Search Results (56)

This study evaluated the performance of the operational GK2A (GEO-KOMPSAT-2A) fog detection algorithm (GK2A_FDA) using ground-based visibility meter data from 176 stations across South Korea from 2021 to 2023. According to the verification method using the nearest pixel and 3 × 3 neighborhood pixel approaches to the visibility meter, the 3-year average probability of detection (POD) is 0.59 and 0.70, the false alarm ratio (FAR) is 0.86 and 0.81, and the bias is 4.25 and 3.73, respectively. POD is highest during daytime (0.72; bias: 7.34), decreases at night (0.57; bias: 3.89), and is lowest at twilight (0.52; bias: 2.36). The seasonal mean POD is 0.65 in winter, 0.61 in spring and autumn, and 0.47 in summer, with August reaching the minimum value, 0.33. While POD is higher in coastal areas than inland areas, inland regions show lower FAR, indicating more stable performance. Over-detections occurred regardless of geographic location and time, mainly due to the misclassification of low-level clouds and cloud edges as fog. Especially after sunrise, the fog dissipated and transformed into low-level clouds. These findings suggest that there are limitations to improving fog detection levels using satellite data alone, especially when the surface is obscured by clouds, indicating the need to utilize other data sources, such as objective ground-based analysis data. Full article

Urban expansion in coastal areas involves infrastructure development, industrial growth, and mining activities. These coastal environments face various environmental and geological hazards that require geo-engineers to devise solutions. An integrated geophysical approach aims to address such complex challenges as sea level rise, sea water intrusion, shoreline erosion, landslides and previous anthropogenic activity in coastal settings. In this study, the proposed methodology involves the systematic application of geophysical methods (FDEM, 3D GPR, 3D ERT, seismic), starting with a broad-scale survey and then proceeding to a localized exploration, in order to identify lithostratigraphy, bedrock depth, sea water intrusion and detect anthropogenic buried features. The critical aspect is to leverage the unique strengths and limitations of each method within the coastal environment, so as to derive valuable insights for survey design (extension and orientation of measurements) and data interpretation. The coastal zone of Throrikos valley, Attica, Greece, serves as the test site of our geophysical investigation methodology. The planning of the geophysical survey included three phases: The application of frequency-domain electromagnetic (FDEM) and 3D ground penetrating radar (GPR) methods followed by a 3D electrical resistivity tomography (ERT) survey and finally, using the seismic refraction tomography (SRT) and multichannel analysis of surface waves (MASW). The FDEM method confirmed the geomorphological study findings by revealing the paleo-coastline, superficial layers of coarse material deposits and sea water preferential flow due to the presence of anthropogenic buried features. Subsequently, the 3D GPR survey was able to offer greater detail in detecting the remains of an old marble pier inland and top layer relief of coarse material deposits. The 3D ERT measurements, deployed in a U-shaped grid, successfully identified the anthropogenic feature, mapped sea water intrusion, and revealed possible impermeable formation connected to the bedrock. ERT results cannot clearly discriminate between limestone or deposits, as sea water intrusion lowers resistivity values in both formations. Finally, SRT, in combination with MASW, clearly resolves this dilemma identifying the lithostratigraphy and bedrock top relief. The findings provide critical input for engineering decisions related to foundation planning, construction feasibility, and preservation of coastal infrastructure. The methodology supports risk-informed design and sustainable development in areas with both natural and cultural heritage sensitivity. The applied approach aims to provide a complete information package to the modern engineer when faced with specific challenges in coastal settings. Full article

As ecologically sensitive interfaces shaped by the interplay of land and sea, coastal zones demand close attention. Uncovering the spatiotemporal evolution of ecosystem service value (ESV) and the intricate interrelations among ecosystem service (ES) functions is imperative for the informed governance of human–land interactions and for fostering sustainable regional development. This study analyzes the spatiotemporal evolution of ESV based on the modified equivalent factor table, combining the Geo-information Tupu, Markov transfer model, and standard deviation ellipse. Additionally, we introduce an ecosystem service tradeoff degree (ESTD) to assess the tradeoffs and synergies among various ESs, and we utilize GeoDetector to elucidate the driving forces behind the spatial disparities in ESV. Our findings reveal that (1) Although the land use composite index in the Liaoning coastal economic belt (LCEB) increased, the pace of land use transformation demonstrated a trend toward stabilization over the study duration. (2) Between 2000 to2020, ESV initially declined but subsequently experienced an upward rebound, resulting in a net gain of approximately 48 billion yuan. Spatial analysis indicated continuous enlargement of the standard deviation ellipse, with its centroid consistently located within Yingkou City and a gradual directional shift toward the southwest. (3) The dominant relationship among ESs showed synergy, with notable tradeoffs between hydrological regulation and other services. (4) Topography and climate factors were the primary drivers of spatial heterogeneity of ESV in the LCEB. The research provides spatial decision support for optimizing the ecological security pattern of the coastal zone. Full article

As a national ecological civilization pilot, Zhejiang’s growing vegetation carbon sink capacity is important for both regional ecological security and China’s carbon neutrality goals, but current studies lack a comprehensive assessment of multi-factor interactions. This study employed an improved Carnegie–Ames–Stanford Approach (CASA) and soil respiration empirical equation to estimate Net Ecosystem Productivity (NEP) in Zhejiang Province, and trend analysis, partial correlation analysis, and the GeoDetector model based on optimal parameters (OPGD) were utilized to investigate the spatiotemporal variations and driving factors of vegetation NEP. The results showed that the multi-year average NEP and carbon sink capacity in Zhejiang Province were 387.67 g C m⁻² a⁻¹ and 38.84 Tg C a⁻¹, exhibiting an increasing trend at an average rate of 2.15 g C m⁻² a⁻¹ and 0.23 Tg C a⁻¹, respectively. Spatially, NEP was higher in the western and southern mountainous regions and lower in the eastern coastal and northern plains. NEP in Zhejiang Province was driven by both natural and anthropogenic factors, with NDVI (q = 0.502) and elevation (q = 0.373) being the primary natural drivers, and nighttime light intensity (q = 0.327) and impervious surface dynamics (q = 0.295) being the main anthropogenic drivers. Moreover, the interactions among these factors all exhibited synergistic enhancement effects. Overall, Zhejiang Province functioned predominantly as a carbon sink, with its sequestration capacity gradually strengthening over time. The combined effects of natural and anthropogenic factors drove the spatiotemporal heterogeneity of vegetation NEP. These findings highlight the importance of coordinated ecosystem management strategies that consider both natural and anthropogenic-induced impacts to enhance the achievement of regional carbon sink goals. Full article

Global ecosystems, particularly in biodiversity-rich tropical rainforests, are increasingly under pressure from human activities. As socio-economic development continues and populations steadily grow, the effective planning of areas surrounding national parks has become a global challenge. This study, based on remote sensing data and utilizing landscape ecology tools, such as ArcGIS 10.8, GeoDa 1.20, and Fragstats 4.2, combines spatial statistical methods, trend analysis, and the Hurst index to conduct a long-term analysis and forecast future trends in vegetation ecological quality indicators (VEQI) and landscape pattern changes within and around the Hainan Tropical Rainforest National Park. VEQI changes across various buffer zones were also assessed. Our results show that both arable and built-up land increased, especially from 2002 to 2022. Arable land decreased from 5566.8 km² to 4796.8 km², then increased to 5904.6 km²; built-up land expanded from 163.97 km² to 314.59 km², reflecting urbanization. Spatiotemporal analysis revealed that 42.54% of the study area experienced significant VEQI changes, with a 24.05% increase (mainly in the northwest) and an 18.49% decrease (mainly in the southeast). The VEQI improvements were consistent across all buffer zones, with the most significant growth in the 7.5 km zone. Landscape indices indicated high fragmentation in coastal areas, while inland areas remained stable, reflecting the tension between conservation and urbanization. These findings provide a theoretical basis for future ecological development and buffer zone policies in the park. Full article

The geographical environment and economic conditions that influence the spatial distribution of minority villages vary significantly, particularly in mountainous regions where they face different levels of disaster risks. Environmental suitability assessment can help us gain a deeper understanding of the differences and degrees of differences among different villages and provide a basis for resource allocation and planning. This study focuses on 499 national level and 68 provincial level minority villages in Fujian province and evaluates the environmental suitability of their spatial distribution using analysis tools such as ArcMap and GeoDetector. The research findings indicated: (1) The ratio between the influence strengths of natural geographical, socioeconomic, and disaster constraint indicators on the environmental suitability of minority villages in mountainous areas is 5:10:7, with the highest influence being the regional gross domestic product (RGDP) in the socioeconomic indicator (0.509) and the lowest influence being flood sensitivity (0.011). (2) Areas with high suitability values are in the southeast coastal and central regions. From east to west, the suitability values gradually decrease. The suitable areas cover 87.2% of the total region, including 91.9% of the minority villages. (3) The geographical correlation coefficient between the spatial distribution of minority villages and environmental suitability is 86.87, indicating a high degree of spatial interaction and fit between the two. This validates the rationality of the multi-factor evaluation model for assessing the environmental suitability of ethnic village spatial distribution in mountainous areas. (4) There is an inverse “U” relationship between environmental suitability and the distribution of national and provincial level minority villages. With the increase in the suitability index, the number of national level minority villages tends to increase, while the number of provincial level minority villages tends to decrease. The research findings have significant implications for promoting the sustainable development of minority villages in Fujian province and provide reference for the regional development and protection of minority villages in other mountainous areas. Full article

Water and its management have played a pivotal role in the evolution of organisms and civilizations, fulfilling essential roles in personal use, industry, irrigation, and drinking from ancient times to the present. This study seeks to evaluate groundwater quality for irrigation and drinking in the Northern Peloponnese region, specifically the wells of Loutraki and Schinos areas and the springs of the Gerania Mountains (Mts.), using geo-environmental indices and ionic ratios. For the first time, geo-environmental indices have been applied to a region where groundwater serves multiple purposes, addressing the challenge of understanding their dynamics to optimize their application in environmental science and groundwater pollution research. To achieve this, 68 groundwater samples from the study area were utilized, and a total of 25 geo-environmental indices were calculated to assess water quality. These indices examined: (i) drinking suitability (NPI, RI, PIG, WQI, and WPI), (ii) irrigation suitability (SAR, KR, %Na, PS, MAR, RSC, SSP, TH, PI, IWQI, and TDS), (iii) potentially toxic element (PTE) loadings (Cd, HEI, and HPI), and (iv) major hydrogeochemical processes, expressed as ionic ratios (Ca/Mg, Ca/SO₄, Ca/Na, Cl/NO₃, Cl/HCO₃, and Si/NO₃). Data processing involved descriptive statistics, hydrogeochemical bivariate plots, Spearman correlation coefficients, and multivariate statistical analyses, including factor analysis (FA) and R-mode hierarchical cluster analysis (HCA). Results revealed that all groundwater samples (100%) from the Loutraki area and the Gerania Mts. were of good quality for both drinking and irrigation purposes. In contrast, groundwater from the Schinos area exhibited lower quality, with most samples (93.9%) considered suitable only for irrigation. The deterioration in the coastal aquifer of the Schinos area is attributed to elevated concentrations of Cl⁻, Na⁺, NO_3⁻, As, and Cr resulting from salinization and relatively limited anthropogenic influences. The study highlights that relying on individual geo-environmental indices can yield misleading results due to their dependence on factors such as researcher expertise, methodological choices, and the indices’ inherent limitations. Consequently, this research emphasizes the necessity of combining indices to enhance the reliability, accuracy, and robustness of groundwater quality assessments and hydrogeochemical evaluations. Last but not least, the findings demonstrate that calculating all available geo-environmental indices is unnecessary. Instead, selecting a subset of indices that either reflect the impact of specific elemental concentrations or can be effectively integrated with others is sufficient. This streamlined approach addresses challenges in optimizing geo-environmental index applications and contributes to improved groundwater resource management. Full article

Traditional coastal flood risk prediction often overlooks critical geographic features, underscoring the need for accurate risk prediction in coastal cities to ensure resilience. This study enhances the prediction of coastal flood occurrence by utilizing the Geospatial Artificial Intelligence (GeoAI) approach. This approach employed models—random forest (RF), k-nearest neighbor (kNN), and artificial neural networks (ANN)—and compared them to the IPCC risk framework. This study used El Salvador as a demonstration case. The models incorporated seven input variables: extreme sea level, coastline proximity, elevation, slope, mangrove distance, population, and settlement type. With a recall score of 0.67 and precision of 0.86, the RF model outperformed the other models and the IPCC approach, which could avoid imbalanced datasets and standard scaler issues. The RF model improved the reliability of flood risk assessments by reducing false negatives. Based on the RF model output, scenario analysis predicted a significant increase in flood occurrences by 2100, mainly under RCP8.5 with SSP5. The study also highlights that the continuous mangrove along the coastline will reduce coastal flood occurrences. The GeoAI approach results suggest its potential for coastal flood risk management, emphasizing the need to integrate natural defenses, such as mangroves, for coastal resilience. Full article

Tourism has emerged as a pivotal element of China’s economic development, particularly within its coastal cities. This paper presents a comprehensive analysis of China’s coastal city tourism economic development, focusing on 53 coastal cities. Through a meticulous combination of literature analysis and data crawling, a robust database is constructed, encompassing tourism resources and revenues. This study delineates the spatial–temporal evolution pattern of China’s coastal city tourism development and employs geo-detector methods to quantitatively analyze the impact factors driving this evolution. Key findings reveal distinct trends in the coastal tourism economy of China from 2009 to 2019, characterized by spatial stability, similar trends in adjacent spatial units, and localized spatial structures. Notably, factors such as actual foreign investment, the presence of star-rated guesthouses, tourism industry employment, airport activity, and import–export trade volume exert significant influence on the domestic tourism economy. Similarly, tourism employment, airport activity, availability of star-rated hotels, import–export trade, and utilization of foreign capital emerge as influential factors shaping inbound tourism. Policy recommendations emphasize the need for government intervention to optimize tourism development strategies for coastal cities. This entails balancing resource exploitation with environmental protection and enhancing the quality of tourism services, fostering sustainable growth and long-term prosperity. Full article

This study describes the prevalent sedimentological and geochemical patterns and investigates the environmental status of the bottom of Gialova lagoon, a highly vulnerable coastal site of the EU’s Natura 2000 network. For this task, lithological, geochemical, and microfaunal analyses of sediment samples were combined with a high-resolution bathymetric survey. Potential pollution was determined using geochemical-based (EF, I-geo, and PLI) and faunal (Foram-AMBI) indices. We find that sedimentation is mainly controlled by the bottom morphology, hydrodynamic variations, and biogenic productivity of the lagoon. The application of the multivariate factor analysis technique revealed four dominant factors explaining the geochemical processes occurring in the lagoon. The first factor, namely “terrigenous aluminosilicates associated with C_org vs. autochthonous biogenic carbonates”, discriminates the deposition of detrital sediments, related to the high adsorption of heavy metals—versus bioclastic sediments. The “sulfides” factor represents an anoxic phase of the lagoon floor, whereas the “Mn-oxyhydroxides” factor indicates increased manganese content with several compounded trace elements. The “phosphate” factor reveals multiple sources of phosphorus in the lagoon. The lagoon bottom shows negligible to minor contamination in heavy metals, except Mo and Pb, which induce moderate pollution levels. The maximum contamination and environmental stress concern two small-sized, shallow basins within the lagoon. Full article

Cultural resources are often overlooked in climate change and resiliency planning, despite them being integral to community identity and the restoration of a sense of normalcy after significant weather events. This vulnerability assessment demonstrates how cultural resources can be included in planning efforts, and how they can be prioritized based on specific criteria. To complete this assessment, a working group with local land managers and cultural resource professionals was formed, and members employed a sophisticated Geo Tool, ACUNE (Adaptation of Coastal Urban and Natural Ecosystems) for climate adaptation, to predict how cultural resources throughout Collier County, Florida, would be impacted in two specific climate scenarios. The working group selected ten significant sites in the county and used ACUNE to prioritize action at these sites, using a matrix of hazard exposure, sensitivity, adaptive capacity, and the environmental, social, and economic consequences of the loss of these sites. Based on the results of our case study vulnerability assessment of cultural resources in Collier County, the next decade (2020 to 2030) has the potential to increase the number of sites at risk of storm flooding from 267 to 318, alerting managers that immediate action is needed for the sites of greatest value. The analysis of 10 case study sites is presented to demonstrate an approach for land managers and other cultural resource professionals to prioritize action at their own sites. Full article

Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region’s socio-economic framework. Full article

(1) Background: The sustainable development of rural areas has become a critical factor in global economic and social transformation. As an essential part of China’s rural ecological and cultural system, traditional villages are now facing a crisis of yearly decline, and sustainable development has become a meaningful way to solve the problem. This study utilized morphological indicator analysis and the SDGs as an evaluation framework to reveal the correlation and driving factors between traditional villages’ spatial form and sustainability indicators. From the perspective of the spatial form, this approach has specific reference significance for improving the sustainability of traditional villages. (2) Methods: A framework for detecting the driving factors of rural sustainability based on four dimensions (morphology, environment, economy, and society) was constructed. A geographic information system (GIS) was used to analyze the geographic patterns and morphological indicator characteristics of traditional villages in Jiangsu Province, and GeoDetector was used to analyze the driving mechanisms of the spatial patterns of sustainability in traditional villages, providing the basis for spatial zoning and differentiated policy design for the construction, planning, and management of sustainable villages. (3) Results: ➀ The spatial patterns and morphological characteristics of traditional villages exhibit prominent geographical imbalances and significant cluster cores. ➁ The high-density and low-aspect-ratio rural form in the southern region (where rural industries are developed) promotes good economic sustainability in rural areas but also leads to poor environmental performance. The rural areas in the southwest and north (high-density forest areas) have medium density and a high aspect ratio, and the lack of agricultural space and external connections affects their social performance. The main focus is on poverty reduction and urban cooperation. The central and northern lakeside areas and the eastern coastal areas (important ecological protection areas) have low density and high aspect ratios, which have helped them to achieve excellent environmental performance but also led to contradictions in environmental, economic, and social performance. Maintaining low-density patterns, using clean energy, and protecting terrestrial and underwater biodiversity are essential to the sustainability of the rural environment. The agglomeration of spatial patterns promotes cooperation between rural and urban areas and improves industrial development, contributing to the sustainability of the rural economy. Improving social welfare and agricultural development contributes to the sustainability of rural societies. ➂ The impacts of various factors vary significantly; for example, Life below Water (SDG14), Climate Action (SDG13), and No Poverty (SDG1) are the most prominent, followed by Partnerships for the Goals (SDG17), Affordable and Clean Energy (SDG7), and Recent Work and Economic Growth (SDG8). (4) Conclusions: It is recommended that the government, with the driving mechanisms, divide the spatial management zoning of traditional villages in Jiangsu into three types of policy areas: environmental-oriented, economic-oriented, and social-oriented. Differentiated and targeted suggestions should be proposed to provide a critical decision-making basis for protecting and utilizing traditional villages in Jiangsu and similar provinces, as well as to help promote rural revitalization and sustainable rural construction in China. Full article

Constructing underground reservoirs has emerged as a crucial strategy to address the shortage of fresh water in Rizhao, Shandong Province, China. However, the water quality, microbial community composition, and biogeochemical cycling of nutrients in underground reservoirs compared to raw water remain unknown. To unveil the characteristics of microbial community structures and their nitrogen cycling metabolic potential in coastal underground reservoirs, we utilized a functional gene array (GeoChip 5.0) in conjunction with high-throughput sequencing of 16S rRNA and 18S rRNA genes. Our findings indicate that the water quality in the underground reservoir exhibits a certain degree of eutrophication compared to raw water, with higher concentrations of TN, TP, NO₃⁻N, NO₂⁻-N, and Chl a, but lower concentrations of DO and NH₄⁺-N. The alpha diversity of bacterial and microeukaryotic communities was significantly lower in the underground reservoir. The bacterial community presented a stronger correlation with environmental factors than the microeukaryotic community. Regarding the relative abundance of bacterial communities, Gammaproteobacteria dominated the bacterial community in raw water, while Gammaproteobacteria and Alphaproteobacteria dominated the bacterial community in underground reservoir water. Additionally, the relative abundance of Nitrospirae was noticeably higher in the underground reservoir water. Moreover, we found significantly higher sequence abundance of the archaea Thaumarchaeota in the underground reservoir. Furthermore, our analysis revealed that, except for the amoA functional gene, which significantly increased the metabolic potential of nitrification, the metabolic potential of other microbial nitrogen functional genes was significantly reduced. This reduction may contribute to the lower concentration of NH₄⁺-N in the underground reservoir. This study provides a comprehensive understanding of the microbial community characteristics and their nitrogen cycling metabolic potential in underground reservoirs. It serves as a valuable reference for water source selection, the formulation of water quality assurance measures, and the construction and management of underground reservoirs for subsequent impounding. Full article

This study addresses the escalating global concern surrounding land degradation (LD) and its far-reaching implications on water and nutrient availability, as well as on human health and well-being. Focused on the southeastern Caspian Sea region, this research employs a novel remote sensing geo-pedological methodology to comprehensively assess soil and land quality dynamics, particularly influenced by salts, and investigates the intricate relationship between LD and soil development. The study area, marked by a susceptibility to seawater level fluctuations and diverse landforms (lagoons, barriers, and coastal plains) offers a unique opportunity for geopedologic analysis. Utilizing particle size distribution data, six distinct landforms are identified, providing insights into the region’s complex sedimentary history. A soil quality assessment is conducted remotely through the calculation of two indexes—the Integrated Quality Index (IQI) and the Nemoro Quality Index (NQI)—employing both Total Data Set (TDS) and Minimum Data Set (MDS) methodologies. The investigation highlights the role of soluble salts in shaping soil quality, thereby influencing LD and development dynamics. The differentiation of landforms significantly enhances classification accuracy, providing a more nuanced understanding of the multifaceted factors governing LD. The study’s implications extend beyond the southeastern Caspian Sea region, and demonstrate that the potential for incorporating a geopedologic approach when assessing soil and land quality dynamics in arid regions globally. Our analytic approach can inform policymakers and land managers when making decisions to combat LD and foster sustainable land development. This research also contributes towards advancing knowledge in geopedology by providing a robust foundation for future studies aimed at enhancing land management practices in the face of ongoing environmental challenges. Full article