Context: The establishment of an ecosystem health assessment framework from a human–environment view is vital to landscape sustainability. Although several studies have improved the assessment framework by integrating ecosystem services (ESs) supply or demand, consideration of the sustainable supply of ESs is lacking. Objectives: The objective of this paper is to improve the current methodological framework by integrating ecological integrity and the sustainable supply of ESs to establish an ecosystem health assessment framework. Methods: An improved assessment framework, including four indicators, vigor, organization, resilience, and ecosystem services supply rate, was established from the perspective of human–environment systems. Then, the performance of the improved assessment framework was demonstrated in a case study in China from 2000 to 2020. Results: From 2000 to 2020, the overall spatial pattern of ecosystem health values in China was high in the southern and southeastern coastal regions, and low health values were mostly located in the western region, parts of Inner Mongolia, and metropolitan areas, with a descending trend from southeast to northwest. The imbalance between the potential and actual supply of ESs greatly contributed to the deterioration of regional ecosystem health. During the study period, the regional ecosystem in China was found to be in a more unhealthy state than in traditional Vigor-Organization-Resilience-Ecosystem services (VORES) evaluation. Conclusions: The improved assessment framework that incorporates the ecological integrity and sustainable supply of ESs provides a new perspective for understanding the complex inherent characteristics of ecosystems and the regional human-nature connectedness in coupled human–environment systems. Our results could serve as a scientific reference for practical landscape governance in a changing world to achieve landscape sustainability.

Spatial equality of parks is a significant issue in environmental justice studies. In cities with high-density development and limited land resources, this study uses a supply-demand adjusted two-step floating catchment area model (2SFCA), paying attention to residents' subjective preferences and psychological accessibility. It assesses equality of access to urban parks from two dimensions: spatial equality and quantitative equality at a fine scale of 100 × 100 m grid resolution. The spatial equality of urban parks in Chengdu is measured under different transportation modes (walking, cycling, and driving) based on multi-source geospatial big data and machine learning approaches. The results show: (1) There were significant differences in the spatial distribution of park accessibility under different modes of transportation. The spatial distribution under walking was significantly influenced by the park itself, while the distribution of rivers significantly influenced the spatial distribution under cycling and driving; (2) Accessibility to urban parks was almost universally equal in terms of driving, relatively equal in terms of cycling, and seriously unequal in terms of walking; (3) Spatial local autocorrelation analysis shows that park accessibility tended to be significantly clustered, with little spatial variation; and (4) The supply and demand of urban parks were relatively equal. The results can help urban planners to formulate effective strategies to alleviate spatial inequality more reasonably and precisely. The applied research methods can further improve the system of scientific evaluation from a new perspective.

Investigating the impact of street visual environments on young adults’ emotions is crucial for the promotion of walkable and healthy streets. However, the applicability and accuracy of existing studies are limited by a lack of large-scale sample validation. Moreover, many studies have determined emotions through subjective evaluation methods or relied solely on a single physiological indicator to assess levels of emotional arousal, neglecting the significance of emotional valence. In response, this study aims to enhance our understanding of the emotional impact of street visual environments by employing a method that integrates physiological feedback technology and deep learning. We collected videos of 100 streets from five districts in Chengdu to serve as experimental stimuli, and utilizing physiological feedback technology, we gathered data on electrocardiograms (ECG), electrodermal activity (EDA), and respiratory responses (RESP) from 50 participants as they observed these street environments. Subsequently, we applied deep learning techniques to process the video and physiological data, ultimately obtaining 500 data entries on street visual environment elements and 25,000 data entries on emotional arousal and valence. Additionally, we established multiple linear regression and multinomial logistic regression models to explore the relationship between visual street environments and emotions. The results reveal that elements such as green view factor (GVF), sky view factor (Sky VF), and sidewalk view factor (SVF) not only reduce emotional arousal levels but also facilitate the shift from negative to positive emotions, positively affecting emotional regulation. In contrast, visual enclosure (VE), vehicle view factor (VVF), and person view factor (PVF) are associated with negative emotional arousal, adversely affecting emotional valence. Moreover, the impact of specific visual environmental elements on different emotional states may vary. This study introduces a novel, multidisciplinary approach to accurately quantify the relationship between the environment and emotions, providing significant theoretical and practical insights for the development of healthier cities.

Urbanization poses a threat to ecosystems and contributes to the degradation of the environment. It is of great importance to identify coordinated economic, societal, and environmental relationships with key ecological functions and services to achieve regional sustainability. Based on a case study in China, this study seeks to fill this gap by estimating the spatial distribution of ecosystem service multifunctionality (ESM) and its spatially heterogeneous response to urbanization. First, the biophysical values of five typical ecosystem services (ESs) (carbon storage, habitat quality, net primary production, soil conservation, and water yield) were assessed based on several simulation models. The biophysical values of these ESs were then standardized and summed to obtain the spatial distribution of ESM. Afterward, the urbanization level was evaluated, and finally, the spatial interaction between urbanization and ESM was exhibited based on the bivariate Moran’s I and Getis-Ord Gi* statistic. The results showed that: (1) the ESM showed obvious spatial heterogeneity in southeastern and northwestern China, with a gradual decline from the coast to the interior; (2) ESM and urbanization had different spatial distribution patterns and produced significant local aggregation effects; and (3) harmonious relationships between ESM and urbanization were observed in southeastern coastal China and the surrounding areas of the North China Plain, which were related to the capacity of local coastal ecosystems, mangrove forests, and aquatic ecosystems to provide multiple services and goods simultaneously. Our results suggest that multifunctional ecosystems can realize a ‘win–win’ situation for ecological conservation and socioeconomic development. The results of this study can advance our understanding of the ecological effects of urbanization on ecosystems and provide valuable implications for the coordinated development of humans and nature in the rapid urbanization process.