Clarifying the factors that influence land surface temperature (LST) is crucial for proposing specific LST mitigation strategies. This article focuses on the Beijing–Tianjin–Hebei (BTH) region and investigates the LST influencing factors of various local climate zone (LCZ) built types from perspectives of urban morphology, land cover, and human activity. The results suggest that the areas of urban LCZ built types vary across cities within the BTH region, attributed to differences in city size and gross domestic product (GDP). The area of urban LCZ built types in Beijing and Tianjin, cities with significantly high city sizes and GDP, exceeds 2000 km ² . In contrast, in Qinhuangdao, Zhangjiakou, and Chengde, which have relatively low GDP, this area is less than 500 km ² . However, the main LST influencing factors for the same LCZ built type across cities are highly consistent. Building coverage ratio (BCR), average building height (ABH), and pervious surface fraction (PSF) are the three most important factors. The correlation between BCR and LST is mainly concentrated on compact high-rise and open high-rise types, with Pearson correlation coefficient ( r ) ranging from 0.2 to 0.44; the correlation between ABH and LST is mainly concentrated on compact high-rise, compact mid-rise, open high-rise, and open mid-rise types, with r ranging from −0.2 to −0.52; the correlation between PSF and LST is concentrated on almost all LCZ built types in cities within the BTH region, with r ranging from −0.2 to −0.56. By integrating these findings with the features of each LCZ built type within the BTH region, the specific LST mitigation strategies were further proposed. This article can help to develop specific LST mitigation strategies within the context of coordinated development of the BTH region, thereby promoting healthy and sustainable development in the region.

The ecological environment is crucial for human health and sustainable development. As urbanization and urban expansion have a significant impact on ecological environment quality, it is necessary to incorporate indicators that characterize urban morphological features into the ecological environment quality evaluations. This study combines the remote sensing ecological index (RSEI) with the local climate zone (LCZ) scheme to evaluate the ecological quality of urban environments and analyze spatial heterogeneity across cities in the Beijing-Tianjin-Hebei region. The results reveal that the same LCZ categories exhibit similar RSEI characteristics across different cities, validating the effectiveness of the LCZ scheme in assessing urban ecological quality. Among them, sparsely built and open low-rise types consistently show higher ecological quality, whereas compact high-rise and heavy industrial types are associated with lower RSEI values. In terms of the influencing factors, land cover indicators—particularly the normalized difference built-up index, tree height, and pervious surface fraction—emerge as dominant drivers. Urban morphological, climatic, and socioeconomic factors also influenced specific LCZ categories in certain cities. The findings underscore the importance of integrating ecological considerations into urban planning, particularly in highly urbanized and industrialized areas. Strategies should focus on increasing vegetation cover, optimizing building density, and mitigating the adverse effects of urban expansion and industrialization to improve urban ecological quality.

This study investigates how Karamay, a typical mining city in Northwest China, has expanded and evolved over the last three decades (1994–2021) with a special study area of the oil production “townships” which fully expressed the characteristics of the scattered spatial pattern of oil cities, by using remote sensing (RS) images and geographical information system (GIS) spatial analyses. The expansion rate and urbanization development index, spatial orientation, and urban compactness are used to discuss the expansion features. The results indicate that Karamay city has continued to expand in the past 30 years, and there were two stages of urban expansion regarding expansion orientation. During the expansion, there was a trend toward more urban compactness. Karamay’s urban space has gradually evolved from the original scattered distribution of townships to functionally concentrated urban areas. Socioeconomic factors and multilevel policies were the main factors influencing urban expansion. Suggested strategies for the future development of oil cities in China were given accordingly. Two main innovative points are presented in this paper. First, a unique perspective was given on spatial changes in oil townships to better capture how industrial activities influence the urban expansion of oil cities, which has not been found in other studies. Second, this study is the first to combine the urban expansion process with the changing of scattered spatial characteristics of cities, which has reference significance for the sustainable development of these types of cities and contributes to the diversity of case backgrounds for discussing the possibility of compact urban growth.

With global warming and the increasing frequency of extreme heat events, heat health risk assessment (HHRA) has become a critical topic in climate change studies. However, the study themes, methods, and governance orientation of HHRA vary significantly across spatial scales, limiting the comparability and practical integration of assessment outcomes. This study conducts a review of the HHRA literature from 2007 to 2025, analyzing publication trends and evolving research paradigms. The results indicate the following: (1) rapid growth in the field with a notable shift from identifying static vulnerabilities to adopting “Hazard–Exposure–Vulnerability–Adaptability” (HEVA) frameworks, particularly at the micro-scale; (2) a clear scale-dependent hierarchy in assessment focus, where macro-scale studies identify regional trends, meso-scale research targets urban spatial heterogeneity and green–blue infrastructure, and micro-scale assessments emphasize housing conditions and individual perceptions; and (3) machine learning has been widely applied to capture complex nonlinear mechanisms and threshold effects. Finally, this study further emphasizes the importance of establishing a full-process feedback mechanism from macro-level early warning to meso-scale planning and micro-scale intervention, bridging the gap between regional policy and community-level action and providing a theoretical foundation for building climate-resilient cities.