This study integrates the analysis of surface temperature data with natural and anthropogenic factors closely related to the urban thermal environment in Nanjing from 2000 to 2020, exploring the spatiotemporal variation characteristics of the urban heat island effect and the interactive relationships among its influencing factors. The research findings are as follows: (1) Between 2000 and 2020, the urban heat island effect in Nanjing exhibited an expansion trend radiating from the city center to the periphery, with the heat island phenomenon primarily concentrated in the old urban areas characterized by developed commerce, industry, and dense populations. Surface temperatures gradually decreased from the city center to the suburbs, forming a distinct spatial distribution gradient. Both the standard deviation ellipse and the centroid of high-temperature areas showed a southward shift. (2) Significant differences in surface temperatures were observed across different land use types, with built-up areas and arable land maintaining relatively stable and higher surface temperatures, while water bodies and forests exhibited lower and stable surface temperatures. (3) Vegetation coverage, normalized water body index, elevation, dispersion, and the Shannon diversity index were negatively correlated with surface temperature, while the normalized difference bare land index, building index, dispersion index, and patch cohesion index were positively correlated with surface temperature. In Nanjing, the interactive effects of dual factors on the urban heat island effect were found to be greater than those of individual factors, with vegetation coverage identified as the most critical factor affecting surface temperature. Considering multidimensional factors together enhances the understanding of the spatial patterns and causes of the urban heat island effect, clarifies the interrelationships and degrees of influence among natural, socio-economic, and landscape pattern factors, and provides a scientific basis for improving the quality of the living environment in Nanjing.

With the severe challenges resulting from global climate change, the role of land use/land cover (LU/LC) optimization in mitigating carbon emissions and promoting carbon cycle balance has gained increasing attention. This study takes Jiangsu Province as a case study, analyzing the changes in LU/LC from 1995 to 2020 and their impacts on carbon emissions and carbon storage. For Jiangsu Province’s five development scenarios in 2030 (business-as-usual, carbon emission, carbon storage, and carbon neutrality scenarios), objective functions and constraints were constructed. The PLUS model was employed to simulate land use for 2030, predicting carbon storage, economic benefits, and ecological benefits under each scenario and evaluating the impact of each scenario on achieving carbon peaking and carbon neutrality goals. The findings indicate that (1) from 1995 to 2020 there were great changes in land use types in Jiangsu Province, with an overall downward trend in carbon storage. (2) The simulated land use quantity structure and spatial patterns for 2030 under different scenarios exhibited significant differences. Compared with the Business-as-Usual Scenario, the other four optimized scenarios achieved a better balance between economic and ecological values. (3) The Integrated Scenario realized optimal synergy between farmland protection, ecological expansion, and economic output, representing the best compromise under multiple objectives.