Search Results (418)

Land use patterns are a critical driver of changes in carbon emissions, making it essential to elucidate the relationship between regional carbon emissions and land use types. As a nationally designated economic strategic zone, the Yangtze River Basin encompasses megacities, rapidly developing medium-sized cities, and relatively underdeveloped regions. However, the mechanism underlying the interaction between landscape patterns and carbon emissions across such gradients remains inadequately understood. This study utilizes nighttime light, land use and carbon emissions datasets, employing XGBoost, CatBoost, LightGBM and a stacking ensemble model to analyze the impacts and driving factors of land use changes on carbon emissions in the Yangtze River Basin from 2002 to 2022. The results showed: (1) The stacking ensemble learning model demonstrated the best predictive performance, with a coefficient of determination (R²) of 0.80, a residual prediction deviation (RPD) of 2.22, and a root mean square error (RMSE) of 4.46. Compared with the next-best models, these performance metrics represent improvements of 19.40% in R² and 28.32% in RPD, and a 22.16% reduction in RMSE. (2) Based on SHAP feature importance and Pearson correlation analysis, the primary drivers influencing CO₂ net emissions in the Yangtze River Basin are GDP per capita (GDPpc), population density (POD), Tertiary industry share (TI), land use degree comprehensive index (LUI), dynamic degree of water-body land use (K_water), Largest patch index (LPI), and number of patches (NP). These findings indicate that changes in regional landscape patterns exert a significant effect on carbon emissions in strategic economic regions, and that stacked ensemble models can effectively simulate and interpret this relationship with high predictive accuracy, thereby providing decision support for regional low-carbon development planning. Full article

Coastal areas are under intense pressure worldwide because diverse stakeholders rely on coastal resources, and the supply of land is highly limited. Coast-dependent economic activities like transportation and logistics infrastructure in the Jade Bay, Germany, have experienced extensive demand for land. The situation is more interesting because national parks encircle the seaport. Understanding the complex seaside–landside dynamics following the development of Jade Weser Port is crucial for promoting sustainability, as massive development exceeds existing spatial capacity. However, a comprehensive framework to assess land use conflicts when dealing with infrastructure development in sensitive coastal areas is often missing. We analyze the origin of land use developments and the planning process at different administrative levels by retracing land use changes from 1970 to 2015 using a time series of satellite images, analyzing planning documents, and examining realized activities. We look for an embedding of transport infrastructure development and its feedback on land use. As a consequence of land use conflicts, these land system dynamics create winners and losers across multidisciplinary aspects. Our findings reflect interdisciplinary aspects which discuss both societal changes and the constellation of inadequate planning approaches to address the complexity of coastal land use. The degree to which these activities cause land use conflicts depends on institutional settings, especially the consistency of ICZM and infrastructure planning. Full article

In karst regions (KRs), unique surface morphology and irrational human exploitation have led to increasingly prominent issues such as land fragmentation and rocky desertification. Understanding the spatiotemporal evolution of cultivated land (CL) in these areas is of great significance for supporting regional socioeconomic development, food security, and ecological sustainability. This study focuses on Guilin, combining GIS spatial analysis with methods including kernel density analysis, dynamic degree, spatial transfer matrix, and a Geodetector to examine the spatiotemporal distribution characteristics, evolution trends, and driving factors of land use based on five-phase of land use data from 2000 to 2020. The results show that: (1) over the past two decades, land use in Guilin has been dominated by CL and forest land, with CL exhibiting a spatial pattern of more in the east and south, and less in the west and north; (2) the CL transfer-out rate exceeded the transfer-in rate, mainly shifting to construction land and forest land; (3) the overall density of CL showed a declining trend, with a relatively stable spatial pattern; and (4) driving factor analysis indicates that the spatiotemporal changes in CL are jointly influenced by multiple factors, with natural factors exerting a stronger influence than socio-economic factors. Among them, the interaction between elevation and temperature had the greatest impact and served as the dominant factor. Although GDP and population were not dominant individually, their explanatory power and sensitivity increased significantly when interacting with other factors, making them key sensitive factors. The results can provide a scientific reference for the protection and rational utilization of CL resources in KR. Full article

Oases in arid regions are crucial for sustaining agricultural production and ecological stability, yet few studies have simultaneously examined the coupled dynamics of land use/cover change (LUCC), carbon emissions, and ecosystem service value (ESV) at the oasis–agricultural scale. This gap limits our understanding of how different land use trajectories shape trade-offs between carbon processes and ecosystem services in fragile arid ecosystems. This study examines the spatiotemporal interactions between land use carbon emissions and ESV from 1990 to 2020 in the Wensu Oasis, Northwest China, and predicts their future trajectories under four development scenarios. Multi-period remote sensing data, combined with the carbon emission coefficient method, modified equivalent factor method, spatial autocorrelation analysis, the coupling coordination degree model, and the PLUS model, were employed to quantify LUCC patterns, carbon emission intensity, ESV, and its coupling relationships. The results indicated that (1) cultivated land, construction land, and unused land expanded continuously (by 974.56, 66.77, and 1899.36 km²), while grassland, forests, and water bodies declined (by 1363.93, 77.92, and 1498.83 km²), with the most pronounced changes occurring between 2000 and 2010; (2) carbon emission intensity increased steadily—from 23.90 × 10⁴ t in 1990 to 169.17 × 10⁴ t in 2020—primarily driven by construction land expansion—whereas total ESV declined by 46.37%, with water and grassland losses contributing substantially; (3) carbon emission intensity and ESV exhibited a significant negative spatial correlation, and the coupling coordination degree remained low, following a “high in the north, low in the south” distribution; and (4) scenario simulations for 2030–2050 suggested that this negative correlation and low coordination will persist, with only the ecological protection scenario (EPS) showing potential to enhance both carbon sequestration and ESV. Based on spatial clustering patterns and scenario outcomes, we recommend spatially differentiated land use regulation and prioritizing EPS measures, including glacier and wetland conservation, adoption of water-saving irrigation technologies, development of agroforestry systems, and renewable energy utilization on unused land. By explicitly linking LUCC-driven carbon–ESV interactions with scenario-based prediction and evaluation, this study provides new insights into oasis sustainability, offers a scientific basis for balancing agricultural production with ecological protection in the oasis of the arid region, and informs China’s dual-carbon strategy, as well as the Sustainable Development Goals. Full article

The green landscapes of oasis cities play an important role in maintaining ecological security. However, these ecosystems face increasing threats from desertification and fragmentation, driven by intensifying climate change and rapid urbanization. Understanding the characteristics and driving mechanisms behind changes in green landscape patterns is crucial for advancing sustainable urban green space management. This study explores the spatio-temporal changes in the green landscape pattern in Urumqi during 1990–2020 using a random forest classifier. This study also applies geographical detectors and geographically weighted regression to comprehensively determine the driving mechanism and spatio-temporal nonstationarity. The results are as follows: (1) The landscape types are primarily dominated by unused land, urban green spaces, and construction land, accounting for more than 80%. The areas of urban green spaces, water bodies, cropland, and unused land decreased by 0.38%, 37.41%, 0.57%, and 4.58%, respectively, from 1990 to 2020. With rapid urbanization, construction land exhibited a significant expansion trend, and the degree of fragmentation of urban green spaces increased spatially over these 30 years. (2) From 1990 to 2020, each landscape index exhibited fluctuating characteristics. Overall, the Shannon’s diversity and evenness indices of the urban green landscapes exhibited an increasing trend. The contagion and connectivity indices exhibited a decreasing trend, decreasing from 50.894 and 99.311 in 1990 to 46.584 and 99.048 in 2020, respectively. (3) During these 30 years, the dynamics of urban greenery were affected by a combination of natural and social factors, with elevation determining the overall urban green distribution pattern. Precipitation and temperature dominate the urban green space changes in the north and south of Urumqi. Socioeconomic factors such as GDP, population, river distance, and town distance regulate the urban green space changes in the central built-up area. Full article

Land use and land cover change (LUCC) is central to regulating human–land relationships and crucial for urban planning and sustainable development in arid oasis cities. As a typical oasis city in Xinjiang, Shihezi City faces the triple challenges of agricultural protection, urban expansion, and ecological conservation. Taking Shihezi City as the research object, this study used the 30 m resolution China Land Cover Dataset and applied the land use dynamic degree, comprehensive index of land use degree, transfer matrix, Geodetector, and PLUS model to analyse the spatiotemporal dynamics of LUCC from 2002 to 2022, identify driving mechanisms, and predict the land use pattern from 2027 to 2032. The results showed that (1) from 2002 to 2022, farmland decreased by 86.1075 km², man-made surfaces increased by 63.7389 km² (annual expansion rate of 2.86%), grassland slightly increased by 24.5592 km², and other land types remained stable; (2) the dynamics of land use showed a phased characteristic of “growth–equilibrium–acceleration”, and the land use degree index rose to 2.8639; natural factors (elevation, soil, temperature) dominated LUCC, and most interactions among factors showed enhancement effects; (3) the PLUS model predicted that by 2032, farmland would decrease to 224.347 km² and man-made surfaces would increase to 111.941 km². This study clarifies the laws of LUCC in Shihezi, demonstrates driving analysis and simulation prediction, and provides scientific support for balancing urban development, agricultural protection, and ecological security in arid oasis regions. Full article

The historic landscape and the value of the ancient city in the stock era present a diversified and mixed problem; as such, this study explores a quantifiable spatial correlation method for landscape layering characteristics and value space, in order to provide support for the urban renewal paths that integrate historical and contemporary needs. Taking as an example Chaozhou Ancient City, a renowned historical and cultural city in China, this study draws on the theory of historical urban landscape layering and comprehensively uses historical graphic interpretation, GIS spatial quantitative analysis, the single-land-use dynamic degree model, the Analytic Network Process, and the Delphi method to quantitatively analyze and evaluate the landscape layering characteristics and value space of the ancient city. Meanwhile, it explores the relationship between the historical landscape layering characteristics and value space of ancient cities using the spatial autocorrelation model and the coupling coordination modulus model. The key findings are as follows: (1) The high-layer space (66.1%) and high-value space (31.1%) of the historic landscape of Chaozhou Ancient City show significant mismatch and imbalance. Spatially, layer spaces increase from the city center toward the periphery, whereas value spaces decrease from the center outward, demonstrating marked spatial heterogeneity. (2) The layer–value space shows a spatial distribution of agglomeration, with Moran’s I index values of 0.2712 and 0.6437, respectively. The agglomeration degree of the value space is much higher than that of the layer space, and both show significant non-equilibrium and associative coupling. (3) Coupling coordination: basically balanced (D = 0.56) indicates a transition toward a more integrated state, although 48% of the region remains in a state of severe dysfunction, mainly consisting of two types of spaces: “high-layer–high-value” and “low-layer–low-value.” These two dysfunctional types should be prioritized in future conservation and renewal strategies. This study provides a more comprehensive quantitative analysis path for identifying and evaluating the landscape layer–value space of the ancient city, providing visualization tools and decision-making support for the future protection and renewal of Chaozhou Ancient City and the declaration of the World Heritage. Full article

Background: The aim of this study was a qualitative assessment and quantitative assessment, i.e., the assessment of time to stability (TTS) before and after fatigue test, of landing in patients with chronic ankle instability, referred to as “copers”, in comparison to a control group of healthy persons. The indirect aim of the study was to develop a new method to assess more time precise measurement of TTS. Methods: The study involved 60 physically young active individuals aged 18 to 35 years. They were divided into three groups: the study population of 29 copers was divided into: I—14 persons with chronic one side ankle instability, study population II—15 persons with chronic bilateral ankle instability, and the control group included 31 persons without ankle instability. The study involved quantitative assessment of time to stability (TTS) after single-leg landing onto the HUR stabilometric platform from a 30 cm high platform before and after fatigue tests based on a modified Short-Term Fatigue Protocol. To conduct qualitative assessment of landing and to verify time to stability with video imaging, a video analysis was conducted. We used three cameras and two markers: on the malleolus lateralis of the fibula and on the malleolus medialis of the tibia. Each landing was subjectively assessed by a physiotherapist on a four-degree scale. A further biomechanic analysis was conducted only for the trials with a correct landing. The trials were repeated after a fatigue test. Results: There were significant differences before and after the fatigue test in qualitative landing analysis (p < 0.001) only for one jump for the right leg. In groups with unilateral and bilateral ankle instability, there was a higher percentage of landings with a considerable shift or unstable landings. The conducted dynamic test (TTS assessment) did not reveal significant differences between groups or after the fatigue test. Conclusions: Copers develop effective mechanisms of compensation, allowing them to participate in physical activities without symptoms of joint instability. Determining biomechanical differences between athletes who return to their sport and patients who develop chronic instability is important in the context of introducing adequate physiotherapy. Full article

Rapid regional development and intensified human activities increasingly disturb ecosystems, posing substantial threats to the integrity of large-scale ecological zones. As a World Natural Heritage site and a crucial national ecological zone, the Zhangjiajie Scenic Area plays a pivotal role in China’s environmental conservation efforts. To comprehensively assess tourism ecological security in the Scenic Area and strengthen the scientific basis for resource management and policymaking, this study developed a multi-dimensional ecological security evaluation system covering 2010–2024, incorporating dynamic changes in perturbation, reaction, and governance. Using entropy weight–TOPSIS and coupling coordination models, combined with obstacle degree analysis, we examined the temporal trajectory of ecological security and analyzed its underlying driving mechanisms. The study also examined factors influencing the sustainable development of the ecosystem. The results indicate the following: (1) Tourism ecological security in the Scenic Area followed a V-shaped trajectory of “rapid degradation—steady recovery—impact and rebound.” It declined sharply to an unsafe level between 2010 and 2014, steadily recovered from 2015 to 2019, briefly dropped in 2020, and then rebounded, reaching a peak evaluation value of 0.519 in 2024. (2) The co-evolution of perturbation, reaction, and governance subsystems has matured: their coupling coordination degree has increased annually and has remained at the level of “intermediate coordination” since 2020. The reaction subsystem plays a central role, serving as a bridge between perturbation and governance. (3) The driving factors exhibit a phased evolutionary pattern of “elements—facilities—structure—function.” Cultivated land area, total road mileage, and artificial afforestation area constitute the main long-term constraints. This research provides important insights for strengthening ecological security and sustainability in the Scenic Area while advancing regional ecosystem development. It also offers valuable guidance for ecological security management and policymaking in similar nature reserves. Full article

China’s major function-oriented zoning (MFOZ) serves as a crucial policy instrument for functional regulation of land use, playing a significant role in the latest territorial spatial planning. Studies on the implementation of MFOZ have been conducted since its release in 2012, but there is a lack of comprehensive methods to assess the effectiveness of its implementation. In China, the newly initiated City Examination provides novel technical support for verifying MFOZ planning, addressing the gap in comprehensive evaluation methodologies and channels. This study proposes a comprehensive urban assessment framework and a major function classification approach based on City Examination data, enabling the identification of implementation deviations in MFOZ planning based on the current urban conditions reflected by City Examination. The methodology incorporates dimensionality reduction, multi-indicator clustering, entropy-weighted overlays, and natural break classification techniques and examines the degree of strategic deviation in China’s MFOZ through a comprehensive and systematic assessment. Due to the timeliness and long-term nature City Examination data, the method allows for the long-time dynamic tracking and evaluation of the real-time progress in MFOZ. Empirical analysis of Hubei Province revealed that 77.9% of its urban development aligns with the 2011 MFOZ scheme while demonstrating discernible deviation types and hierarchical discrepancies, with geographically clustered patterns observed among cities exhibiting such deviations. Full article

Antibiotic resistance (AR) in environmental Escherichia coli represents a growing public health challenge. This study evaluated the prevalence of AR among E. coli isolates recovered from surface water bodies within the Ameca River basin in Jalisco, Mexico, and examined associations with anthropogenic influence and seasonal variation. Over a 1-year period, water samples were collected monthly from 16 sites, including tributaries, wetlands, and main river channels with differing degrees of urban impact. E. coli isolates were confirmed by malB gene PCR and tested for susceptibility to six antibiotics using the Kirby–Bauer disk diffusion method. High resistance frequencies were observed for ampicillin (93.9%), tetracycline (92.4%), and streptomycin (89.6%), while gentamicin exhibited the lowest resistance rate (48.1%). Resistance prevalence was significantly higher at sites adjacent to urban settlements and during the rainy season (p < 0.05). These findings underscore the influence of land use and seasonal dynamics on AR dissemination in aquatic environments and highlight the need for improved wastewater management strategies to mitigate the spread of resistant bacteria. Full article

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in Zhejiang Province, China, as a case study, with the research objective of exploring the processes, patterns, and mechanisms of the coevolution between ecosystem services (ES) and human well-being (HWB) in ecotourism-dominated counties. By integrating multi-source heterogeneous data, including land use data, the normalized difference vegetation index (NDVI), and statistical records, and employing methods such as the dynamic equivalent factor method, the PLUS model, the coupling coordination degree model, and comprehensive evaluation, we analyzed the synergistic evolution of ES-HWB in Chun’an County from 2000 to 2020. The results indicate that (1) the ecosystem service value (ESV) fluctuated between 30.15 and 36.85 billion CNY, exhibiting a spatial aggregation pattern centered on the Qiandao Lake waterbody, with distance–decay characteristics. The PLUS model confirms ecological conservation policies optimize ES patterns. (2) The HWB index surged from 0.16 to 0.8, driven by tourism-led economic growth, infrastructure investment, and institutional innovation, facilitating a paradigm shift from low to high well-being at the county level. (3) The ES-HWB interaction evolved through three phases—disordered, antagonism, and coordination—revealing tourism as a key mediator driving coupled human–environment system sustainability via a pressure–adaptation–synergy transmission mechanism. This study not only advances the understanding of ES-HWB coevolution in ecotourism-dominated counties, but also provides a transferable methodological framework for sustainable development in similar regions. Full article

Amid China’s national strategic prioritization of the Chengdu–Chongqing Economic Circle and accelerated territorial spatial planning, this study deciphered the synergistic evolution of Land Use Intensity (LUI) and Balance Degree of Land Use Structure (BDLUS) during rapid urbanization. Leveraging 1 km grid units and integrating emerging spatiotemporal hotspot analysis, BFAST, and geographic detectors, we systematically analyzed spatiotemporal patterns and drivers of LUI, BDLUS, and their Coupling Coordination Degree (CCD) from 2000 to 2022. Key findings: (1) LUI strongly correlated with economic growth, with core areas reaching high-intensity development (average > 2.96) versus ecologically constrained marginal zones (<2.42), marked by abrupt changes during 2011–2014; (2) BDLUS improvements covered 82.22% of the study area, driven by the Yangtze River Economic Belt strategy (21.96% hotspot concentration), yet structural imbalance persisted in transitional zones (18.81% cold spots); (3) CCD exhibited center-edge dichotomy, contrasting high-value cores (CCD > 0.68) with ecologically sensitive edges (9.80% cold spots), peaking in regulatory shifts around 2010; (4) terrain constraints and intensified human activities (the interaction effect between nighttime lighting and population density increased by 219.49% after 2020) jointly governed coupling mechanisms, with urbanization and industrial transition becoming dominant drivers. This research advances an “intensity–structure–coordination” framework and elucidates “dual-core resonance” dynamics, offering theoretical foundations for spatial optimization and ecological civilization. Full article

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

Background/Objectives: The simulation of human movement offers transformative potential for the design of medical devices, particularly in understanding the cause–effect dynamics in individuals with neurological or musculoskeletal impairments. This study presents a simulation-driven framework to determine the optimal ankle–foot orthosis (AFO) stiffness for mitigating the risk of ankle sprains due to excessive subtalar inversion during high-impact activities, such as landing from a free fall. Methods: We employed biomechanical simulations to assess the influence of translational stiffness on subtalar inversion control, given that inversion angles exceeding 25 degrees are strongly correlated with injury risk. Simulations were conducted using a musculoskeletal model with and without a passive AFO; the stiffness varied in three anatomical directions. A Design of Experiments (DoE) approach was utilized to capture nonlinear interactions among stiffness parameters. Results: The results indicated that increased translational stiffness significantly reduced inversion angles to safer levels, though direction–dependent effects were noted. Based on these insights, we developed a 4D visualization tool that integrates simulation data with an interactive color–coded interface to depict ”safe design” zones for various AFO stiffness configurations. This tool supports clinicians in selecting stiffness values that optimize both safety and functional performance. Conclusions: The proposed framework enhances clinical decision-making and engineering processes by enabling more accurate and individualized AFO designs. Full article