Cities in cold regions face significant challenges, including high carbon emissions, intense energy use, and outdated energy structures, making them critical areas for achieving carbon neutrality and sustainable development. While studies have explored the impact of spatial structures on urban carbon emissions, the effects of multi-scale spatial structures remain insufficiently understood, limiting effective spatial planning strategies. This research examines Changchun, a city in a severe cold region, using data from 2012 to 2021, including road networks, land use, nighttime light, and energy statistics. Employing spatial syntax, landscape pattern indices, random forests, and segmented linear regression, this research establishes a carbon emission translation pathway to analyze the nonlinear effects of multi-scale spatial structures. Findings reveal a 26.70% annual decrease in carbon emissions, with winter emissions 1.84 times higher than summer ones. High-emission zones have shifted from industrial areas to transportation, commercial, and residential zones, reflecting growing seasonal variability and structural changes. Spatial complexity increased while connectivity declined. Multi-scale analysis identified a “decrease–increase–decrease” pattern, with macro-scale centrality declining and micro-scale hierarchy rising. These results provide both theoretical and practical guidance for urban planning in cold regions, supporting early carbon neutrality and long-term sustainable development goals.

The sharp decline in the population along the northeastern border poses a significant threat to the security of the region, the prosperity of border areas, and the stability of the social economy in our country. Effective management of human and land resources is crucial for the high-quality development of border areas. Taking Changbai County on the northeastern border as an example, based on multi-source data such as land use, the natural environment, climate conditions, transportation location, and social economy from 2000 to 2020, the land use transfer matrix, spatial kernel density, and PLUS model were used to analyze the spatio-temporal evolution characteristics of land use and explore simulation scenarios and optimization strategies under different planning concepts. This study reveals the following: (1) During the study period, the construction land continued to increase, but the growth rate slowed down, mainly transferred from cultivated land and forest land, and the spatial structure evolved from a single center to a double center, with the core always concentrated along the border. (2) The distance to the port (transportation location), night light (social economy), slope (natural environment), and average annual temperature (climate conditions) are the main driving factors for the change in construction land, and the PLUS model can effectively simulate the land use trend under population contraction. (3) In the reduction scenario, the construction land decreased by 1.67 km², the scale of Changbai Town slightly reduced, and the contraction around Malugou Town and Badagou Town was more significant. The study shows that the reduction scenario is more conducive to the population aggregation and industrial carrying capacity improvement of shrinking county towns, which is in line with the high-quality development needs of border areas in our country.