Heritage is the commonwealth of all humankind. In the context of the rise in global tourism and the continuous deepening of cultural and tourism integration, tourism has emerged as an effective vehicle for the preservation and development of heritage sites. However, it also imposes adverse effects on the local ecological environment and heritage sites, exerting significant pressure on regional sustainable development. In this study, three cities along Jianmen Shu Road were selected as the study area. A comprehensive evaluation index system was developed for tourism ecological security (TES) based on the Driver–Pressure–State–Impact–Response model, and an in-depth analysis of its spatial–temporal evolution characteristics, spatial–temporal migration trends, and influencing factors was performed. The results show that (1) from 2012 to 2022, the average TES in the study area decreased annually, while it increased in Jiange County, Anzhou District, and Santai County. The TES indices were generally higher in areas with a high density of heritage sites or developed economies. Additionally, the districts and counties along the Jianmen Shu Road route never exhibited a deteriorated state. (2) From 2012 to 2022, TES in the study area exhibited an obvious “northeast–southwest” directional pattern, and its center of gravity followed a “V”-shaped trajectory. Overall, the spatial patterns showed minimal variation and exhibited agglomeration characteristics. (3) From 2012 to 2022, the main factors influencing TES included the density of Jianmen Shu Road heritage sites (S6), the number of 3A and above scenic areas (S5), the proportion of cultural tourism and sports in total expenditure (R3), the Normalized Difference Vegetation Index (NDVI) (S4), and other tourism and environmental factors. Moreover, TES systems are becoming increasingly complex and diverse. Finally, based on the results, a comprehensive conceptual framework of the driving mechanism was developed. Additionally, four targeted and scientifically grounded policy recommendations were formulated for restoring, protecting, and managing the TES in the Jianmen Shu Road Heritage Area. This study provides significant reference value for ecological environment preservation and the high-quality development of cultural tourism integration in heritage areas.

Land utilization—a crucial resource for human survival and development—reflects the outcomes of intricate interactions between human communities and their respective environments. The Jianmen Shu Road Heritage Area presents both opportunities and challenges in terms of protection and development. Any alterations in its land use and landscape patterns directly impact the sustainable development of the regional environment and heritage sites. In this study, we considered three cities along the Jianmen Shu Road, analyzed the evolution characteristics of land use and landscape patterns from 2012 to 2022, and used the multi-criteria evaluation–cellular automata-Markov (MCE-CA-Markov) model to predict the land use and landscape patterns in 2027. The results show the following: (1) From 2012 to 2022, forest land was at its greatest extent, the growth rate of forest land increased, the loss rate of cropland increased, and impervious land continued to expand. (2) From 2012 to 2022, the degrees of fragmentation in cropland, impervious land, and grassland increased; water area had the highest connectivity; forest land had the lowest connectivity; and barren land had the highest degree of separation. The degree of fragmentation and connectivity of the landscape patterns decreased, the degree of complexity increased, and landscape diversity increased and gradually stabilized. (3) Predictions for 2022–2027 indicate that forest land, impervious land, grassland, and barren land will increase, whereas cropland and the water area will decrease. The growth rate of grassland will increase, the loss rates of cropland and water area will decrease, and the growth rates of impervious land and forest land will decrease. (4) Further predictions for 2022–2027 indicate that the density and complexity of the grassland edge will decrease, whereas the fragmentation and complexity of the remaining patches will increase. The degree of fragmentation, complexity, connectivity, and separation of landscape patterns will increase significantly, whereas landscape diversity will remain stable. This study deepens our understanding of how land use and landscape patterns change in the heritage area from a long-term perspective that involves both the past and future. Such research can provide crucial information for tourism management, heritage protection, and spatial planning in the heritage area and, thus, has important management implications for the study area and similar heritage areas in other regions.

This study examines how visual features and green space morphology jointly shape restorative perception in dog-friendly urban green spaces using a data-driven analytical framework. A self-constructed dataset integrating street-view imagery, landscape element composition, and morphological metrics was developed to quantify visual entropy, visual richness, and spatial structure. Ten dimensions of visual perception were modeled using an XGBoost framework optimized with a genetic algorithm, achieving high predictive performance (R² = 0.827–0.989). Streetscape analysis revealed relatively stable visual entropy but pronounced heterogeneity in visual richness, reflecting variability in color, form, and spatial layering. Element-level decomposition showed the visual dominance of natural components, particularly trees, sky, and grass. Piecewise linear regression further identified threshold-dependent and dimension-specific effects of green space proportion, fragmentation, patch size, connectivity, aggregation, and shape complexity. Moderate fragmentation and aggregation enhanced perceived complexity and stimulation, whereas excessive shape complexity reduced most restorative responses.

Urban mental health burdens are increasing, prompting interest in how nearby green spaces aid emotional restoration. Bamboo-dominant green spaces are widespread in East Asia, but evidence connecting their management and structural features to restorative experiences is limited. This study conducted a controlled photo-exposure experiment in Ya’an, China, to examine how bamboo space typology and structural attributes relate to visual attention, affective responses, and short-term physiological recovery. One hundred and twenty participants viewed 50 photographs representing five bamboo space types (ecological conservation, productive–economic, protective–greenbelt, landscape–recreational, and understory–composite). Each image was linked to a matched field plot, enabling integration of structural indicators with eye tracking, EEG β/α, and repeated ratings of relaxation, pleasure, and preference. Results showed that landscape–recreational spaces received the highest affective ratings, while understory–composite spaces had longer fixations, indicating higher visual processing demands. Vertical stratification and groundcover coverage were robust predictors of affect beyond typology. Eye-movement metrics did not mediate structure–affect associations, and EEG β/α, as an auxiliary and context-dependent indicator under brief photo-based exposure, showed limited sensitivity. These findings offer insights into structural elements that can inform the design and management of bamboo green spaces for improved emotional restoration.