Search Results (84)

Balancing protection and development is essential for mitigating anthropogenic threats and achieving sustainable development in coastal regions. However, integrated spatial planning that links marine protected areas (MPAs) with developed spaces and incorporates land–sea coordination remains insufficiently explored—despite global frameworks such as the “Post-2020 Global Biodiversity Framework” advocating for such integration. In this study, we used Xiamen, a typical bay city in China, as an example, assessed its habitat suitability through the MaxEnt model, and determined its key development areas through hotspot analysis, aiming to coordinate protection and development, as well as land and marine utilization in coastal areas. The results indicate the following: (1) existing protected areas require adjustments; (2) multiple development hotspots overlap, while several cold spots with limited potential for functional development were identified; (3) prioritizing MPAs in decision-making led to an approximate 42.8% increase in MPA coverage in Xiamen. Overall, this study produced a comprehensive plan that integrates both ecological and social objectives. Full article

This study presents a comprehensive geospatial framework for assessing coastal vulnerability and ecosystem service distribution along the Greek coastline, one of the longest and most diverse in Europe. The framework integrates two complementary components: a Coastal Erosion Vulnerability Index applied to all identified beach units, and Coastal Flood Risk Indexes focused on low-lying and urbanized coastal segments. Both indices draw on harmonized, open-access European datasets to represent environmental, geomorphological, and socio-economic dimensions of risk. The Coastal Erosion Vulnerability Index is developed through a multi-criteria approach that combines indicators of physical erodibility, such as historical shoreline retreat, projected erosion under climate change, offshore wave power, and the cover of seagrass meadows, with socio-economic exposure metrics, including land use composition, population density, and beach-based recreational values. Inclusive accessibility for wheelchair users is also integrated to highlight equity-relevant aspects of coastal services. The Coastal Flood Risk Indexes identify flood-prone areas by simulating inundation through a novel point-based, computationally efficient geospatial method, which propagates water inland from coastal entry points using Extreme Sea Level (ESL) projections for future scenarios, overcoming the limitations of static ‘bathtub’ approaches. Together, the indices offer a spatially explicit, scalable framework to inform coastal zone management, climate adaptation planning, and the prioritization of nature-based solutions. By integrating vulnerability mapping with ecosystem service valuation, the framework supports evidence-based decision-making while aligning with key European policy goals for resilience and sustainable coastal development. Full article

This study presents a validated framework to quantify regional sea-level risk on U.S. coasts by (i) extracting trends and seasonality from satellite altimetry (ADT, GMSL), (ii) learning regional dynamical regimes via PCA-embedded KMeans on gridded ADT time series, and (iii) coupling these regimes with socioeconomic exposure (population, income, ocean-sector employment/GDP) and wetland submersion scoring. Relative to linear and ARIMA/SARIMA baselines, a sinusoid+trend fit and an LSTM forecaster reduce out-of-sample error (MAE/RMSE) across the North Atlantic, North Pacific, and Gulf of Mexico. The clustering separates high-variability coastal segments, and an interpretable submersion score integrates elevation quantiles and land cover to produce ranked adaptation priorities. Overall, the framework converts heterogeneous physical signals into decision-ready coastal risk tiers to support targeted defenses, zoning, and conservation planning. Full article

Against the backdrop of China’s “dual carbon” targets, the energy transition is accelerating. However, the expansion of onshore renewables is often constrained by land scarcity. Offshore areas thus present a promising alternative. In this study, high-resolution wind field data from 1995 to 2024 were generated using the WRF model driven by ERA5 reanalysis, enabling a 30-year spatiotemporal assessment of offshore wind power density (at 160 m hub height) and photovoltaic potential (PVP) across China’s four major seas—the Bohai Sea, Yellow Sea, East China Sea, and South China Sea. The results show clear spatial and seasonal patterns: solar PV potential decreases from south to north, with the South China Sea exhibiting the highest and most stable annual average PVP (16–18%) and summer peaks exceeding 25%. Wind energy resources are spatially heterogeneous; the East China Sea and Taiwan Strait are identified as the richest zones, where wind power density frequently reaches 800–1800 W/m² during autumn and winter. Importantly, a pronounced seasonal complementarity is observed: wind peaks in autumn/winter while solar peaks in spring/summer at representative coastal sites. This study provides, for the first time, a long-term, integrated assessment of both offshore wind and solar resources over all four Chinese seas, offering quantitative data and a scientific basis for differentiated marine energy planning, optimized siting, and the design of wind–solar hybrid systems. Full article

Dynamic task planning for heterogeneous platforms across land, sea, air, and space is essential for achieving integrated situational awareness, yet current systems suffer from limited spatiotemporal coverage and inefficient resource scheduling. To address these challenges, we propose a novel mission planning method that integrates spatiotemporal segmentation with Deep Reinforcement Learning (DRL). The approach establishes a multidimensional spatiotemporal decomposition model to break down complex observation scenarios into manageable subtasks, while incorporating a unified accessibility–visibility computation framework that accounts for Earth curvature, platform dynamics, and sensor constraints. Using a Spatio-Temporal Adaptive Scheduling Network (STAS-Net) algorithm optimized with a multi-objective reward function covering mission completion rate, temporal coordination, and residual detection capacity, the method enables intelligent coordination of heterogeneous platforms. Experimental results across small-, medium-, and large-scale scenarios demonstrate that the proposed framework consistently achieves high target coverage (up to 98.4% in small-scale and 89.7% in large-scale tasks), with a reduction in coverage loss that is only about half of that exhibited by greedy and genetic algorithms as task scale expands. Moreover, STAS-Net maintains low planning time (as low as 9.5 s in small-scale and only 18.3 s in large-scale scenarios) and high resource utilization (reaching 86.8% under large-scale settings), substantially outperforming both baseline methods in scalability and scheduling efficiency. The framework not only establishes a solid theoretical foundation but also provides a practical and feasible solution for enhancing the overall performance of multi-platform cooperative observation systems. Full article

Coastal cities face escalating flood risk under sea-level rise, yet landscape-based adaptation strategies often remain speculative and weakly connected to the accessibility and economic constraints that shape sustainable urban development. This study developed a modeling-to-design framework that translates coupled climate and land-use projections into implementable landscape interventions, through planning-level spatial allocation, using Dalian, China as a case study under “middle of the road” (SSP2-4.5) climate conditions. The framework integrates the Land-use Evolution and Assessment Model (LEAM) with connected-bathtub flood modeling to evaluate whether strategic landscape design can redirect development away from flood-prone zones while accommodating projected growth and maintaining accessibility to employment and services. Interventions—protective wetland restoration (810 km²) and blue–green corridors (8 km²)—derived from a meta-synthesis of implemented coastal projects were operationalized as LEAM spatial constraints. Our results show that residential development can be redirected away from coastal risk with 100% demand satisfaction and elimination of moderate-risk allocations. Cropland demand was fully accommodated. In contrast, commercial development experienced 99.8% reduction under strict coastal protection, reflecting locational dependence on port-adjacent sites. This modeling-to-design framework offers a transferable approach to quantifying where landscape interventions succeed, where they face barriers, and where complementary measures are required, supporting decision-making that balances environmental protection, economic function, and social accessibility in sustainable coastal development. Full article

Existing research on tourism spatial planning primarily focuses on different political and economic systems (PESs)—but most often within capitalist democracies. However, there is a lack of research examining how frequent changes in PESs (capitalism, socialism and recapitalism) act as critical points, as they affect tourism spatial planning legislation, land use and spatial management. By analysing the spatiotemporal evolution of the Kupari tourist zone in Croatia (1880–2024), we investigate how PES changes act as critical turning points that shape tourism spatial planning and administrative practices. Key results reveal that tourism recovery and resilience are closely linked to the stability of PESs. Frequent PES changes (1) reduce the overall resilience of tourism and its institutions, (2) lead to recurring changes in tourism spatial planning legislation (e.g., ownership and land use) and (3) disrupt the positive correlation between space and tourism development. Frequent changes in PESs are reflected in legislation, as well as in challenges of compromise for issues closely related to tourism and spatial management. Only a stable PES can enable continuous monitoring of legislation and its spatial consequences in real time. An integrated methodology for monitoring legislation, together with a framework for spatial management, offers practical solutions for the sustainable management of tourist areas. These findings provide both scientific evidence and practical strategies for better harmonization of legislation with the resilience of tourism spatial planning on the eastern coast of the Adriatic Sea. Full article

In parallel with achieving its 2040 Vision toward establishing smart cities, this study aims to pinpoint promising locations for future urban development in Oman, which reflect the unique physical attributes of the country, its renewable energy resources, and socio-economic conditions. To meet this goal at the national scale, the research relied on the following key factors: topography, diurnal temperature range, relative humidity, dust concentrations, wind speed, solar radiation, and access to electricity. These inputs were derived from remote sensing sources. A multi-layer spatial analysis was carried out within a Geographical Information System (GIS) environment to identify high-priority locations for future and sustainable urban growth. All parameters were assigned equal weights, particularly when applying a standard approach to produce a baseline suitability model at the national scale and to avoid subjective bias in the overall suitability assessment. Results showed that 2.1% of Oman’s land shows strong potential for sustainable urban development. Specifically, three locations stand out with the highest occurring along the southern section of the Arabian Sea between Al Jazir and Ad-Duqum. The other two locations occur at Salalah in the south and Sohar in the north. The promising locations occur proximate to major harbors and can benefit from existing infrastructure, including airports, highways, educational and medical services. Suggested locations also align well with earlier relevant studies. This study demonstrates the capabilities of integrating remotely sensed data with geospatial analysis in urban planning and development. Results are expected to help policymakers and planners to prioritize national-scale urban development. Full article

Heat extremes or heatwave events have significantly impacted socioeconomic activities and ecological systems, causing serious health issues and increased mortality rates in Pakistan over the past few decades. This study investigates the relationship between heat extremes in the northern Indian Ocean’s sea surface temperature (SST) and atmospheric temperature over Land (ATL) in Pakistan, and their connection to the Niño 3.4 Index, for monthly (March–August) and seasonal (spring and summer) basis from 1979 to 2015. Results show that SST has a higher frequency of heat extreme anomalies over different stretches of days than ATL. On a seasonal scale, heat extremes in ATL showed a significant correlation with SST, while the relationship was insignificant on a monthly basis. Both ATL and SST exhibited strong associations with the Niño 3.4 Index for land and ocean. These findings suggest that large-scale ocean-atmosphere interactions, particularly El Niño Southern Oscillation (ENSO), play a key role in modulating heat extremes in the region. The results of this study support SDGs by improving adaptive capacity and resilience on health, hunger, and climate by guiding policymakers in mitigating heat extremes. Integrating the findings of this study into national and provincial heat extreme plans may facilitate timely resource allocation and adaptation strategies in one of the world’s most climate-vulnerable regions. Full article

Across the Baltic Sea region, areas situated in climate-sensitive water zones are increasingly exposed to environmental and socio-economic challenges. Gdańsk, Poland, is a prominent example where the rising threat of climate-related hazards, particularly connected with flooding, coincides with growing demand for resilient and adaptive housing solutions. Located in the Vistula Delta, the city’s vulnerability is heightened by its low-lying terrain, polder-based land systems, and extensive waterfronts. These geographic conditions underscore the urgent need for flexible, climate-responsive design strategies that support long-term adaptation while safeguarding the urban fabric and the well-being of local communities. This study provides evidence-based guidance for adaptive housing solutions tailored to Gdańsk’s waterfronts. It draws on successful architectural and urban interventions across the Baltic Sea region, selected for their environmental, social, and cultural relevance, to inform development approaches that strengthen resilience and social cohesion. To achieve this, an exploratory case study methodology was employed, supported by desk research and qualitative content analysis of strategic planning documents, academic literature, and project reports. A structured five-step framework, comprising project identification, document selection, qualitative assessment, data extraction, and analysis, was applied to examine three adaptive housing projects: Hammarby Sjöstad (Stockholm), Kalasataman Huvilat (Helsinki), and Urban Rigger (Copenhagen). Findings indicate measurable differences across nine sustainability indicators (1–5 scale): Hammarby Sjöstad excels in environmental integration (5/5 in carbon reduction and renewable energy), Kalasataman Huvilat demonstrates strong modular and human-scaled adaptability (3–5/5 across social and housing flexibility), and Urban Rigger leads in climate adaptability and material efficiency (4–5/5). Key adaptive measures include flexible spatial design, integrated environmental management, and community engagement. The study concludes with practical recommendations for local planning guidelines. The guidelines developed through the Gdańsk case study show strong potential for broader application in cities facing similar challenges. Although rooted in Gdańsk’s specific conditions, the model’s principles are transferable and adaptable, making the framework relevant to water sensitivity, flexible housing, and inclusive, resilient urban strategies. It offers transversal value to both urban scholars and practitioners in planning, policy, and community development. Full article

This study reconstructs and projects relative sea-level change (RSLC) along Chesapeake Bay, a global hotspot for sea-level rise, from 1900 to 2100 by statistically extrapolating observed tide gauge trends, rather than employing climate model-based scenarios. The approach integrates global mean sea-level rise (GMSLR), regional sea-level rise (RSLR), and local land subsidence (LS) to evaluate both past and future behavior. Tide gauge data reveal that Chesapeake Bay’s sea level has accelerated at 0.099 ± 0.013 mm/year² since 1992, with a linear rate of 1.26 mm/year since 1900, slightly outpacing global averages. LS, primarily driven by glacial isostatic adjustment (GIA) and sediment compaction, has been the dominant contributor to RSLC since the early 20th century, accounting for up to 71% of the RSLC prior to 1992 across 15 tide gauge stations. However, with GMSLR accelerating at 0.120 ± 0.025 mm/year², the relative contribution of LS to RSLC is projected to decline to 31–43% by 2100. The reconstructed RSLC for the 20th century ranges between 32 and 44 cm, while extrapolated projections for the 21st century indicate a further increase of 53–99 cm. By 2100, GMSLR is expected to contribute to 60–70% of total RSLC. Spatial variability in RSLC across 15 tide gauge stations reflects differing geological conditions and anthropogenic influences such as groundwater withdrawal and construction-induced subsidence. These findings highlight the critical need for adaptive strategies to mitigate the impact of rising sea levels on coastal communities and infrastructure in the Chesapeake Bay region. Continued monitoring, improved modeling, and targeted resilience planning are essential to address the accelerating threats posed by sea-level rise and to ensure the sustainability of vulnerable coastal areas. Full article

The Chesapeake Bay (CB) region faces significant risks from relative sea-level change (RSLC), driven by global mean sea-level rise (GMSLR), regional sea-level rise (RSLR), and local land subsidence (LS). This study introduces a methodology to decipher RSLC trends in the CB area by integrating these components. We develop trend equations spanning 1900–2100, incorporating acceleration for GMSLR and RSLR since 1992, with linear LS estimation using tide gauge, satellite altimetry, and InSAR data. Our approach employs dynamic RSLC equations, Maclaurin series expansions, and inverse simulations to project RSLC trends through 2100. Stable RSLC rates require over 122 years of data for reliable linear trend estimation, with the Baltimore tide gauge providing the necessary long-term dataset. Similarity in monthly mean sea-level variations within a coastal region enables a new method to identify LS from short-term tide gauge data by correlating it with corresponding long-term data at Baltimore. LS is categorized into bedrock-surface subsidence (BSS) and compaction subsidence (CS), with methods proposed to map BSS contours and estimate CS. CS is further classified into primary consolidation, secondary consolidation, construction-induced, and negative subsidence to determine specific compaction types. The projection model highlights the dominant influence of GMSLR acceleration since 1992, with local LS and RSLR influenced by ocean circulation, density changes, and gravitational, rotational, and deformational (GRD) effects. This integrated approach enhances understanding and predictive reliability for RSLC trends, supporting resilience planning and infrastructure adaptation in coastal CB communities. Full article

China’s sinuous coastline is increasingly threatened by land subsidence driven by complex geological conditions and intensive human activity. Using year-round Sentinel-1A acquisitions for 2023 and SBAS-InSAR processing, we generated the first millimetre-resolution subsidence velocity field covering the 50 km coastal buffer of mainland China. We elucidated subsidence patterns and their drivers and quantified the associated socio-economic risks by integrating 1 km GDP and population data. Our analysis shows that ~55.77% of the coastal zone is subsiding, exposing 97.42 million residents and CNY 16.41 billion of GDP. Four hotspots—Laizhou Bay, northern Jiangsu, the Yangtze River Delta (YRD) and the Pearl River Delta (PRD)—exhibit the most pronounced deformation. Over-extraction of groundwater is identified as the primary driver. The 15 m resolution subsidence product provides an up-to-date, high-precision dataset that effectively supports sustainable development research in coastal hazard prevention, territorial spatial planning, and sea-level rise studies. Full article

Protection of coastal cultural heritage is among the most urgent global priorities, as these sites face increasing threats from climate change, sea level rise, and human activity. This study emphasises the value of innovative geospatial tools and data ecosystems for timely risk assessment. The role of land administration systems, geospatial documentation of coastal cultural heritage sites, and the adoption of innovative techniques that combine various methodologies is crucial for timely action. The coastal management infrastructure in Greece is presented, outlining the key public authorities and national legislation, as well as the land administration and geospatial ecosystems and the various available geospatial ecosystems. We profile the Hellenic Cadastre and the Hellenic Archaeological Cadastre along with open geospatial resources, and introduce TRIQUETRA Decision Support System (DSS), produced through the EU’s Horizon project, and a Digital Twin methodology for hazard identification, quantification, and mitigation. Particular emphasis is given to the role of Digital Twin technology, which acts as a continuously updated virtual replica of coastal cultural heritage sites, integrating heterogeneous geospatial datasets such as cadastral information, photogrammetric 3D models, climate projections, and hazard simulations, allowing for stakeholders to test future scenarios of sea level rise, flooding, and erosion, offering an advanced tool for resilience planning. The approach is validated at the coastal archaeological site of Aegina Kolona, where a UAV-based SfM-MVS survey produced using high-resolution photogrammetric outputs, including a dense point cloud exceeding 60 million points, a 5 cm resolution Digital Surface Model, high-resolution orthomosaics with a ground sampling distance of 1 cm and 2.5 cm, and a textured 3D model using more than 6000 nadir and oblique images. These products provided a geospatial infrastructure for flood risk assessment under extreme rainfall events, following a multi-scale hydrologic–hydraulic modelling framework. Island-scale simulations using a 5 m Digital Elevation Model (DEM) were coupled with site-scale modelling based on the high-resolution UAV-derived DEM, allowing for the nested evaluation of water flow, inundation extents, and velocity patterns. This approach revealed spatially variable flood impacts on individual structures, highlighted the sensitivity of the results to watershed delineation and model resolution, and identified critical intervention windows for temporary protection measures. We conclude that integrating land administration systems, open geospatial data, and Digital Twin technology provides a practical pathway to proactive and efficient management, increasing resilience for coastal heritage against climate change threats. Full article

This paper presents the development of a high-resolution composite index to monitor and quantify climate-related risks across Italy. The country’s complex climatic variability, extensive coastline, and low insurance penetration highlight the urgent need for robust, locally calibrated tools to bridge the climate protection gap. Building on the methodological framework of existing actuarial climate indices, previously adapted for France and the Iberian Peninsula, the index integrates six standardised indicators capturing warm and cool temperature extremes, heavy precipitation intensity, dry spell duration, high wind frequency, and sea level change. It leverages hourly ERA5-Land reanalysis data and monthly sea level observations from tide gauges. Results show a clear upward trend in climate anomalies, with regional and seasonal differentiation. Among all components, sea level is most strongly correlated with the composite index, underscoring Italy’s vulnerability to marine-related risks. Comparative analysis with European indices confirms both the robustness and specificity of the Italian exposure profile, reinforcing the need for tailored risk metrics. The index can support innovative risk transfer mechanisms, including climate-related insurance, regulatory stress testing, and resilience planning. Combining scientific rigour with operational relevance, it offers a consistent, transparent, and policy-relevant tool for managing climate risk in Italy and contributing to harmonised European frameworks. Full article