and VGA manifestation, analyzes the influencing factors of the characteristics of in situ space morphology, and proposes guidelines for renewing ancient towns according to the in situ characteristics of space morphology. The research results indicate that ① multidimensional factors influencing the historical development of the research area have been clarified for the three aspects of its status as a canal transport hub, canal settlement industries, and traditional residential courtyards in ancient towns; ② the in situ space morphology of the streets in Yangliuqing Town is reflected in three aspects such as the core guiding and control of historical and cultural resources, the inherent influence of space element layout, and the attractiveness of street space; ③ it extracts the guidelines for the renewal of the ancient towns in terms of the space morphology strategy, the environmental element strategy, the interface attribute strategy, and the business attribute strategy. The research methods and conclusions boast great significance for clarifying the characteristics of the space morphology of the ancient towns along the Grand Canal and improving the practice of preservation there.

In the urbanization process, phenomena such as the urban heat island effect exacerbate climatic deteriorations, leading to environmental issues in cities. Campus areas, as significant ecological components within the urban environment, play a crucial role in environmental regulation. This paper investigates the impact of outdoor physical environments in campuses on users’ thermal comfort from the perspective of thermal comfort. Using surveys, meteorological measurements, and behavioral analysis, this study examines four distinctive spaces within a campus in Xi’an, establishing a thermal comfort baseline for the population in Xi’an’s campus spaces. The research results indicate: (1) Globe temperature (T_g), air velocity (V_a), air temperature (T_a), and ground temperature (G) are the primary factors affecting students’ thermal sensations in campus open spaces. Respondents tended to improve their thermal sensations through changes in humidity and solar radiation. (2) In the campus open spaces of Xi’an, the overall NPET of the subjects was 13.9 °C, with the NPETR ranging from 9.4 to 18.4 °C. (3) The preferred warmth temperature for university students in Xi’an is 15.15 °C, which is 1.25 °C higher than the NPET (13.9 °C).

Urban park cooling accessibility is often assessed using temporally aggregated thermal performance, which may obscure variation in accessible cooling potential. We combined Landsat-derived park cooling intensity with a fixed network of 77 park destination records and 63 subdistricts in Tianjin, China, across 14 screened summer observations in 2021–2025. Mean cooling accessibility (MeanCA), its 25th percentile (Q25CA), and absolute and relative lower-tail gaps (AG and TAG) were compared across 10, 15, and 20 min catchments. Positive-supply coverage increased from 23 to 41 and 51 subdistricts, while MeanCA and Q25CA retained similar spatial rankings. Among the 23 subdistricts already served at 10 min, TAG showed a small overall threshold difference (Kendall’s W = 0.178); its 10–20 min decline coexisted with an increase in AG. The TAG difference was not significant in the broader 41-subdistrict comparison from 15 to 20 min. Among the 27 eligible multi-source subdistricts, direct Q25CA modelling did not provide clear evidence of an additional asynchrony association after nonlinear MeanCA adjustment. Replacing TAG with AG changed 29 of 63 diagnostic labels. These findings distinguish expanded access from changes in relative and absolute lower-tail gaps. The framework offers a conditional planning diagnosis across observed dates, with category-level conclusions sensitive to indicator choice.