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Climate change represents one of the main challenges of this century. The hazards generated by this process are various and involve territorial assets all over the globe. Hydrogeological risk represents one of these aspects, and the violence of rain precipitations has led experts to focus their interest on the study of geotechnical assets in relation to these dangerous weather events. At the same time, geospatial representation in 3D WebGIS based on open-source solutions led specialists to employ this kind of technology to remotely analyze and monitor territorial events considering different sources of information. This study considers the construction of a 3D WebGIS framework for the real-time management of geospatial information developed with open-source technologies applied to the dynamic mapping of precipitation in the metropolitan area of Palermo (Italy) based on real-time weather station acquisitions. The structure considered is a WebGIS platform developed with Cesium.js JavaScript libraries, the Postgres database, Geoserver and Mapserver geospatial servers, and the Anaconda Python platform for activating real-time data connections using Python scripts. This framework represents a basic geospatial digital twin structure useful to municipalities, civil protection services, and firefighters for land management and for activating any preventive operations to ensure territorial safety. Furthermore, the open-source nature of the platform favors the free diffusion of this solution, avoiding expensive applications based on property software. The components of the framework are available and shared using GitHub. Full article

To ensure water source security and sustainability of the national major strategic project “South-to-North Water Diversion”, this study aims to evaluate the spatio-temporal evolution characteristics of the ecosystem service value (ESV) in its water source area from 2002 to 2022. This study reveals its changing trends and main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Quantitative assessment of the ESV of the region was carried out using the Equivalence Factor Method (EFM), aiming to provide scientific support for ecological protection and resource management decision-making. In the past 20 years, the ESV has shown an upward trend year by year, increasing by 96%. The regions with the highest ESV were Garzê Prefecture and Aba Prefecture, which increased by 130.3% and 60.6%, respectively. The ESV of Xinlong county, Danba county, Rangtang county, and Daofu county increased 4.8 times, 1.5 times, 12.5 times, and 8.9 times, respectively. In the last two decades, arable land has decreased by 91%, while the proportions of bare land and water have decreased by 84% and 91%, respectively. Grassland had the largest proportion. Forests and grasslands, vital for climate regulation, water cycle management, and biodiversity conservation, have expanded by 74% and 43%, respectively. It can be seen from Moran’s I index values that the dataset as a whole showed a slight positive spatial autocorrelation, which increased from −0.041396 to 0.046377. This study reveals the changing trends in ESV and the main influencing factors, and thereby provides scientific support for the ecological protection and management of the water source area. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. Based on 423 valid distribution points, this study utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Leontopodium nanum under both current and future climate scenarios, while clarifying the key factors that influence its distribution. The primary ecological drivers of distribution are altitude (2886.08 m–5576.14 m) and the mean temperature of the driest quarter (−6.60–1.55 °C). Currently, the suitable habitat area is approximately 520.28 × 10⁴ km², covering about 3.5% of the global land area, concentrated mainly in the Tibetan Plateau, with smaller regions across East and South Asia. Under future climate scenarios, low-emission (SSP126), suitable areas are projected to expand during the 2050s and 2070s. High-emission (SSP585), suitable areas may decrease by 50%, with a 66.07% reduction in highly suitable areas by the 2070s. The greatest losses are expected in the south-eastern Tibetan Plateau. Regarding dynamic habitat changes, by the 2050s, newly suitable areas will account for 51.09% of the current habitat, while 68.26% of existing habitat will become unsuitable. By the 2070s, newly suitable areas will rise to 71.86% of the current total, but the loss of existing areas will exceed these gains, particularly under the high-emission scenario. The centroid of suitable habitats is expected to shift northward, with migration distances ranging from 23.94 km to 342.42 km. The most significant shift is anticipated under the SSP126 scenario by the 2070s. This study offers valuable insights into the distribution dynamics of L. nanum and other alpine species under the context of climate change. From a conservation perspective, it is recommended to prioritize the protection and restoration of vegetation in key habitat patches or potential migration corridors, restrict overgrazing and infrastructure development, and maintain genetic diversity and dispersal capacity through assisted migration and population genetic monitoring when necessary. These measures aim to provide a robust scientific foundation for the comprehensive conservation and sustainable management of the grassland ecosystem on the Qinghai–Tibet Plateau. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

Posidonia oceanica seagrass, endemic to the Mediterranean Sea, provides ecological goods and ecosystem services of paramount importance. In shallow and sheltered bays, P. oceanica meadows can reach the sea surface, with leaf tips slightly emerging, forming fringing and barrier reefs. During the 20th century, P. oceanica declined conspicuously in the vicinity of large ports and urbanized areas, particularly in the north-western Mediterranean. The main causes of decline are land reclamation, anchoring, bottom trawling, turbidity and pollution. Artificial sand nourishment of beaches has also been called into question, with sand flowing into the sea, burying and destroying neighbouring meadows. A fringing reef of P. oceanica, located at Saint-Mandrier-sur-Mer, near the port of Toulon (Provence, France), is severely degraded. Analysis of aerial photos shows that, since the beginning of the 2000s, it has remained stable in some parts or continued to decline in others. This contrasts with the trend towards recovery, observed in France, thanks to e.g., the legally protected status of P. oceanica, and the reduction of pollution and coastal developments. The sand nourishment of the study beach, renewed every year, with the sand being washed or blown very quickly (within a few months) from the beach into the sea, burying the P. oceanica meadow, seems the most likely explanation. Other factors, such as pollution, trampling by beachgoers and overgrazing, may also play a role in the decline. Full article

Urban coral reefs in Jakarta Bay and the Thousand Islands, Indonesia, are chronically exposed to land-based pollution and increasing thermal stress. These reefs—including the site of Indonesia’s first recorded coral bleaching event in 1983—remain highly vulnerable to climate-induced disturbances. During the fourth global coral bleaching event (GCBE), we recorded selective bleaching in the region, associated with a Degree Heating Weeks (DHW) value of 4.8 °C-weeks. Surveys conducted in January 2024 across a shelf gradient at four representative islands revealed patchy bleaching, affecting various taxa at depths ranging from 3 to 13 m. A follow-up survey in May 2024, which tracked the fate of 42 tagged bleached colonies, found that 36% had fully recovered, 26% showed partial recovery, and 38% had died. Bleaching responses varied across taxa, depths, and microhabitats, often occurring in close proximity to unaffected colonies. While some corals demonstrated resilience, the overall findings underscore the continued vulnerability of urban reefs to escalating thermal stress. This highlights the urgent need for a comprehensive and coordinated national strategy—not only to monitor bleaching and assess reef responses, but also to strengthen protection measures and implement best-practice restoration. Such efforts are increasingly critical in the face of more frequent and severe bleaching events projected under future climate scenarios. Full article

Against the backdrop of rapid urbanization in western China, which has triggered remarkable land-use changes and habitat degradation, Chengdu, as a developed city in China, plays a demonstrative and leading role in the economic and social development of China during the transition period. Therefore, integrated modeling approaches are required to balance development and conservation. This study responds to this need by conducting a scenario-based assessment of urbanization-induced land-use changes and regional habitat quality dynamics in Chengdu (1990–2030), using the FLUS-InVEST model. By integrating remote sensing-derived land-use data from 1990, 1995, 2000, 2005, 2010, 2015, and 2020, we simulate future regional habitat quality under three policy scenarios: natural development, ecological priority, and cropland protection. Key findings include the following: (1) From 1990 to 2020, cropland decreased by 1917.78 km², while forestland and built-up areas increased by 509.91 km² and 1436.52 km², respectively. Under the 2030 natural development scenario, built-up expansion and cropland reduction are projected. Ecological priority policies would enhance forestland (+4.2%) but slightly reduce cropland. (2) Regional habitat quality declined overall (1990–2020), with the sharpest drop (ΔHQ = −0.063) occurring between 2000 and 2010 due to accelerated urbanization. (3) Scenario analysis reveals that the ecological priority strategy yields the highest regional habitat quality (HQ_mean = 0.499), while natural development results in the lowest (HQ_mean = 0.444). This study demonstrates how the FLUS-InVEST model can quantify the trade-offs between urbanization and regional habitat quality, offering a scientific framework for balancing development and ecological conservation in rapidly urbanizing regions. The findings highlight the effectiveness of ecological priority policies in mitigating habitat degradation, with implications for similar cities seeking sustainable land-use strategies that integrate farmland protection and forest restoration. Full article

The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined multi-source data such as DEM, soil texture and land use type, in order to construct scenarios of territorial spatial change (TSC) across distinct periods. Based on the CMADS-L40 data and the SWAT model, it simulated the runoff dynamics in the Xitiaoxi River Basin, and analyzed the hydrological response characteristics under different TSCs. The results showed that The SWAT model, driven by CMADS-L40 data, demonstrated robust performance in monthly runoff simulation. The coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSE), and the absolute value of percentage bias (|PBIAS|) during the calibration and validation period all met the accuracy requirements of the model, which validated the applicability of CMADS-L40 data and the SWAT model for runoff simulation at the watershed scale. Changes in territorial spatial patterns are closely correlated with runoff variation. Changes in agricultural production space and forest ecological space show statistically significant negative correlation with runoff change, while industrial production space change exhibits a significant positive correlation with runoff change. The expansion of production space, particularly industrial production space, leads to increased runoff, whereas the enlargement of agricultural production space and forest ecological space can reduce runoff. This article contributes to highlighting the role of land use policy in hydrological regulation, providing a scientific basis for optimizing territorial spatial planning to mitigate flood risks and protect water resources. Full article

The ecological environment is crucial for human survival and development. As ecological issues become more pressing, studying the spatiotemporal evolution of ecological quality (EQ) and its driving mechanisms is vital for sustainable development. This study, based on MODIS data from 2000 to 2022 and the Google Earth Engine platform, constructs a remote sensing ecological index for the Beibu Gulf Urban Agglomeration and analyzes its spatiotemporal evolution using Theil–Sen trend analysis, Hurst index (HI), and geographic detector. The results show the following: (1) From 2000 to 2010, EQ improved, particularly from 2005 to 2010, with a significant increase in areas of excellent and good quality due to national policies and climate improvements. From 2010 to 2015, EQ degraded, with a sharp reduction in areas of excellent quality, likely due to urban expansion and industrial pressures. After 2015, EQ rebounded with successful governance measures. (2) The HI analysis indicates that future changes will continue the past trend, especially in areas like southeastern Chongzuo and northwestern Fangchenggang, where governance efforts were effective. (3) EQ shows a positive spatial correlation, with high-quality areas in central Nanning and Fangchenggang, and low-quality areas in Nanning and Beihai. After 2015, both high–high and low–low clusters showed changes, likely due to ecological governance measures. (4) NDBSI (dryness) is the main driver of EQ changes (q = 0.806), with significant impacts from NDVI (vegetation coverage), LST (heat), and WET (humidity). Urban expansion’s increase in impervious surfaces (NDBSI rise) and vegetation loss (NDVI decline) have a synergistic effect (q = 0.856), significantly affecting EQ. Based on these findings, it is recommended to control construction land expansion, optimize land use structure, protect ecologically sensitive areas, and enhance climate adaptation strategies to ensure continuous improvement in EQ. Full article

Archaeological sites located on the edge of growing cities often struggle to reconcile heritage protection with rapid development. To understand this tension, we examined a 50.83 km² zone around the Western Han Imperial Mausoleums in the Qin-Han New District. Using Landsat images from 1992, 2002, 2012, and 2022, this study applied supervised classification, land-use transfer matrices, and dynamic-degree analysis to trace three decades of land-use change. From 1992 to 2022, built-up land expanded by 29.85 percentage points, largely replacing farmland, which shrank by 35.64 percentage points and became fragmented. Forest cover gained a modest 5.78 percentage points and migrated eastward toward the mausoleums. Overall, urban growth followed a “spread–integrate–connect” pattern along major roads. This study interprets these trends through five interrelated drivers, including policy, planning, economy, population, and heritage protection, and proposes an integrated management model. The model links archaeological pre-assessment with land-use compatibility zoning and active community participation. Together, these measures offer a practical roadmap for balancing conservation and sustainable land management at imperial burial complexes and similar urban fringe heritage sites. Full article

Coal gangue, a major by-product of coal mining, poses significant environmental challenges due to its large-scale accumulation, land occupation, and potential for air and water pollution. This manuscript presents a comprehensive overview of continuous chamber gangue storage technology as a sustainable mining solution for coal mines. The principles of this approach emphasize minimizing disturbance to overlying strata, enabling uninterrupted mining operations, and reducing both production costs and environmental risks. By storing the surface or underground gangue in continuous chambers, the proposed method ensures the roof stability, maximizes the waste storage, and prevents the interaction between mining and waste management processes. Detailed storage sequences and excavation methods are discussed, including continuous and jump-back excavation strategies tailored to varying roof conditions. The process flows for both underground and ground-based chamber storage are described, highlighting the integration of gangue crushing, paste preparation, and pipeline transport for efficient underground storage. In a case study with annual storage of 500,000 t gangue, the annual economic benefit reached CNY 1,111,425,000. This technology not only addresses the urgent need for sustainable coal gangue management, but also aligns with the goals of resource conservation, ecological protection, and the advancement of green mining practices in the coal industry. Full article

Eco-enzymatic stoichiometry provides a basis for understanding soil ecosystem functions, with implications for land management and ecological protection. Long-term climatic factors and human interferences have caused significant land-use transformations in the Qinghai–Tibet Plateau region, affecting various ecological functions, such as soil nutrient cycling and chemical element balance. It is currently unclear how large-scale land-use conversion affects soil ecological stoichiometry. In this study, 763 soil samples were collected across three land-use types: farmland, grassland, and forest land. In addition, changes in soil physicochemical properties and enzyme activity and stoichiometry were determined. The soil available phosphorus (SAP) and total phosphorus (TP) concentrations were the highest in farmland soil. Bulk density, pH, SAP, TP, and NO₃⁻-N were lower in forest soil, whereas NH₄⁺-N, available nitrogen, soil organic carbon (SOC), available potassium, and the soil nutrient ratio increased. Land-use conversion promoted soil β-1,4-glucosidase, N-acetyl-β-glucosaminidase, and alkaline phosphatase activities, mostly in forest soil. The eco-enzymatic C:N ratio was higher in farmland soils but grassland soils had a higher enzymatic C:P and N:P. Soil microorganisms were limited by P nutrients in all land-use patterns. C limitation was the highest in farmland soil. The redundancy analysis indicated that the ecological stoichiometry in farmland was influenced by TN, whereas grass and forest soils were influenced by SOC. Overall, the conversion of cropland or grassland to complex land-use types can effectively enhance soil nutrients, enzyme activities, and ecosystem functions, providing valuable insights for ecological restoration and sustainable land management in alpine regions. Full article

The Three Gorges Reservoir Area (TGRA) is an important ecological barrier and cultural intermingling zone in the upper reaches of the Yangtze River, and its traditional villages carry unique information about natural changes and civilisational development, but face the challenges of conservation and development under the impact of modernisation and ecological pressure. This study takes 112 traditional villages in the TGRA that have been included in the protection list as the research objects, aiming to construct a cultural landscape identification framework for the traditional villages in the TGRA. Through field surveys, landscape feature assessments, GIS spatial analysis, and multi-source data analysis, we systematically analyse their cultural landscape type systems and spatial differentiation characteristics, and then reveal their cultural landscape types and spatial differentiation patterns. (1) The results of the study show that the spatial distribution of traditional villages exhibits significant altitude gradient differentiation—the low-altitude area is dominated by traffic and trade villages, the middle-altitude area is dominated by patriarchal manor villages and mountain farming villages, and the high-altitude area is dominated by ethno-cultural and ecologically dependent villages. (2) Slope and direction analyses further reveal that the gently sloping areas are conducive to the development of commercial and agricultural settlements, while the steeply sloping areas strengthen the function of ethnic and cultural defence. The results indicate that topographic conditions drive the synergistic evolution of the human–land system in traditional villages through the mechanisms of agricultural optimisation, trade networks, cultural defence, and ecological adaptation. The study provides a paradigm of “nature–humanities” interaction analysis for the conservation and development of traditional villages in mountainous areas, which is of practical value in coordinating the construction of ecological barriers and the revitalisation of villages in the reservoir area. Full article

In response to the global ecological and agricultural challenges posed by coastal saline-alkali areas, this study focuses on Dongying City as a representative region, aiming to develop a high-precision soil salinity prediction mapping method that integrates multi-source remote sensing data with machine learning techniques. Utilizing the SCORPAN model framework, we systematically combined diverse remote sensing datasets and innovatively established nine distinct strategies for soil salinity prediction. We employed four machine learning models—Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Geographical Gaussian Process Regression (GGPR) for modeling, prediction, and accuracy comparison, with the objective of achieving high-precision salinity mapping under complex vegetation cover conditions. The results reveal that among the models evaluated across the nine strategies, the SVR model demonstrated the highest accuracy, followed by RF. Notably, under Strategy IX, the SVR model achieved the best predictive performance, with a coefficient of determination (R²) of 0.62 and a root mean square error (RMSE) of 0.38 g/kg. Analysis based on SHapley Additive exPlanations (SHAP) values and feature importance indicated that Vegetation Type Factors contributed significantly and consistently to the model’s performance, maintaining higher importance than traditional salinity indices and playing a dominant role. In summary, this research successfully developed a comprehensive, high-resolution soil salinity mapping framework for the Dongying region by integrating multi-source remote sensing data and employing diverse predictive strategies alongside machine learning models. The findings highlight the potential of Vegetation Type Factors to enhance large-scale soil salinity monitoring, providing robust scientific evidence and technical support for sustainable land resource management, agricultural optimization, ecological protection, efficient water resource utilization, and policy formulation. Full article

In mining areas with high groundwater levels, intensive coal mining has led to the accumulation of substantial surface water and significant alterations in regional landscape patterns. Reconstructing the ecological security pattern (ESP) has emerged as a critical focus for ecological restoration in coal mining subsidence areas with high groundwater levels. This study employed the patch-generating land use simulation (PLUS) model to predict the landscape evolution trend of the study area in 2032 under three scenarios, combining environmental characteristics and disturbance features of coal mining subsidence areas with high groundwater levels. In order to determine the differences in ecological network changes within the study area under various development scenarios, morphological spatial pattern analysis (MSPA) and landscape connectivity analysis were employed to identify ecological source areas and establish ecological corridors using circuit theory. Based on the simulation results of the optimal development scenario, potential ecological pinch points and ecological barrier points were further identified. The findings indicate that: (1) land use changes predominantly occur in urban fringe areas and coal mining subsidence areas. In the land reclamation (LR) scenario, the reduction in cultivated land area is minimal, whereas in the economic development (ED) scenario, construction land exhibits a marked increasing trend. Under the natural development (ND) scenario, forest land and water expand most significantly, thereby maximizing ecological space. (2) Under the ND scenario, the number and distribution of ecological source areas and ecological corridors reach their peak, leading to an enhanced ecological network structure that positively contributes to corridor improvement. (3) By comparing the ESP in the ND scenario in 2032 with that in 2022, the number and area of ecological barrier points increase substantially while the number and area of ecological pinch points decrease. These areas should be prioritized for ecological protection and restoration. Based on the scenario simulation results, this study proposes a planning objective for a “one axis, four belts, and four zones” ESP, along with corresponding strategies for ecological protection and restoration. This research provides a crucial foundation for decision-making in enhancing territorial space planning in coal mining subsidence areas with high groundwater levels. Full article