Search Results (281)

Accurate coastline extraction in muddy and macro-tidal environments is challenging due to tidal variability and complex coastal surfaces. The Jiangsu coast of China, characterized by extensive tidal flats, silty coastlines, and strong land–sea interactions, provides an ideal case for long-term coastline change analysis. This study investigates the spatiotemporal evolution of the Jiangsu coastline from 2018 to 2025 using multi-temporal Sentinel-2 imagery. A tide-independent coastline extraction framework was developed by integrating the Normalized Difference Water Index, Modified Normalized Difference Water Index, and Normalized Difference Vegetation Index for different coastal environments. An annual maximum spectral index composite was applied to approximate the highest water-level conditions without explicit tidal correction. Coastline dynamics were quantified using fractal dimension analysis and a transect-based method. The extracted coastlines yielded an average Root Mean Square Error (RMSE) of 13.14 m and an average Mean Absolute Distance Error (MADE) of 9.39 m. Results show that the total coastline length varied within 5% during the study period, with a maximum of 1079.84 km in 2022 and a minimum of 1004.99 km in 2018. Coastline change was dominated by erosion, accounting for 56.21% of the total coastline length. Land cover analysis revealed that accretion mainly occurred near river mouths and aquaculture areas, whereas erosion was more common at interfaces between forested land and engineered coastlines. The proposed framework provides an efficient and consistent approach for short-term coastline monitoring in muddy coastal environments. Full article

Continuous dynamic monitoring of coastline changes is essential for revealing the evolutionary laws and spatiotemporal characteristics of coastal systems. In this study, we employed AlphaEarth Foundations (AEF) data and Sentinel-2 imagery to investigate coastline and land use changes in the Pearl River Estuary (PRE) region over the period 2017–2023. The Random Forest (RF) algorithm was adopted to extract coastlines and classify coastal land-use types, after which their spatiotemporal evolution was quantitatively analyzed. The results demonstrate that the classification performance of AEF data is significantly better than that of Sentinel-2 imagery, with the average overall accuracy and Kappa coefficient exceeding 92% and 89%, respectively. The PRE coastline shows an evolutionary pattern of “overall contraction accompanied by regional differentiation”: its total length first increased and then decreased, peaking at 1029.05 km in 2019, representing a cumulative net reduction of 7.54 km over the 2017–2023 period. Meanwhile, land use expansion driven by reclamation resulted in a cumulative net increase of 25.26 km². Aquaculture ponds (AP) constitute the dominant type of newly reclaimed land, accounting for more than 50%, while the expansion of impervious surface (IS) accounts for 24.52%. This study provides novel insights and a scientific basis for the refined management of coastlines, sustainable land use planning, and coastal-marine ecological protection in the Pearl River Estuary and similar regions worldwide. Full article

PM2.5 and near-surface O₃ compound pollution is a major challenge for further air quality improvement in the Yangtze River Delta (YRD). Despite research on the chemical coupling mechanisms and concentration co-variation between PM2.5 and O₃, the directional linkages of compound pollution events among cities and the network mechanisms underlying their formation remain unclear. Here, we identified PM2.5–O₃ compound pollution events for 41 YRD cities from 2015 to 2024 using city-year-specific P80 dual-threshold criteria. We then constructed annual directed synchronization networks based on event-leading relationships and used temporal exponential random graph models to identify the formation mechanisms of significant leading ties. PM2.5–O₃ compound pollution events in the YRD generally decreased during 2015–2024, with characteristics shifting from high frequency, persistence, and strong intercity linkage in the early stage to lower frequency, weaker intensity, and continued episodic fluctuations. Directed event networks exhibited a clear stage-dependent evolution: network density, total edge weight, reciprocity, and local closure were relatively high during 2015–2018, networks became markedly sparse during 2020–2022, and a partial rebound occurred after 2023. Spatial backbone analysis indicated reorganization of the dominant linkage structure, shifting from the Shanghai–southern Jiangsu–northern Zhejiang coastal core toward the northern Jiangsu, Anhui, and interprovincial corridors. Key node analysis further revealed a clear functional differentiation among cities, with some cities acting as potential leading sources, some as receiving nodes, and several non-traditional core cities serving as cross-regional bridges. Significant leading ties were jointly shaped by reciprocity, local closures, temporal memory, economic development, industrial structure, and digital governance. Therefore, as well as a problem of co-occurrence, PM2.5–O₃ compound pollution in the YRD is a cross-city event-network process characterized by directionality, stage-dependent evolution, and differentiated urban roles. This study provides empirical evidence for dynamic joint prevention and control based on event linkages, urban roles, and cross-city coordination. Full article

Understanding sea surface temperature (SST) variability is essential for assessing climate-driven changes in semi-enclosed basins such as the Black Sea. This study investigates SST variability in the western Black Sea over 2003–2024 using MODIS Aqua nighttime SST observations. Annual mean SST time series were constructed for coastal, shelf, and open-sea subregions and analysed using linear regression, ARIMA modelling, segmented regression, and spectral methods. SST exhibits a persistent warming signal across all subregions, with an overall increase of ~2.0–2.5 °C and a mean trend of 0.64 ± 0.08 °C decade⁻¹. Warming is spatially heterogeneous, with stronger trends in coastal and shelf regions, indicating a pronounced cross-shelf gradient. Temporal evolution reveals a multi-phase structure, with breakpoints around 2006–2008 and ~2022 marking shifts in warming intensity. Extreme anomalies include basin-wide cooling in 2017 and a sustained warming episode during 2019–2020. Statistical analyses indicate that SST variability is dominated by short-term persistence, while the influence of the North Atlantic Oscillation (NAO) is weak at the annual scale. In addition to the warming trend, SST variability undergoes a systematic reorganization, with variability remaining pronounced and spatially differentiated, particularly in coastal and shelf regions. Near-term projections further suggest that SST evolution may be moderated by internal variability, resulting in limited net change relative to recent peak conditions. Overall, SST variability reflects the combined effects of basin-scale warming, stratification, and regional circulation, indicating a transition toward a more stratified and dynamically variable system with implications for regional climate and marine ecosystems. Full article

This study investigates ecosystem service valuation on Zhoushan Island. Based on Landsat remote sensing images for 2000, 2010, and 2020 acquired through the Google Earth Engine (GEE) platform, six land use types are extracted using the Random Forest method. By integrating land use dynamic degree, transfer matrix, ecosystem service value (ESV) accounting, and five-level land–sea gradient zoning approaches, this study systematically analyzes the spatiotemporal evolution of land use and its effects on ESV over the 20-year period, and reveals the spatial differentiation pattern of land use change and ESV gains and losses along the land–sea gradient. The results indicate that from 2000 to 2020, water bodies and cultivated land on Zhoushan Island experienced continuous decline while construction land expanded rapidly, driven by policy regulation, urbanization, and industrial transformation. Localized coastal areas exhibited a typical chain conversion process of “water body → bare land → construction land,” which is closely associated with reclamation and land reclamation activities. Regional ESV declined continuously, reaching only 56.7% of its 2000 level by 2020, with regulating and provisioning services exhibiting the most pronounced deterioration. Analysis of the ESV net transfer matrix indicates that the primary driver of ESV decline was the large-scale conversion of high-value water bodies to low-value construction land and bare land, the magnitude of which far exceeded the positive ecological gains generated by all other land use conversions. The reduction in cultivated land area, compounded by adjustments in cropping structure, has placed sustained pressure on regional food security, and policy responses have lagged considerably behind the pace of ecological degradation. In terms of spatial differentiation, both the intensity of land use change and ESV loss exhibited a gradient pattern that decreases progressively from the coastal zone moving inland. Zone 1 and Zone 2 in the nearshore area together accounted for approximately 80% of total ESV loss, whereas Zone 4 and Zone 5 maintained relatively stable land use structures and ecological support capacity, owing to higher forestland coverage. Spearman’s rank correlation analysis confirmed a statistically significant monotonically decreasing relationship between land use dynamic degree and coastal distance. Policy regulation served as the primary driver of regional land use pattern evolution: early sea reclamation policies facilitated rapid land transformation along the coastline, while subsequent tightening of controls effectively curbed disorderly expansion. Full article

As coastal communities face escalating climate risks driven by climate change and biodiversity loss, integrating mangrove ecosystems into sustainability-oriented governance frameworks spanning ecological conservation, climate adaptation, and natural capital accounting has become a global priority. However, quantifying their protection values based on spatiotemporal shoreline dynamics under extreme disturbance remains challenging. Focusing on Dongzhai Harbor (China), this study integrates multi-temporal remote sensing (2010–2021), shoreline evolution analysis, and the Replacement Cost Method to assess ecosystem resilience against Super Typhoon Rammasun in 2014. Results show mangroves exhibited substantial post-disturbance resilience, with only 6.10% area loss following Typhoon Rammasun and 46% natural recovery within six years. Bootstrap confidence intervals for the mangrove-shoreline association overlapped zero across all three temporal periods, indicating that the observational data do not support a statistically confirmed causal protection effect at the landscape scale. This finding underscores that spatially co-occurring ecosystem services do not automatically imply causation, reinforcing the need for empirically grounded valuation in sustainable land-use planning. Because mangroves naturally establish in sheltered environments, the observed spatial overlap between mangroves and the shoreline cannot be interpreted as direct evidence of causal shoreline stabilization. Based on this framework, the potential protection value reached 907.65 × 10⁴ CNY yr⁻¹ across 32.57 km of weighted coastline aligned with mangroves. Notably, erosional segments contributed 50.5% of this value despite comprising only 27.3% of the length, indicating that the replacement-cost estimate is concentrated in erosional segments under the assumed parameters. While acknowledging the need for local biophysical validation and uncertainty analysis in scaling, these findings support integrating dynamic nature-based solutions into territorial planning and Gross Ecosystem Product accounting. The resulting valuation framework offers a replicable pathway for advancing multi-dimensional sustainability encompassing climate-adaptive coastal governance, natural capital integration, and evidence-based coastal spatial planning. Full article

Aquaculture ponds and salt pans represent the dominant forms of coastal production spaces along the Jiangsu coast, China; however, their long-term co-evolution and mutual transitions remain poorly understood. To bridge this gap, this study developed a 40-year (1985–2025) spatiotemporal dataset of these land covers leveraging Landsat imagery via the Google Earth Engine (GEE) platform. We established an integrated classification workflow encompassing single-scene water mask extraction, annual Modified Normalized Difference Water Index (MNDWI)-based water frequency statistics, Otsu automatic thresholding, connected-component labeling, and the masking of natural water bodies. The resulting dataset demonstrated high reliability, achieving overall accuracies (OA) ranging from 92.32% to 94.15% and an average Kappa coefficient of 0.89. Based on multi-metric analyses of area dynamics, annual change rates, and transition patterns, we identified three distinct co-evolutionary stages: simultaneous expansion (1985–1995), internal reorganization (1995–2015), and overall contraction (2015–2025). Notably, transitions between the two production spaces were highly asymmetric over the 40-year period; the area converted from salt pans to aquaculture ponds was approximately 15.23 times greater than the reverse conversion. Furthermore, their distribution exhibited strong spatial heterogeneity at the county level, underscoring the critical role of localized coastal planning in balancing economic production and wetland conservation. Ultimately, this work provides foundational data and methodological insights for long-term coastal ecological monitoring and sustainable production space management. Full article

Continuous ground-based microwave (MW) measurements with the RPG-HATPRO radiometer at the observational site of St. Petersburg State University located near the coastline of the Gulf of Finland have provided a large amount of data on the cloud liquid water path (LWP) of non-raining clouds. The 12-year (2013–2024) time series of the LWP values has been analysed and the diurnal evolution of the LWP has been assessed for each month of the year. The calculations have been made for the LWP in the range 0–0.4 kg m⁻² using different sampling subsets that include the so-called true and virtual LWP values. True LWP values correspond to measurements with clouds in the field of view of the radiometer, whereas virtual LWP values correspond to measurements with clouds or with clear sky in the field of view of the instrument and, therefore, virtual values can be zero (in clear sky cases). Based on the correlation analysis, time periods characterised by similar meteorological conditions and suitable for assessing the daily dynamics of LWP were identified. The LWP diurnal cycles in December, January, and February demonstrated a similar pattern with a maximum around local astronomical noon and with a minimum around midnight. For the remaining months except March and June, the maximum LWP is observed in the early morning and the minimum is observed in the afternoon. This cycle is characteristic of marine stratocumulus clouds. The diurnal cycles of the LWP in March and June, peaking in the afternoon and morning, respectively, are typical of convective continental clouds. Thus, the LWP diurnal cycle in the coastal zone of the Gulf of Finland may have characteristics of both marine and continental clouds. Parameters of the two-mode sinusoidal approximation of the diurnal cycle of the LWP in different seasons are presented. Full article

Coastal basins are systems highly susceptible to flooding and erosion, processes that intensify during extreme cyclonic events. This study aims to develop an integrated physical–geographic framework to characterize the geomorphological and multi-hazard dynamics of the La Sabana River basin in Acapulco, Guerrero, in southeastern Mexico. The methodology integrates the analysis of natural and anthropogenic landscape components, 19 morphometric indicators, and Principal Component Analysis (PCA) at the sub-basin scale. The results reveal a high drainage network density (3.8–5.4 km/km²) and short concentration times (0.98–2.75 h), indicating a rapid hydrological response and high susceptibility to flash floods and active erosion. Six critical sub-basins with concentration times ≤ 1.5 h have been identified, spatially coinciding with areas of high anthropogenic exposure. The hypsometric index values (0.04–0.388) indicate advanced geomorphological evolution in most sub-basins. Principal component analysis (PCA) explained 65.8% of the total variance in the first two components: component 1 (52.7%) is linked to basin size and drainage network organization, and component 2 (13.1%) is associated with basin shape. The findings of this research have provided a spatially explicit, robust, and replicable framework that helps strengthen risk governance and guide land-use planning in tropical coastal basins exposed to hydrometeorological hazards. Full article

Human modification of tidal embayments, estuaries, and deltas through polders, dykes, and embankments has profoundly altered sediment dynamics and coastal morphology worldwide. Mont-Saint-Michel Bay (northwestern France) exemplifies a macrotidal system affected by large-scale land reclamation, accelerated infilling, rapid saltmarsh expansion, and progressive loss of the insular character of the World Heritage abbey. To restore its maritime setting, a large-scale restoration programme initiated in the 1990s combined engineering measures with nature-based management, including embankment removal, managed retreat, and controlled hydraulic flushing. Future morphodynamic evolution was initially assessed using a movable-bed physical model complemented by numerical simulations. Here, a 22-year LiDAR dataset is used to quantify post-restoration topographic changes and sediment budgets, and evaluate model performance. The results show enhanced erosion and deepening of tidal flats around Mont-Saint-Michel, indicating effective sediment export, together with spatial redistribution of salt marshes that maintained the overall ecological value of the bay. Discrepancies between model predictions and field observations reflect both the difficulty of reproducing long-term channel migration variability and evolving hydro-meteorological forcing conditions, as well as differences between the initially modelled restoration scheme and the engineering works ultimately implemented. This study provides a rare multi-decadal comparison between pre-project morphodynamic forecasts and post-restoration observations. The results highlight both the potential and the limitations of long-term morphodynamic forecasting in non-stationary tidal systems undergoing anthropogenic modifications and climate-driven environmental change, emphasising the importance of long-term monitoring and adaptive management strategies. Full article

Against the backdrop of the global green development concept, scientifically assessing the level of urban green transformation (UGT) in China and revealing its spatiotemporal evolution are critical for promoting high-quality development in the country. We constructed an evaluation index system based on four dimensions: economic, social, resource, and environmental transformation. Using the entropy method, we determined the scores for a comprehensive green transformation development index for 285 prefecture-level-and-above cities in China from 2000 to 2023. We further employed kernel density estimation, standard deviation ellipses, the Dagum Gini coefficient, and convergence models to systematically examine the dynamic evolution, regional disparities, and convergence characteristics pertaining to UGT. The key findings are as follows: (1) There is a steady upward trend in the overall level of UGT in China, with intra-regional differences gradually converging. However, a “better–getting-better” differentiation pattern exists, while there is no observable multi-peak polarization. (2) Based on the UGT level, cities in China can be classified into four types: leading areas, potential areas, catching-up areas, and lagging areas. Spatially, a gradient pattern consisting of “high in coastal areas and low in inland areas” was identified. The overall centroid of green transformation has shifted southward, with a northeast–southwest distribution direction. The spatial agglomeration pattern exhibits a transition from dispersion to concentration. (3) There is a decreasing trend in overall disparity among the eight major economic regions, with inter-regional disparity being the primary source, while intra-regional disparity in coastal areas has increased. (4) Regarding convergence characteristics, σ-convergence can be observed in all economic regions except the Eastern Coastal, Southern Coastal, and Middle Yangtze River economic regions. Both absolute β-convergence and conditional β-convergence were found for China overall and its eight comprehensive economic regions, with the highest convergence speed in the Northeast region and the lowest in the Middle Yangtze River region. Furthermore, spatial absolute β-convergence and conditional β-convergence are also present, indicating strong spatial dependence among cities. This study provides empirical evidence and policy references for promoting UGT and optimizing regional development layouts in China. Full article

To mitigate large-scale blackout risks in urban distribution systems under typhoon-induced extreme weather and to reduce post-disaster restoration costs, this study proposes a resilience-oriented spatiotemporal co-optimization framework integrating transportation networks, power grids, and distributed energy resources. First, a city-scale typhoon spatiotemporal model is established, integrating static wind field, dynamic evolution, and trajectory-based mobility with urban-geometry-driven wind speed correction to characterize the spatiotemporal progression of extreme wind hazards. Second, the time-varying failure rates of distribution network components are quantified by explicitly accounting for network topology correlations, while the spatiotemporal dispatchability and output characteristics of distributed resources under disaster conditions are systematically modeled. Third, a pre-disaster proactive deployment model is formulated to minimize load curtailment costs and resource allocation expenditures. The model integrates active network reconfiguration with coordinated placement of distributed generation (DG) and mobile energy storage systems (MESSs), enabling resilience-enhancing pre-positioning strategies. Subsequently, a post-disaster restoration scheduling model is developed with the objective of minimizing unserved load. By embedding traffic flow constraints and optimal path computation under disrupted transportation conditions, the proposed framework realizes spatiotemporal coordination among MESSs, DG, and electric vehicles (EVs), thereby accelerating system-level recovery. Finally, the effectiveness of the proposed strategy is validated on a 51-node urban distribution system located in eastern coastal China, demonstrating significant improvements in restoration performance and resilience enhancement. Full article

Understanding the spatiotemporal formation mechanisms of built cultural heritage is essential to interpreting regional cultural landscapes and informing differentiated conservation strategies. Using Fujian Province, China, as a representative mountain–sea transitional region, this study constructs a province-scale, multi-category, and dynamically oriented analytical framework to investigate the temporal evolution, spatial structure, and driving mechanisms of immovable cultural relics. Based on a georeferenced dataset of 940 immovable cultural relics, textual historical records were standardized into continuous temporal variables and integrated with GIS-based kernel density estimation, spatial autocorrelation analysis, distance-to-coast modeling, and category co-occurrence analysis. The results reveal a pronounced temporal concentration in the Ming–Qing and modern periods, with a primary formation peak during the Qing Dynasty and a secondary peak in the early 20th century driven by modern heritage. Spatially, relics exhibit significant positive spatial autocorrelation (Global Moran’s I = 0.375, p < 0.001) and form a structured dual-core pattern, consisting of a persistent coastal heritage belt and a distinct inland modern core centered in western Fujian. More than 75% of relics are located within 110 km of the coastline, confirming strong maritime orientation, while regression analysis reveals that this inland shift is primarily driven by the Modern Era rather than representing a continuous long-term trend. Category-level correlation analysis further demonstrates a clear spatial decoupling between traditional heritage and modern sites, indicating fundamentally different locational logics. Synthesizing these findings, this study proposes a dual-core driven model under a mountain–sea geographical framework, in which a path-dependent, economically reinforced coastal core coexists with a historically contingent, politically driven inland core. The results advance quantitative understanding of how multiple cultural logics, operating across different temporal scales, jointly shape complex regional heritage systems and provide a transferable framework for heritage analysis and spatially differentiated conservation planning. Full article

Accurate measurement of atmospheric temperature profiles in the mesopause region is crucial for understanding the atmospheric dynamics and climate processes. To address this challenge, a sodium Doppler lidar based on the resonance fluorescence scattering mechanism was recently developed to precisely detect atmospheric temperatures in the mesopause region in Qingdao (36.1°N, 120.1°E), China. For the first time, high-resolution observations of atmospheric temperature in the mesopause region (80–105 km) were achieved by the self-developed Na Doppler lidar in Qingdao under the complex atmospheric conditions of the mid-latitude coastal zone. A systematic cross-validation between the self-developed lidar and SABER satellite observations was conducted, and the temperature bias between the two detection methods in the mesopause region and its altitude-dependent characteristics were quantitatively assessed. The temperature profiles measured by lidar exhibited good agreement when compared with the satellite data yielding estimations of RMSE and mean absolute deviation of 9.2 K and 7.3 K, respectively, from 80 km to 100 km altitudes. A correlation analysis conducted between the lidar temperature data and satellite data showed that the closer the satellite passed over Qingdao, the better the correlation demonstrated by the data. The correlation coefficient of the closer comparison data can reach 0.86, which means that the self-developed lidar system in Qingdao has a good ability to detect temperature profiles in the middle and upper atmosphere. The nocturnal evolution details and short-period fluctuations of the temperature field in the mesopause region over Qingdao were observed, revealing the local temperature structural characteristics under the complex atmospheric conditions at the land–sea interface in the Qingdao area. Full article

This study analyzes the evolution of rural welfare vulnerability among agricultural households in Peru under the influence of extreme climate events, particularly those associated with the El Niño–Southern Oscillation. The research employs a Socio-Climatic Vulnerability Index (SCVI) constructed from microdata of the National Household Survey (ENAHO) covering the period 2000–2018. Using a longitudinal and territorial perspective, the study evaluates how climate shocks affect household welfare dynamics across Peru’s major geographic regions. The results show that extreme weather events systematically increase rural vulnerability in the years they occur, followed by partial recovery in subsequent periods, indicating temporary but recurrent welfare disruptions. Significant regional heterogeneity is observed. Coastal departments exhibit increasing vulnerability linked to hydro-meteorological exposure and rapid territorial expansion. The Andean region shows the highest and most volatile vulnerability levels due to geographic isolation, infrastructure constraints, and persistent socioeconomic inequalities. Amazonian regions present relatively lower initial vulnerability but display gradual increases associated with climate variability and limited connectivity. Decomposition of the SCVI reveals that improvements in demographic and educational conditions contribute positively to resilience, whereas the productive-economic dimension remains highly sensitive to climatic shocks. Although agricultural households demonstrate adaptive responses and coping strategies, structural gaps hinder full welfare recovery. These findings highlight the need for territorially differentiated climate adaptation policies that strengthen human capital, diversify rural livelihoods, and improve institutional support to enhance long-term resilience in vulnerable rural communities. Full article