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To address the problem of ignoring unpaved roads when planning off-road emergency rescue paths, an improved A* algorithm that incorporates road factors is developed to create an off-road emergency rescue path planning model in this study. To reduce the number of search nodes and improve the efficiency of path searches, the current node is classified according to the angle between the line connecting the node and the target point and the due east direction. Additionally, the search direction is determined in real time through an optimization method to improve the path search efficiency. To identify the path with the shortest travel time suitable for emergency rescue in wilderness scenarios, a heuristic function based on the fusion of road factors and a path planning model for off-road emergency rescue is developed, and the characteristics of existing roads are weighted in the process of path searching to bias the selection process toward unpaved roads with high accessibility. The experiments show that the improved A* algorithm significantly reduces the travel time of off-road vehicles and that path selection is enhanced compared to that with the traditional A* algorithm; moreover, the improved A* algorithm reduces the number of nodes by 16.784% and improves the search efficiency by 27.18% compared with the traditional 16-direction search method. The simulation results indicate that the improved algorithm reduces the travel time of off-road vehicles by 21.298% and improves the search efficiency by 93.901% compared to the traditional A* algorithm, thus greatly enhancing off-road path planning. [ABSTRACT FROM AUTHOR]

The ecological and environmental problems of arid zones have become an urgent global concern. Current research on ecological risk is based mainly on the dominant functions of land use, with a primary focus on land use landscape projections and less consideration of potential risks to ecosystems, system resilience and interactions between nature and future sustainable development. In this study, a potential–connectivity–resilience ecological risk assessment model based on the SDGs was constructed using multisource data to spatially quantify indicators at the grid scale in the Turpan and Hami regions of Xinjiang, China. This model was used as a basis for studying ecological risk in arid zones from a production–living–ecological space (PLES) perspective. The results revealed that, during the period 2000–2020, PLESs in the Turpan and Hami regions presented significant spatial similarity, with an increasing trend in overall risk. The production space in the Turpan and Hami regions showed a parabolic trend of increasing and then decreasing, whereas the living space and ecological space in the Hami region showed continuous linear upward trends. The state of ecological security in the Turpan and Hami regions is gradually deteriorating, and comprehensive ecological protection and restoration measures are urgently needed to rationally allocate the structure and layout of the production-–living-–ecological space. The study of ecological risk from a PLES perspective not only helps in fully understanding the development trend of the arid zone; it also provides new ideas and methods for evaluating regional ecological environmental safety and scientific references for formulating regional sustainable development, ecological risk prevention and control and the rational allocation of resources. [ABSTRACT FROM AUTHOR]

Ecologically fragile areas are confronted with the contradiction between economic development and ecological protection, especially in the Tuha region (Turpan and Hami), where the extremely vulnerable ecological environment limits local sustainable development. To address this, this study utilizes POI (Point of Interest) data, land use, and socioeconomic statistical data to achieve spatial quantification of indicators on a kilometer grid scale, constructing a multi-factor, multi-dimensional evaluation system for the socioeconomic and ecological effects of sustainable development based on SDGs (Sustainable Development Goals). The entropy method, comprehensive evaluation method, coupling coordination degree model, and geographical detector method are used to analyze the coupling relationships between systems at different scales and the factors influencing the system's coupling coordination degree. The results indicate that from 2010 to 2020, the economic, social, and ecological systems of the Tuha region, as well as their comprehensive scores, exhibited spatial similarity. The economic system showed an upward trend, the social system displayed an inverted U-shaped trend of rising then declining, while the ecological system presented a U-shaped trend of declining then increasing. At the county scale, the coupling coordination degree closely approximates the trend of the comprehensive coordination index, showing a continuous upward trajectory. Compared with Turpan city, Hami city, especially Yizhou district, exhibits the best development in coupling coordination degree, while the growth in coupling coordination degree is most significant in Gaochang district. The main factors influencing the degree of coupling coordination are grain production and GDP (gross domestic product). This study provides a new perspective on the quantification of sustainable development indicators, which is of great significance for balancing economic and social development with ecological protection and promoting the coupled and coordinated development of society, economy, and ecology in ecologically fragile areas. [ABSTRACT FROM AUTHOR]

In recent years, rapid urban expansion and increasing ecological sensitivity in arid zones have led to extreme imbalances in ecosystem development. Therefore, there is an urgent need to balance the dual goals of synergistic development of ecosystem services (ESs) and increased urbanization. Previous studies have analyzed the impacts of urbanization on ESs but have selected a limited number of indicators and have not focused on the impacts of urbanization on ES pair interactions. In this study, six key ESs (water yield, habitat quality, soil conservation, carbon storage, carbon sequestration and oxygen production, and food production) and total ecosystem services (TESs) were selected, and trends in the temporal and spatial relationship between trade-offs and synergies were analyzed over 20 years. This study refined the living standards urbanization indicator and evaluated the impact of urbanization and multiple drivers on ESs and ES pair interrelationships based on geo-detectors and segmented linear regression. The results show that there is heterogeneity in the overall and regional ES trade-offs and synergistic relationships, and water yield (WY)-related ES pairs generally exhibit synergistic relationships at the overall level. Spatially, however, the trade-off ratio exceeds the synergy ratio. Segmented linear regression results show that the relationship between all the urbanization indicators and TESs demonstrates an upward trend followed by a downward trend. Measures such as the increase in man-made oases in the early stages of urbanization did have some positive effects on TESs. However, as urbanization increased, these positive effects were quickly offset by the negative effects of overdevelopment and environmental degradation, leading to an overall decline in TESs. Urbanization of construction land (CL) had the most direct impact on ecosystem services. In summary, due to special climatic constraints, arid zones are more sensitive than other ecosystems, and urban development is strictly limited by oasis capacity. As cities expand, attention needs to be focused on protecting ecological land and limiting the expansion of CL to promote the synergistic development of urbanization and ecosystem services in arid zones. [ABSTRACT FROM AUTHOR]