The accelerating processes of globalization and modernization have imposed unprecedented anthropogenic pressures on the cultural diversity of historic districts, leading to the physical degradation of historical heritage and the fragmentation of cultural transmission chains. To address this challenge, this study establishes an innovative spatial-gene theoretical framework that seeks to balance heritage protection with urban development by integrating landscape characteristics and cultural connotations, thereby enhancing the conservation of cultural diversity in historic districts. Focusing on the historic Small Wild Goose Pagoda district as a case study, we developed a comprehensive methodology integrating field research, historical induction, spatial analysis, and place-making. Through this operational framework, we systematically identified four constitutive spatial genes: the mountain–water pattern, the urban-axis, the li-fang, and the architectural courtyard. These genetic elements inform a dual-regeneration strategy that promotes synergy and dialogue between old and new: (1) place-making guided by historical morphological grammar rules and (2) activity organization that reconfigures the value system of “openness and inclusiveness”. This research not only advances spatial-gene theory but also provides a replicable model for regenerating historic districts oriented toward cultural diversity, effectively combining historical authenticity with contemporary functionality to promote sustainable urban development.

Small cities warrant focused attention for robust low-carbon development strategies due to their significant numbers. In these cities, residential buildings emerge as notable contributors to carbon emissions, consuming substantial energy in their operations. This study employs an optimized IPAT equation, utilizing government statistical data, satellite remote sensing images, and panel data models to analyze the impact of the urban environment on carbon emissions from residential building operations (CERBOs) in 36 small Chinese cities. The findings reveal geographical variations in sensitivity to scale, economic, and spatial structure factors. Population size, municipal jurisdiction area, urbanization level, GDP, and per capita disposable income significantly contribute to CERBOs. Particularly, a 1% increase in municipal jurisdiction area leads to a 1.698% increase in total CERBOs, the highest influencing factor. Spatial structure only affects western cities, with compact development being more conducive to reducing CERBOs. Notably, carbon emissions from electricity are more influenced by environmental factors than those from heating and gas. The study proposes region-specific low-carbon planning strategies based on these findings. The theoretical optimization model proposed in the study, as well as the identified impact factors, will provide a theoretical basis and data support for understanding and reducing carbon emissions in small cities.