Pressure-State-Response Research Articles

Exploring the spatiotemporal trends and influencing factors of human settlement suitability in Hunan province traditional villages

The conservation and sustainable development of traditional villages have raised global attention in the context of rapid urbanization and modernization. Taking 703 traditional villages in Hunan Province as an example, this study first constructed a Traditional Village Human Settlement Suitability (TVHSS) evaluation system based on the Pressure-State-Response (PSR) model. Then, the entropy weighting method was used to assess the spatiotemporal evolution of TVHSS from 2005 to 2020, while the Geographically Weighted Regression (GWR) model was employed to analyze the influencing factors. The results indicate that the overall TVHSS score increased from 0.521 to 0.776 from 2005 to 2020, with a spatial distribution characterized by lower suitability in the northwest and higher suitability in the southeast. During this period, the pressure subsystem experienced an increase, peaking at 0.058 in 2015 before declining to 0.055 in 2020. Meanwhile, the state subsystem remained relatively stable, with scores slightly decreasing from 0.040 in 2005 to 0.033 in 2020. In contrast, the response subsystem showed a continuous upward trend, rising from 0.430 in 2005 to 0.688 in 2020. The distance to educational institutions, degree of relief, distance to water, and distance on intangible cultural heritage sites have the highest effects on TVHSS. These findings provide a scientific basis for the conservation and sustainable development of traditional villages and offer a replicable analytical framework for similar contexts globally. By addressing the complex interactions between environmental, social, and economic factors, this study contributes to the global discourse on rural sustainability, offering insights that can inform policy-making and guide the preservation of cultural heritage in the face of modernization pressures.

Assessment and forecasting of water ecological security and obstacle factor diagnosis in the Hexi Corridor of Northwest China

The water ecological security pattern is a core factor. A scientific, accurate, and practical evaluation of water ecological security provides a theoretical basis for regional water ecological management. Using water resource data from five cities in the Hexi Corridor of Gansu Province (Jiuquan (JQ), Jiayuguan (JYG), Zhangye (ZY), Jinchang (JC), and Wuwei (WW)) from 2006 to 2021, a water ecological security evaluation index system based on the PSR (pressure-state-response) framework was constructed, covering 27 factors related to water resources, socio-economics, and the ecological environment. The main obstacle factors of water ecological security were identified using the obstacle degree model, and the grey GM(1,1) model was employed to predict water ecological security. Results indicated that the comprehensive assessment index of water ecology in the Hexi Corridor increased from 2006 to 2021, showing a transition from relatively unsafe (0.319) to basic safety and then to relatively safe (0.672). The pressure and response systems were the main limiting factors affecting water ecological security in the Hexi Corridor. After a slight decline in 2008, the overall spatial distribution continued to rise, with WW City and ZY City leading since 2016. ZY had a higher safety grade proportion (25%) compared to other areas in the Hexi region. The pressure system was the most significant obstacle to water ecological security after 2006. Prediction results indicated that the comprehensive evaluation index of water ecological security would continue to rise annually from 2022 to 2031, reaching a very safe level by 2025. The evaluation results provide a scientific basis for ecological security and risk decision-making in the study area.

Comprehensive evaluation of rural entrepreneurial environment based on Pressure-State-Response model -evidence from China

Background and aimsThe study of rural entrepreneurial environment is one of the key issues in rural entrepreneurship research.The rural entrepreneurship environment plays a key role in increasing the success rate of farmers' entrepreneurship and promoting their employment. Scientific evaluation of the rural entrepreneurial environment is important for governments to formulate relevant policies and optimize the rural entrepreneurial environment. Methods and resultsThis paper constructs a rural entrepreneurship environment evaluation index system based on PSR (Pressure-State-Response) model.The entropy Weight-TOPSIS method was used to measure the rural entrepreneurship environment in 30 provinces in China, the Gini coefficient was used to explore the regional differences, and the barrier degree model was used to diagnose the barrier factors. The results of the study show that: China's rural entrepreneurship environment has a ladder, the rural entrepreneurship environment is divided into four tiers, Guizhou is in the leading tiers, Shandong and other 13 provinces are in the challenging tiers, Inner Mongolia and other 11 provinces are in the catching-up tiers, and Hainan and other 5 provinces are in the improving tiers. Provincial differences are large, and the regional rural entrepreneurship environment is obviously unbalanced. ConclusionThis paper applies the PSR ("Pressure State Response") model to rural entrepreneurship environment evaluation, analyzes the relationship between the indicators according to the relationship structure of the sub-models in the model, and provides a theoretical basis for the rural entrepreneurship environment evaluation system and scientific evaluation. The rural entrepreneurship evaluation index system is regarded as an ecosystem, and the nonlinear effect between the elements is considered.

Towards Environmental Sustainability: Integrating RS and GIS for Ecology Assessment

The environment provides numerous benefits for human well-being, such as ecosystem services. These services directly and indirectly depend on the physical state of the ecosystem. However, the over-exploitation of natural resources along with socio-economic factors, i.e. economic growth, poverty, agriculture expansion, population growth and weak environmental governance and regulation for fulfilling the human needs for food, fuel, and shelter, is leading to the degradation of the ecological health of an area. Therefore, monitoring and assessment of spatial and temporal changes in the ecology of a region in terms of vital ecological services is very critical and would help the decision-makers to develop and plan appropriate adaptation and mitigation measures for the conservation of natural ecosystems at various scales to ensure environmental sustainability. The present study aimed to assess the ecological status of the Mahi Bajaj Sagar catchment area in Rajasthan (India) from the year 2000 to 2020, using remote sensing-based indices. Indicators such as greenness, dryness, and heat index have been selected as per the pressure-state-response (PSR) framework. Multi-spectral remote sensing data and image processing methods have been used to estimate these indicators, and a remote sensing-based Ecological Status Index (RSBI) has been generated by their integration using the principal component analysis (PCA) to assess the ecological status of the Mahi Bajaj Sagar catchment. Findings from the study indicate a consistent decline in the overall ecological status of the Mahi Bajaj catchment, where decreased forest areas have a pronounced effect on ecological health. Interestingly, approximately 43.6% of the area displayed resilience to changes in ecological status; however, 36.4% of the area exhibited signs of ecological degradation. Our study underscores the efficacy of a remote sensing-based approach in quantifying and detecting ecological changes, offering a promising methodology for monitoring and assessing the ecological health of large areas that can help promote environmental sustainability. Keywords: Environmental Sustainability, Ecological Status, RSBI, Remote Sensing, PSR Framework

Assessment of mangrove health based on pressure–state–response framework in Guangxi Beibu Gulf, China

Mangroves, primarily found along tropical and subtropical coastlines, are crucial ecosystems that offer significant ecological services, including coastal protection, carbon sequestration, and biodiversity support. However, these ecosystems are under severe threat from human activities such as aquaculture, agriculture, and urban development, leading to deforestation and degradation. This study aims to develop a comprehensive framework for assessing the health of mangrove ecosystems using the Pressure-State-Response (PSR) model with annual temporal resolution from 2019 to 2023. It consists of three dimensions: Pressure (human activities and natural factors affecting the ecosystem), State (current condition of the ecosystem), and Response (efforts to mitigate adverse effects and restore health). This study incorporates innovative physical and structural parameters alongside traditional indicators to improve the accuracy of the assessment. The method offers advantages such as ease of measurement, low cost, early warning capabilities for ecosystem damage, and high sensitivity to ecological changes. It provides valuable insights for decision-makers and enhances the ability to detect trends in mangrove health over time through a large-scale, multi-temporal analysis. Using remote sensing techniques and the Analytic Hierarchy Process (AHP), we identified 12 key indicators. The AHP method was used to determine the weight of each indicator, achieving a consistency ratio (CR) of less than 0.1, which ensures the reliability of the assessment. The evaluation included calculating and analysing the Comprehensive Health Index (CHI), Pressure (PHI), State (SHI), and Response (RHI) health indices. Results indicated that the mangrove ecosystems in the Beibu Gulf region were “healthy” state by 2019 through 2022. However, in 2023, the health status declined to “relatively healthy,” indicating a downward trend. In conclusion, this study presents a robust framework for assessing mangrove ecosystem health using the PSR model. The findings underscore the urgent need for conservation efforts to reverse the declining health trend and ensure the long-term sustainability of mangrove ecosystems in the Beibu Gulf.

Remote Sensing Evaluation and Monitoring of Spatial and Temporal Changes in Ecological Environmental Quality in Coal Mining-Intensive Cities

In coal-dependent urban economies, the dichotomy between resource exploitation and ecological conservation presents a pronounced challenge. Traditional remote sensing ecological assessments often overlook the interplay between mining activities and urban environmental dynamics. To address this gap, researchers developed an innovative Resource-Based City Ecological Index (RCEI), anchored in a Pressure–State–Response (PSR) framework and synthesized from six discrete ecological indicators. Utilizing geodetic remote sensing data, the RCEI facilitated a comprehensive spatiotemporal analysis of Jincheng City’s ecological quality from 1990 to 2022. The findings corroborated the RCEI’s efficacy in providing a nuanced portrayal of the ecological state within mining regions. (1) Jincheng City’s ecological quality predominantly sustained a mudhopper-tier status, exhibiting an overarching trend of amelioration throughout the study period. (2) Disparities in ecological landscape quality were pronounced at the county level, with Moran’s Index exceeding 0.9, signifying a clustered ecological quality pattern. High–high (H–H) zones were prevalent in areas of elevated altitude and dense vegetation, whereas low–low (L–L) zones were prevalent in urban and mining sectors. (3) Further, a buffer zone analysis of two coal mines, differing in their mining chronology, geographical positioning, and operational status, elucidated the ecological impact exerted over a 32-year trajectory. These insights furnish a robust scientific and technical foundation for resource-centric cities to fortify ecological safeguarding and to advance sustainable development stratagems.

Water resource safety assessment of the Hexi inland river of China based on the PSR model

ABSTRACT The Hexi Corridor is located in northwest China, and its water resources mainly rely on meltwater from the Qilian Mountains and limited precipitation. The Hexi Corridor is an important regional population center and grain production area. However, limited rainfall restricts regional development due to inadequate water resources. Assessing water resource security in the Hexi region and providing targeted recommendations are crucial for rational planning and utilization of water resources, protecting the ecological environment, and promoting development. This study employs the entropy weight method to construct a pressure-state-response (PSR) system, assessing the water resource security of various river basins in the Hexi inland area. The evaluation results indicate that since the 21st century, the comprehensive water resource security scores of the three river basins have shown an upward trend. Specifically, the economic and social systems of the Shule River Basin and Heihe River Basin are improving, while their natural systems are declining; all three systems in the Shiyang River Basin are improving. Based on these results, targeted recommendations for different areas are proposed, providing a basis for enhancing water resource security in the region.

Integrated Benefits of Sustainable Utilization of Construction and Demolition Waste in a Pressure-State-Response Framework

This study presents the first application of the pressure-state-response (PSR) model in the comprehensive assessment of construction and demolition waste (CDW) recycling benefits. Unlike traditional methods, the PSR model provides a multi-dimensional analysis that integrates economic, environmental, and social factors, offering a more holistic approach to evaluating the impact of CDW recycling strategies. This model enables stakeholders to better understand the pressures, states, and responses involved in CDW management, providing actionable insights to optimize recycling efforts and support sustainable urban development. Using the pressure-state-response (PSR) logical framework of sustainable economics, this paper systematically analyzed the comprehensive benefit mechanism of the recycling of construction and demolition waste (CDW), and designed a comprehensive benefit evaluation model for CDW recycling. At the same time, taking Chongqing as an example, the management status of construction and demolition waste, the supply and demand matching of sustainable recycling products, and the impact of the input and output of CDW management were analyzed. The results were as follows: (1) The recovery rate of urban manure fluctuated between 0.13 and 0.17, mainly in temporary landfill. (2) Based on the latest market demand data of CDW recycled products, the supply–demand ratio of recycled products fluctuated between 0.11 and 0.21. This change in the supply–demand ratio reflects improvements in recycling technologies, such as the introduction of C2CA technology, which has greatly increased the supply of high-quality recycled materials. In addition, government policies encouraging the use of recycled products in public projects have contributed to this shift, further aligning supply with market demand. (3) The benefit–cost ratio of CDW management reflects new recycling technologies and the improved efficiency of CDW management. The benefit–cost ratio, which currently fluctuates between 0.32 and 0.39, more accurately reflects the current state of CDW management, which is increasingly adopting advanced technologies, resulting in increased efficiency and reduced costs. Based on this, this paper discusses the supply–demand relationship and benefit–cost ratio in CDW management from supply-side and demand-side perspectives, and puts forward corresponding countermeasures and suggestions. The research results provide a clear reference for improving the efficiency of building demolition waste resource utilization, especially in optimizing the balance of market supply and demand, and improving the economic benefits of recycled products. By analyzing the balance between the supply and demand ratio and the benefit–cost ratio, this study helps inform policy makers, businesses, and investors, to promote the sustainable development of CDW recycling projects to maximize resource efficiency, while reducing environmental pressures. These results not only provide practical guidelines for the implementation of CDW recycling projects, but also lay a foundation for future policy formulation and the setting of industry standards.

Developing a global sustainable electricity use index using the pressure-state-response framework

This study analyse and compare the sustainable electricity usage in 60 countries listed on the official websites of World Energy Consumption Statistics and Climate Bond Initiative. The study also analyses the impact of increased usage of sustainable electricity on the economies' dependence on non-renewable energy sources in the evaluation system. We used a standard index system based on the Pressure-State Response (PSR) model to measure global sustainable electricity usage. Model results convey that Norway is the best performer in sustainable electricity usage, while several European countries display commendable scores, confirming their commitment to sustainable electricity practices. On the other hand, despite being the leading economies in terms of GDP, major economies such as the United States, China, Japan, and India have underperformed compared to others in the evaluation system. The study employs regression techniques to explain the relationship between sustainable electricity usage and non-renewable energy dependence. Results confirm a negative relationship between the variables, indicating the role of sustainable energy practices in reducing fossil fuel consumption. It emphasizes the urgency of a balanced approach to economic growth and natural resource usage to support a green future.

Modeling and application of urban waterlogging resilience assessment based on PSR–NES framework and analysis of driving mechanisms

ABSTRACT Extreme weather events are escalating globally, intensifying urban waterlogging disasters and endangering inhabitants and assets while hindering socio-economic progress. This study explores factors hindering cities' waterlogging disaster mitigation using urban resilience theory. It introduces a pressure–state–response (PSR)–natural–economic–social (NES) assessment model to evaluate urban waterlogging resilience, focusing on Nanjing as a key city in flood control. Flood scenarios are simulated using the MIKE model for different rainstorm recurrence periods. Urban flooding resilience is assessed with a hybrid approach. Geodetector analysis identifies primary resilience drivers. Results validate the PSR–NES composite resilience index, showing complex resilience patterns across the study area. High-resilience areas are mainly in the east and southeast, while low-resilience areas cluster along roads and low-lying communities. Key resilience indicators include waterlogging duration, inundation depth, warning capacity, economic density, and road accessibility. These factors interact with nonlinear enhancements and synergies. The study's insights can identify urban management or flood defense infrastructure deficiencies, guiding tailored flood defense strategies for stakeholders.

Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis

The spatial mapping and prediction of groundwater quality (GWQ) is important for sustainable groundwater management, but several research gaps remain unexplored, including the inaccuracy of spatial interpolation, limited consideration of the geological environment and human activity effects, limitation to specific pollutants, and unsystematic indicator selection. This study utilized the entropy-weighted water quality index (EWQI), the LightGBM model, the pressure-state-response (PSR) framework and SHapley Additive exPlanations (SHAP) analysis to address the above research gaps. The normalized importance (NI) shows that NO3− (0.208), Mg2+ (0.143), SO42− (0.110), Cr6+ (0.109) and Na+ (0.095) should be prioritized as parameters for remediation, and the skewness EWQI distribution indicates that although most sampled locations have acceptable GWQ, a few areas suffer from severely poor GWQ. The PSR framework identifies 13 indicators from geological environments and human activities for the SMP of GWQ. Despite high AUROCs (0.9074, 0.8981, 0.8885, 0.9043) across four random training and testing sets, it was surprising that significant spatial uncertainty was observed, with Pearson correlation coefficients (PCCs) from 0.5365 to 0.8066. We addressed this issue by using the spatial-grid average probabilities of four maps. Additionally, population and nighttime light are key indicators, while net recharge, land use and cover (LULC), and the degree of urbanization have the lowest importance. SHAP analysis highlights both positive and negative impacts of human activities on GWQ, identifying point-source pollution as the main cause of the poor GWQ in the study area. Due to the limited research on this field, future studies should focus on six key aspects: multi-method GWQ assessment, quantitative relationships between indicators and GWQ, comparisons of various spatial mapping and prediction models, the application of the PSR framework for indicator selection, the development of methods to reduce spatial uncertainty, and the use of explainable machine learning techniques in groundwater management.

Assessment of wetland ecosystem health in Rarh Region, India through P-S-R (pressure-state-response) model

The current study attempted to assess wetland ecosystem health (EH) in the Murshidabad district's Rarh tract using the P-S-R (Pressure-State-Response) model and machine learning (ML) algorithms and validated it with a field-based validation approach as well as conventional validation approaches. To assess the ecosystem's health, 27 metrics were used to monitor the wetlands' pressure, state, and response. All of the models found that 46.1 % of wetlands in strong EH zones have transformed to 11.41 % in relatively fragile EH zones during the previous thirty years, demonstrating a progressive loss of EH quality throughout larger wetland areas. All of the applied models were deemed to be acceptable based on the results of the model validation process, however, the Random Forest (RF) model performed exceptionally well. The deterioration of EH in the wetlands happened due to the rapid expansion of settlement areas and agricultural land. So, the findings of the study deepen our knowledge about EH in the Rarh tract's wetlands, assisting decision-makers in creating sustainable wetland management strategies.

Modelling the present and future scenario of urban green space vulnerability using PSR based AHP and MLP models in a Metropolitan city Kolkata Municipal Corporation

ABSTRACT Urban green spaces, despite their recognized importance for sustainable urban development, face significant challenges to their resilience and viability due to rapid urbanization and various associated pressures. The scientific problem addressed in this paper is the vulnerability of urban green spaces to various stressors, including proximity to settlement, land use and land cover changes, and proximity to roads, among others. Despite their importance, there is a lack of comprehensive assessments and frameworks to systematically evaluate and address this vulnerability. Therefore, this study aims to fill this gap by employing a multi-criteria decision-making framework, namely the Analytic Hierarchy Process (AHP), and the Pressure-State-Response (PSR) framework. By analyzing 10 indicators related to urban green space vulnerability through a pairwise comparison matrix, the study identifies critical factors influencing vulnerability and categorizes urban green spaces into different susceptibility levels. Additionally, the research extends its analysis to future scenario development for the years 2030 and 2040, using a Multi-Layer Perceptron (MLP) based Markov Chain model, incorporating various parameters such as distances from built-up areas, roads, rails, streams, slopes, and elevation. Through these methodologies, the study aims to provide valuable insights to urban planners, policymakers, and environmental practitioners, enabling them to make informed decisions to enhance the resilience and sustainability of urban green spaces and urban areas as a whole.

Risk evaluation, spatiotemporal evolution, and driving factors of provincial food safety in China

The cross-regional transfer of food safety risks has become more prominent, bringing new challenges to the food ecosystem and food safety regulation. This study develops an evaluation index system of food safety risks based on the pressure-state-response (PSR) framework. The food safety risk indices of 30 provinces in China from 2011 to 2020 are calculated by determining the index weights using the real-coded accelerated genetic algorithm–projection pursuit model (RAGA-PP). Furthermore, this study elaborates the spatiotemporal differences and correlations of provincial food safety risks, characterizes the spatial aggregation and spatiotemporal changes of risks, and investigates driving factors affecting the spatiotemporal evolution of risks. The following findings are established. First, the overall risk value of food safety in China in 2020 decreased by approximately 5% compared with year 2010. In 2020, the national food safety environment was relatively favorable and tended toward stability. The overall trend of food safety risks in China is decreasing, although socioeconomic development has increased the risks, and the corresponding social management measures have also reduced the risks. Second, food safety risks were unevenly distributed among provinces, showing significant regional differences. Specifically, generally higher risks were observed in eastern provinces versus other regions and in coastal provinces versus inland provinces. Concentrated and superimposed risks were observed in the Yangtze River Delta, a large urban agglomeration centered on Shanghai. Lastly, population density and urbanization level were the main drivers of the evolution of regional food safety risks; whereas policy instruments used by the government to manage risks played a limited role. The results show that establishing a cross-regional collaborative governance mechanism to manage food safety risks should constitute an important component of the regional integration strategy of China.

Assessment of Effectiveness and Suitability of Soil and Water Conservation Measures on Hillslopes of the Black Soil Region in Northeast China

There are four sizable black soil regions throughout the world, all of which are valuable natural resources. The black soil region in Northeast China is a major foundation for grain production. Serious risks of soil erosion do exist, and they have an immediate impact on both the country’s food security and future ecological security. Many soil and water conservation measures have been put in place to control soil erosion. However, how effective and suitable are these measures? Currently, systematic analyses and assessments are lacking. The objective of this study was to assess the effectiveness and suitability of soil and water conservation measures on hillslopes using the comprehensive index method and the Pressure–State–Response model. The categorization of effectiveness and suitability of these measures were similar for both methods: that is, very effective and suitable measures included no-tillage + straw mulch and ridge belt or contour ridge. The two methods validated one another. Thus, this categorization standard is useful for choosing the best soil and water conservation measures for different soil erosion regions.

Warming planet and expanding wallets: Climate risk and managerial moral hazard

As global climate change intensifies, its potential risks have captured international scrutiny. This paper systematically analyzes the relationship and influence mechanism between climate risk and managerial self-interested behavior by constructing the PSR (Pressure-State-Response) model and the theoretical framework of internal and external perspectives of agency theory. The results of empirical tests using a sample of Chinese listed companies from 2010 to 2020 reveal that there is a U-shaped relationship between climate risk and managerial self-interest, implying that this will intensify managerial self-interested behavior as climate risk continues to increase to a certain stage. We also identify management discretion and donation income as internal and external influencing mechanisms. In addition, this U-shaped relationship is particularly significant in non-state-owned firms as well as in the non-energy sector. Overall, our study provides new theoretical and empirical insights into the relationship between climate risk and internal managerial behaviors of firms, and it also has important implications for both firm practice and policy making.

Ecological security assessment of Yunnan Province, China in the context of Production-Living-Ecological space division.

With the rapid development of population, society and economy, human activities have caused serious adverse impacts on the environment, ecosystems and landscape patterns over the long term. In order to address the series of impacts of human activities on the environment, territorial space and resource use, the study of Production-Living-Ecological Space (PLES) and ecological security have all become academic frontiers in the field of sustainable development. In this study, we applied multi-source data and GIS technology to construct an ecological security evaluation model based on the results of PLES delineation and the Pressure-State-Response (PSR)framework, and carried out the three-period PLES ecological security evaluation for 2000, 2010 and 2020 at the county and grid scales in Yunnan Province. The PLES pattern in Yunnan Province is dominated by ecological space, which accounts for 75%, followed by 23% of production space, with ecological space shrinking from 2000 to 2020. Ecological security in ecological space and living space shows an improving trend from 2000 to 2020. The ecological security of production space improved in 2010 compared to 2000 but then showed a decreasing trend in 2020. Ecological security in ecological space shows that north-western and southern Yunnan is safer than central Yunnan, while ecological security in living space is safer in central Yunnan, and ecological security in production space is better in southern Yunnan than in northern Yunnan. Comparison with related research results shows that the ecological security evaluation results of PLES in Yunnan Province in this study are scientific and reasonable. The ecological security evaluation model of PLES constructed in this study solves the problem of complex and incomplete ecological security evaluation indexes in the past, and the results of the study are more refined and precise, which provides new ideas for the study of regional ecological security.

Analyzing resilience influencing factors in the prefabricated building supply chain based on SEM-SD methodology

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

Ecological Evaluation of Land Resources in the Yangtze River Delta Region by Remote Sensing Observation

The evaluation of land ecological security (LES) evaluates how human activity and land use affect land ecosystems. Its ultimate objective is to provide guidance and assistance for decision making in order to preserve and restore the efficacy and health of terrestrial ecosystems. The assessment model presented in this article is comprehensive and integrates the advantages of both subjective and objective weighting techniques. This study extends the “Pressure–State–Response” (PSR) model to “Driver–Pressure–State-Impact–Response” (DPSIR) and combines it with TOPSISI to determine the weights of each contributing component. Furthermore, the geographical and temporal distribution patterns of regional land ecological security levels were investigated using GIS geostatistical approaches. According to this study, (1) the Yangtze River Delta region’s LES index, with a mean value in the fairly safe range, is generally safe. The year 2019 marks an inflection point for the index, with the highest level of ecological safety on land. The primary element is the modification of environmental policies that are enacted by the government. (2) The LES status is divided into two stages during the course of this study. The Yangtze River Delta region’s LES quickly develops throughout the first stage (2012–2019), which sees a shift in the safety rating from IV to II. The second stage (2019–2023) sees a progressive improvement in the LES index and a shift in the safety category from Class II to Class I. (3) Important variables influencing the geographical distribution of LES in the Yangtze River Delta region include barrier elements, including soil and water erosion areas, flood disaster areas, grain planting areas, urban green covering areas, and effective irrigation areas of farmland.

Spatiotemporal Changes and Simulation Prediction of Ecological Security Pattern on the Qinghai–Tibet Plateau Based on Deep Learning

Over the past two decades, due to the combined effects of natural and human factors, the ecological environment and resources of the Qinghai–Tibet Plateau (QTP) have faced serious threats, profoundly impacting its ecosystem and the lives of its residents. Therefore, the establishment of the ecological security pattern (ESP) is crucial to cope with climate change, maintain ecosystem function, and sustainable development. Based on the Pressure–State–Response (PSR) model, this study constructed an evaluation index system for the ecological security (ES) of the QTP, evaluated the ES of the QTP during 2000–2020, and predicted the ES of the QTP during 2025–2035 based on the deep learning model. Combined with the residents’ perception of ES, the ES of the QTP was evaluated comprehensively. The results showed that: (1) From 2000 to 2020, the ES value of the QTP continued to rise, the number of dangerous and sensitive counties decreased, and the number of other counties increased. The overall spatial distribution features higher values in the southeast and lower values in the northwest and central regions. (2) From 2000 to 2020, both hot spots and cold spots on the QTP decreased, with the hot spots mainly concentrated in the southeast of the QTP, represented by Yunnan Province, and the cold spots shifting from west to east, mainly concentrated in the central QTP, represented by Qinghai Province. (3) The Long Short-Term Memory (LSTM) model demonstrates high prediction accuracy. Based on the prediction of LSTM, the ES value of the QTP will continue to rise from 2025 to 2035, and the number of safe counties will reach the highest level in history. The spatial distribution is still higher in the southeast and lower in the northwest and central regions. (4) By analyzing residents’ perception of 25 potential factors that may affect the ES of the QTP, the results show that residents generally believe that these factors have an important impact on ES, and their evaluation is between “important” and “very important”. In addition, there is a significant correlation between these factors and the predicted values of ES. The results of the study will help to improve our understanding of the overall ecological environment of the QTP, provide accurate positioning and reasonable help for the government to formulate relevant protection strategies, and lay a methodological and practical foundation for the sustainable development of the QTP.