Urban forests are one of the most ecologically significant systems in urban ecosystems. To make the layout and input–output ratio of urban forests more economically rational for sustainable strategic planning, it is necessary to assess the ecological benefits and ecosystem services of urban forests according to the local geographical characteristics of different cities and analyse their cost–benefit relationships. In this study, the i-Tree Eco model was used to assess the ecological benefits of urban forests in terms of four aspects: carbon sequestration and oxygen release, energy saving, rainwater retention, and air quality improvement. To translate them into economic benefits, using mathematical and statistical analysis, the cost–benefit relationship of urban forests with different tree and shrub proportions was analysed, and the impact range of urban forests with different layout types was compared. The research found that: (1) tree species are the main influencing factor of urban forest ecological benefits, (2) linear urban forests have a wider impact range, (3) if the proportion of trees in urban forests in the research area is adjusted to 0.36, the ecological benefits can increase by RMB 0.061 billion per year. We provide efficient and convenient research paths and tools for studying the cost–benefit relationship. By using an i-Tree Eco model, we realized the economic characteristics of urban forests. This research provides quantitative support for the balanced construction of urban ecological civilization and economic benefits. It can provide quantitative support for a balance between urban ecological development, economic development, and spatial optimization.

The harsh climate and the aging of urban populations have negatively impacted the quality of life of the elderly in severely cold regions. As a result, there is an urgent need to improve environment quality and accurately evaluate outdoor thermal comfort. However, existing studies have paid little attention to older adults living in severely cold climates. This paper aims to fill this gap by studying the elderly population in severely cold cities with high aging rates in China. By combining on-site testing, questionnaire surveys, CFD modeling, parametric computing, and statistical analysis, the study presents an adapted UTCI for elderly people, as well as multi-seasonal prediction models. The results (1) show that the neutral ranges of the UTCI are significantly affected by both climate zones and age groups. Older people are more tolerant to heat but more sensitive to cold. (2) The results also reveal the importance of factors such as air temperature, wind speed, solar radiation temperature, wind direction, relative humidity, and cloud cover in evaluating outdoor thermal comfort. (3) Multi-seasonal thermal comfort models based on neural networks were developed, and empirical studies verified that the model had the highest accuracy in the transitional season and the lowest accuracy in the winter season.

Traditional villages have reached milestones in developing a living culture, politics, economy, and society, among other aspects, while acting as important carriers of agricultural culture formed by long-term interactions between humans and nature. Unfortunately, traditional villages could disappear with the advent of urbanization. Therefore, this study enhances the accuracy of traditional village classification protection work by examining traditional villages in the Jinjiang River Basin in Quanzhou, China. A spatial pattern is extracted for the socio-ecological systems (SES) prototype of traditional villages, and an SES classification protection system is constructed based on a prototype analysis. Given the evaluation results, a K-means cluster analysis is applied to establish the SES sustainability levels for six types of traditional villages. After adjusting the types according to the principles of sustainability, equilibrium, and individual cases, six SES system types are identified: SES decay and shrinkage (Type 1), SES fusion and development (Type 2), SES ecological decline (Type 3), SES social decline (Type 4), SES ecological conservation (Type 5), and SES extensive development (Type 6). This system provides a quantitative analysis method to classify and protect concentrated and contiguous traditional villages. It also helps facilitate a better understanding of local rural society, economy, and culture, especially a deeper understanding of the interactions between humans and the rural environment.

Many developing countries are challenged with the revival of rural vitality against increasing urbanization. Rural tourism is effective in enhancing the countryside’s vitality. Previous studies used qualitative methods to explore the spatial organization of resources, but it was difficult to quantify the effective organization of tourism resources. Taking the example of Jilin Province, China, this study quantitatively measured the use of tourism resources in rural areas at the initial stage and created a developmental model to organize tourism resources more effectively. The organization mechanism has specific reference significance for the optimization model of upgrading rural tourism in developing countries. Spatial performance measurement was used to evaluate the spatial performance of rural tourism resources in the case area. The specific research included analyzing the coupling mechanism of rural tourism resources, constructing an evaluation system, analyzing a resource regulation mechanism, and establishing a rural tourism network model through a complex network analysis method and dynamic simulation. According to the spatial performance analysis, the allocation and linkage of various tourism-related elements are not yet mature. The structural restructuring mode in Jilin Province is mainly divided into internal and external dual-drive guidance, secondary integration, and a characteristic linkage mode. An organizational mechanism for optimizing tourism resources was proposed, which could be referred to for evaluating and optimally organizing the tourism resources in the rural areas of developing countries.

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.

Chunyuan Yuan, Chong Zhang, Zhen Fang, Ming Pang, Xue Jiang, Changping Peng, Zhangang Lin, Ching Law. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track). 2025.