Search Results (6,392)

Within the domain of Earth observation, tracking terrestrial transitions via high-resolution optical data plays a fundamental role. Nevertheless, current methods face critical challenges, including the difficulty in collaborative modeling of local details and global features and the singularity of bi-temporal difference representation, along with insufficient cross-scale feature communication, thereby constraining both the precision and resilience of models when applied to complicated environments. To solve these problems, we propose LADENet (Locally Adaptive Mamba and Multi-scale Feature Enhancement Network), an innovative framework that synergizes CNN, Transformer, and Mamba paradigms. By leveraging customized local contextual refinement alongside sophisticated hierarchical fusion, this integration delivers highly precise and resilient detection performance. LADENet adopts a weight-sharing multi-level Transformer encoder combined with a sequence reduction mechanism to generate multi-scale global features, achieving precise alignment of bi-temporal features and global context modeling while reducing computational complexity. To realize accurate localization and local enhancement of changed regions, we design a dual spatiotemporal adaptive local feature marking module based on State-Space Scanning (SSS). This module screens high-saliency changed regions through an adaptive scanning strategy, realizes pixel-aligned spatiotemporal feature fusion via cross-temporal state-space scanning, and introduces a sliding window boundary calibration mechanism to alleviate boundary information loss caused by window segmentation. To strengthen the feature representation of changed regions, a dual-branch difference enhancement module is constructed, which collaboratively captures global change trends and fine-grained local features through an attention-enhanced difference branch and a multi-scale convolution concatenation branch, effectively suppressing background interference. To address the semantic gap between cross-scale features, a global cross-scale spatial feature fusion decoder is proposed, which balances local detail preservation and global context perception through the synergy of spatial attention and two-dimensional selective scanning, completing refined multi-scale feature fusion and spatial resolution recovery. To rigorously validate the proposed LADENet, comprehensive experiments were conducted across four widely adopted bi-temporal benchmarks: LEVIR-CD, WHU-CD, CLCD-CD, and GVLM-CD. The presented architecture establishes substantial superiority over existing cutting-edge methodologies across primary evaluation criteria. Specifically, it yields an F1-measure of 91.06% alongside an IoU of 85.28% in the LEVIR-CD tests, while registering 90.51% (F1) and 82.45% (IoU) for WHU-CD. Similarly, robust outcomes are delivered on CLCD-CD (82.15% F1, 72.83% IoU) as well as GVLM-CD (89.12% F1, 77.78% IoU). These results demonstrate that LADENet possesses excellent detection accuracy, boundary delineation capability and generalization performance in diverse and intricate bi-temporal observation environments. Full article

This study investigated vegetation frontline dynamics, fractional vegetation cover (FVC), and community succession in the tidal-flat wetlands of the Liaohe Estuary. The eastern bank of the Liaohe River within the Shuangtaihe National Nature Reserve was selected as the study area, and six periods of Landsat and Gaofen-1 (GF-1) imagery from 2000 to 2025 were used. Remote-sensing preprocessing, normalized difference vegetation index (NDVI)-based FVC inversion, vegetation frontline extraction, Digital Shoreline Analysis System (DSAS)-based rate calculation, land-cover classification, and spatial correlation analysis were integrated to characterize wetland spatiotemporal dynamics and succession patterns. The results showed that the linear regression rate (LRR) and end point rate (EPR) effectively captured the long-term trend and five short-term fluctuations in vegetation frontline migration. FVC fluctuated markedly over the 25-year period, whereas the weighted average (WA) of the five FVC classes remained generally stable and effectively summarized overall vegetation growth. Vegetation frontline migration was spatially associated with annual FVC change (ΔFVC); both LRR and ΔFVC showed significant positive spatial autocorrelation and evident spatial clustering. In addition, the conversion among mudflats, Suaeda salsa, Phragmites australis, and water bodies was closely coupled with frontline migration. These findings provide a scientific basis for quantifying coastal wetland sustainability and for designing spatially targeted restoration strategies in the Liaohe Estuary. The proposed coupling analysis framework also offers a transferable remote sensing approach for monitoring wetland sustainability under changing environmental conditions. Full article

Accurately assessing the spatiotemporal evolution of ecological environment quality (EEQ) on the Loess Plateau of Northern Shaanxi is of great significance for consolidating the ecological security barrier of the Yellow River Basin. Most of the existing research focuses on a single ecological theme, which does not reflect the overall ecological status of the region. In this study, a remote sensing ecological index (RSEI) model was constructed to systematically assess the EEQ from 2000 to 2024. The Theil–Sen estimator, Mann–Kendall test, and Hurst exponent were jointly employed to detect change significance and predict future trends, while the Geodetector model was applied to explore driving factors. The results were as follows: (1) EEQ exhibited a fluctuating but overall upward trend, with the mean RSEI rising from 0.376 in 2000 to 0.545 in 2024—an average annual increase of approximately 0.00569. (2) Spatially, a distinct pattern of “higher in the south, lower in the north and the lowest in the northwest” was observed. Over the 25-year period, the combined proportion of “excellent” and “good” grades increased by roughly 20 percentage points, and the “moderate” grade expanded from 13.61% to 47.12%. (3) Areas showing an improving trend accounted for 91.21% of the total area and highly overlapped with those projected to improve in the future. (4) Single-factor detection revealed that geomorphological type exerted the greatest influence on the spatial heterogeneity of EEQ, with a multi-year mean q-value of 0.701. Interaction detection further indicates that the geomorphology–land use interaction may continue to shape the regional EEQ’s spatial distribution. These findings provide a scientific basis for precise ecological restoration planning and spatial optimization on the Loess Plateau of Northern Shaanxi. Full article

With global warming and rapid urbanization, short-duration summer rainstorms are becoming more intense and localized, posing growing challenges to urban flood resilience. However, their spatiotemporal characteristics, vertical structures, and environmental drivers remain poorly understood. Here, we combine multi-source remote sensing datasets and China’s new-generation satellite-borne dual-frequency precipitation radar observations to investigate summer rainstorms in Nanjing, China, during 2017–2024. Results reveal pronounced spatiotemporal heterogeneity, with higher rainfall intensities concentrated over urban and adjacent areas. During the study period, rainstorm intensity and duration increased by 7.44% and 38.63%, respectively, while the affected area decreased by 8.18%, indicating a transition toward more localized yet more intense rainfall events. Environmental analyses suggest that large-scale thermodynamic conditions and regional topographic forcing provide a favorable background for convection development, while local urban thermal effects may further modulate rainfall enhancement. Three-dimensional radar detection of an illustrative rainstorm event indicates an inverted-cone vertical structure, suggesting a mixed convective-stratiform precipitation structure involving both warm-rain and ice-phase processes. An Explainable Bayesian-Optimized XGBoost (EBOX) model further identifies near-surface air temperature and specific humidity as the primary environmental factors associated with rainstorm occurrence and development. Overall, this study highlights the value of integrating satellite remote sensing with explainable artificial intelligence to improve understanding of urban extreme rainfall and provide new insights into how climate change, topography, and urbanization jointly shape precipitation extremes in rapidly urbanizing monsoon regions. Full article

Vegetation is a key component of ecosystems and a core indicator for monitoring terrestrial ecosystem changes. Studying its spatio-temporal dynamics and natural drivers is essential for ecological restoration and management in the Loess Plateau, a region with fragile ecology and complex human-land interactions. Using data from 2000 to 2024, this study systematically investigated the spatio-temporal evolution patterns, future trends, and primary influencing factors of Fractional Vegetation Cover (FVC) by integrating the Dimidiate Pixel Model, trend analysis, Hurst index, and optimal parameter geographic detector methods. The results show that: (1) Over the 25 years, FVC on the Loess Plateau showed an overall fluctuating upward trend, with a spatial distribution pattern characterized as “low in the northwest and high in the southeast”, and notable variations across different land use types. (2) The FVC change trend was dominated by extremely significant and significant increases, accounting for 67.92% of the total area, while areas with no significant change accounted for 31.27%. Spatially, the central region exhibited strong persistence in its increasing trend, whereas the northwestern and southeastern margins tended to remain stable. (3) Precipitation was the most important single factor affecting FVC (explanatory power q = 0.4199). The interactive explanatory power of factors was higher than that of single factors, with precipitation and elevation having the strongest interaction (q = 0.5124). Land use type, as an anthropogenic proxy, also plays a significant regulatory role in FVC patterns. Using conventional remote sensing methods (dimidiate pixel model, trend analysis, Hurst index, and optimal parameter geographic detector), this study primarily contributes by extending the analysis period to 2024 and providing a focused assessment of post-2020 vegetation dynamics. This study systematically analyzes the spatio-temporal evolution patterns of FVC and quantifies the explanatory power of natural factors and land use as a human activity proxy on the Loess Plateau, providing a scientific basis for assessing regional ecological restoration effectiveness and optimizing ecological management strategies. Full article

Land Use and Land Cover (LULC) change is widely acknowledged as a pivotal driver of environmental change, exerting an escalating influence on surface hydrological processes. The accelerating pace of LULC alterations in response to burgeoning human populations underscores the pressing need for a comprehensive evaluation of their ramifications on surface runoff dynamics. This study investigates the impacts of LULC changes on flood behavior in a Mediterranean watershed in Crete, Greece (Geropotamos watershed). LULC data spanning the years 1990, 2006, and 2018 were procured from the European CORINE Land Cover database at a refined spatial resolution. The HEC-HMS hydrological model is employed to simulate peak discharge and associated hydrograph characteristics under varying recurrence intervals. Subsequently, selected river segments within the studied catchments undergo hydrodynamic flood modelling using the HEC-RAS hydraulic model. Flood depth maps are generated to illustrate the evolution of inundated areas relative to LULC change. The overarching objective of this research is to furnish a comprehensive understanding of how spatiotemporal variations in land use and land cover in-fluence flood characteristics, thereby facilitating informed decision making for sustainable planning. Full article

Carbon storage dynamics in dryland and semi-arid ecosystems remain a major uncertainty in global carbon cycle assessments, particularly in regions like the Yellow River Basin (YRB). Using the Arid Ecosystem Model (AEM), we simulated the spatiotemporal evolution of four major carbon pools—total carbon (TOTC), vegetation carbon (VEGC), soil organic carbon (SOC), and litter carbon (LTRC)—from 1981 to 2060 under factorial climate scenarios. During 1981–2020, TOTC increased by 0.09 Pg C (+3.54%), driven by gains in VEGC (+0.03 Pg C, +21.43%) and SOC (+0.06 Pg C, +2.78%). LTRC showed minimal net change but was highly sensitive to interannual variability. From 2021 to 2060, under the high-emission SSP5 scenario, TOTC is projected to increase by 0.114 Pg C (+4.81%), with VEGC contributing most of the gain (+23.87%). CO₂_only simulations showed similar increases, underscoring the dominant role of CO₂ fertilization. In contrast, warming and precipitation alone produced weaker and more variable effects. Spatially, upper YRB regions are expected to maintain strong sink capacity, while the Loess Plateau and central-western subregions remain vulnerable to warming and moisture decline. LTRC exhibited the highest variability across scenarios (−18% to +22%), highlighting its role as a sensitive indicator of sink stability. These findings emphasize the need to account for nonlinear climate–carbon interactions and regional heterogeneity. Region-specific, adaptive strategies that integrate ecological restoration and climate adaptation will be critical to enhancing carbon sinks and supporting China’s carbon neutrality targets in the Yellow River Basin. Full article

Wildfires in plateau and mountainous regions are increasingly destructive, often disrupting ground transportation networks and severely constraining emergency logistics, while unmanned aerial vehicles (UAVs) remain limited by payload capacity. To address this challenge, this study proposes an air–ground collaborative emergency material dispatch method for dynamic, time-varying wildfire environments. A multi-layer spatiotemporal network model is developed by incorporating key uncertainties, including fire spread and meteorological fluctuations, into dynamic parameters, and a multi-objective mixed-integer programming framework is established to jointly optimize emergency response time, total dispatch cost, and rescue fairness. To solve the resulting high-dimensional dynamic rescheduling problem, a Fast Ant Colony Optimization-Genetic Algorithm (FACO-GA) integrated with a rolling horizon mechanism is designed. Simulation results under Level 1–10 dynamic perturbations show that, compared with conventional standalone algorithms (GA and ACO), the proposed method demonstrates markedly better robustness and computational efficiency, reducing the extreme average rescheduling response time to 6.80 s, while maintaining a Hypervolume (Hv) retention rate of 96.30% and limiting the Spacing (Sp) change rate to 4.15%. These findings indicate that the proposed approach can effectively overcome computational bottlenecks and provide an adaptive decision-support framework for emergency logistics dispatch in complex wildfire scenarios. Furthermore, comprehensive ablation studies and sensitivity analyses validate the structural necessity of the rolling horizon and ACO modules, ensuring the algorithm’s parameter robustness under extreme stochastic perturbations. Full article

For advancing carbon peaking and neutrality objectives and regional socio-ecological sustainability, it is critical to examine how land use change and ecosystem carbon storage may evolve under different development scenarios, and to reveal the spatiotemporal patterns and key drivers of carbon sink capacity across the Lower Yangtze River Basin. Such analysis bears both substantial scientific insight and practical relevance. By coupling the PLUS, InVEST, and Geographical Detector models, the present study conducted a comprehensive assessment of land use and carbon storage dynamics in the Lower Yangtze River region from 2000 to 2025. We further explored how different factors drive the spatiotemporal variation in carbon storage, and predicted the potential land use patterns and associated carbon storage values in the research area by 2030 under three hypothetical scenarios. Collectively, our analysis yielded four core conclusions. (1) Between 2000 and 2025, the land use transformation in the research area was dominated by the continuous shrinkage of arable land and the expansion of construction land. (2) The total carbon storage in the study area declined steadily throughout the study period, showing distinct phased characteristics with a steep drop in the early stage and a slower decline thereafter. (3) Implementing the S2 scenario could effectively curb regional carbon storage loss, whereas the S3 Scenario would result in the most severe carbon stock depletion. (4) The spatial configuration of carbon storage is primarily structured by natural environmental factors. In light of these research outcomes, several recommendations are proposed to guide regional sustainable development. Specifically, efforts should be made to improve the intensive use of urban construction land, thereby minimizing carbon storage loss caused by urbanization. Additionally, develop scientific and targeted ecological conservation policies based on the spatial distribution patterns of high carbon storage zones. Finally, implementing regionally tailored management measures will help achieve coordinated and sustainable development across the study area. Full article

This study conducted a six-month time-series micro-topographic analysis using high-resolution UAV LiDAR technology to precisely characterize the complex terrain changes in regressive tidal creeks within coastal wetlands. To overcome the unique challenges posed by vegetation-dense regressive tidal flats, the LiDAR Penta Return (5-pulse) mode was applied, yielding high-density point cloud data with an average of 174 pts/m². The analysis successfully reproduced the bare earth surface beneath the vegetation canopy at sub-centimeter-level precision, overcoming the limitations of conventional optical surveying, and enabled quantitative detection of micro-topographic changes of ±25 cm or greater. Time-series analysis based on the DEM of Difference (DoD) revealed spatiotemporally asymmetric erosion and deposition patterns concentrated at the lower elevation zone (0.0–2.0 m) and slope boundaries of the regressive tidal creek. However, the apparent large elevation changes in the lowest, intermittently inundated creek-bed zone (including a maximum of about 3.7 m between the summer surveys, T2–T1) were found to scale monotonically with the tide level at the time of each flight, indicating that they are governed by the tide-dependent water-surface return rather than by genuine bed erosion. After excluding this water-affected zone, the consistently sub-aerial surface showed only modest net change over the six-month period, indicating that the regressive tidal creek adjusts gradually rather than through abrupt large-magnitude erosion and deposition. This study presents the essential value of high-precision time-series monitoring for assessing the geomorphic stability of coastal wetlands in an environment where extreme weather events under climate change are increasing in frequency. Full article

Water scarcity is redefining the limits of industrial development across the Middle East and North Africa (MENA), yet the regional dynamics of industrial water withdrawal remain poorly quantified. In this study, industrial water withdrawal was examined for 18 MENA countries over the period 1995–2022 using four seven-year periods, integrating spatio-temporal assessment, hierarchical clustering, Tapio decoupling, and Logarithmic Mean Divisia Index (LMDI) decomposition. The results showed that industrial water withdrawal per capita was highly concentrated: Iraq exceeded 300 m³/person/year between 1995 and 2001, and then declined to roughly 150–200 m³/person/year by 2002–2008, while Lebanon rose to 150–200 m³/person/year and became the highest-intensity case in the period 2009–2015 and 2016–2022. In addition, clustering identified four groups, with Egypt and Iraq forming a distinct pair and Saudi Arabia remaining structurally unique. Decoupling analysis presented favorable decoupling states most clearly in the 2002–2008 period, but became mixed after 2009. Decomposition further showed that population growth and economic development were the most persistent positive drivers of industrial water withdrawal, whereas technical change was the most variable counterforce. These results show that industrial water withdrawal in MENA is concentrated, structurally uneven, and increasingly shaped by country-specific interactions between growth, demography, technology, and industrial structure. The findings provide actionable evidence for policymakers, industrial planners, and water managers seeking to align industrial growth with water security in the MENA region. Full article

This study presents a meta-analysis of relatively high-resolution paleohydrological proxies derived from geological archives in Sardinia and in the Italian Peninsula–Sicily over the last 2000 years, with particular emphasis on the Medieval Warm Period (MWP) and the Little Ice Age (LIA). The investigated climate proxies, ranging from annual-decadal to centennial resolution, include terrestrial and marine sediment cores, glaciers, pollen spectra, speleothems, lake-level fluctuations, as well as sedimentary and geomorphological inventories. Such datasets were analyzed through holistic and stratigraphic approaches along West–East and North–South transects across the central Mediterranean. Limited temporal resolution and incomplete stratigraphic continuity of several paleoclimatic records from the investigated regions thwart full reconstructions of paleohydrological trends. Nevertheless, the presented meta-analysis has enabled: (1) the recognition of reliable paleoclimatic correlations between the two regions, which exhibit long-lasting anti-phase hydroclimatic trends (wetter conditions in Sardinia and drier conditions in central Italy during the MWP, with the opposite pattern during the LIA); and (2) the identification of the North Atlantic Oscillation (NAO) as the primary driver of these paleohydrological variations. The significance of this anti-phase pattern is discussed in the context of the North–South and West–East climatic dipoles identified in the Mediterranean region during the middle to late Holocene. Furthermore, we assessed the potential of the investigated paleohydrological network to: (1) compare reconstructed hydrological patterns with mean temperature and precipitation records derived from empirical and model-based climate reconstructions in southern Europe and the Mediterranean; and (2) identify gaps in data coverage that currently limit our understanding of high-resolution spatiotemporal hydrological variability and dynamics.The hydroclimatic pattern in Sardinia and in the Italian Peninsula–Sicily has exhibited marked spatio-temporal divergences, with major hydroclimatic transitions coincident with well-known solar minima over the last millennium, thus suggesting a possible cause-and-effect relationship. The interpretations presented in this study provide a framework for understanding how changes in the paleoclimatic variability of water resources may have influenced different regions of Italy since the Middle Ages, potentially affecting societal transitions as well as historical and socioeconomic dynamics. Comparison of the multidecadal-to-centennial reconstructions of paleohydrological patterns is presented for both areas, pending the development of new, higher-resolution, and more precisely dated proxies from the Italian records. Their importance is emphasized in order to improve reconstructions of past climate variability and to enhance assessments of future climate trajectories. Full article

Water yield is a key indicator for regional water resource assessment and directly concerns multidimensional socio-ecological sustainability. However, in arid and semi-arid regions, integrated long-term water yield simulation and nonlinear interpretation of driving factors remain insufficient. Therefore, Inner Mongolia was selected to analyze the spatial pattern and nonlinear driving mechanism of water yield depth for sustainable water resource management. Based on the InVEST model, water yield depth during 2001–2024 was simulated, and trend analysis was conducted. Annual XGBoost models with SHAP were used to explain nonlinear driver effects. Results showed a significant east-high and west-low pattern, with significantly increasing and decreasing areas accounting for 12.35% and 4.5%, respectively. Precipitation was the dominant driver, with higher ∣SHAP∣ values in wet years than in dry years. Zonal SHAP showed Pre led in all zones (48.8%, 63.5%, 37.7%), with secondary drivers shifting from forest/topography in the East to temperature in the West. SHAP values increased rapidly after precipitation exceeded thresholds of 200–300 mm in dry years and 400–500 mm in wet years. Under high precipitation, precipitation–non-forest interactions increased rapidly, whereas forest interactions changed little or became negative, showing a scissor-like divergence pattern. XGBoost reproduced the InVEST-simulated water yield depth well (R² = 0.91 ± 0.03). This workflow provides a reproducible pathway for water resource assessment in arid and semi-arid regions. Full article

High-altitude rock slides frequently occur in the high-mountain canyon regions of the eastern Tibetan Plateau, posing significant disaster risks. The Baige landslide catastrophically failed in October 2018, blocking the Jinsha River and forming a major landslide-dammed lake. However, quantitative understanding of the spatiotemporal evolution and environmental control mechanisms remains insufficient, particularly regarding stage-dependent driving mechanisms. This study investigates the Baige landslide using mall Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR), Seasonal-Trend decomposition based on Loess (STL) time-series decomposition, Principal Component Analysis–Independent Component Analysis (PCA-ICA) signal analysis, and slope-unit spatial statistics. Results indicate that: (1) deformation exhibited three stages separated by October 2018: slow pre-slide deformation, post-slide residual creep, and long-term sustained acceleration; (2) instability caused systematic restructuring of the deformation field, with valid pixels decreasing from 2766 to 560, deformation changing from slight positive line-of-sight (LOS) displacement to pronounced negative LOS displacement, and global standard deviation increasing from 21.40 mm to 40.55 mm, with stronger disturbances in the steep front zone; and (3) the driving mechanism shifted from short-term multi-factor control to a temperature-dominated long-term environmental control regime after failure, while gravity-driven creep and post-failure structural adjustment remained important background controls. Slope fragmentation and structural reorganization likely contributed to this transition. Full article

This study examines the evolving patterns and zoning characteristics of gas migration and storage zones during coal seam mining, taking the 215 fully mechanized longwall face at Huangling No. 2 Coal Mine as the engineering background. By integrating theoretical analysis, physical similarity simulation experiments, and field measurements, the research systematically explores the zonal linkage evolution mechanism of mining-induced depressurization gas migration and storage zones, together with the associated depressurization gas extraction technology. A flow regime determination equation, driven by the fracture expansion coefficient and permeability, is established on the basis of the fluid Reynolds number criterion. According to differences in gas flow states and medium morphology, the mining-induced fracture field is divided into five distinct zones: a high-permeability zone dominated by turbulent transport, a medium-to-high permeability zone with transitional flow as the secondary dominant region, a low-permeability zone featuring linear laminar flow with micro-permeability, an extremely low-permeability zone characterized by linear laminar flow in a locked state, and a zone of abrupt permeability change associated with gas enrichment. The dynamic evolution of depressurization gas migration and storage zones and their regional linkage mechanisms are clarified. On the basis of these findings, a dynamic targeted layout strategy for high-level boreholes is proposed that is consistent with the spatiotemporal evolution of the overburden permeability field. Field engineering practice shows that the optimized high-level borehole layout maintains the overall gas extraction rate at the drilling site stably above 70%, with a peak value of 93.7%, thereby ensuring safe and efficient mining of the working face. Full article