Search Results (12)

The mapping and monitoring of coastal regions are critical to ensure their sustainable use and viability in the long term. Delineation of coastlines is becoming increasingly important in the light of climate change and rising sea levels. However, many coastlines are highly dynamic; therefore, mono-temporal assessments of coastal ecosystems and coastlines are mere snapshots of limited practical value for space-based planning. Understanding of the spatio-temporal dynamics of coastal ecosystem boundaries is important to inform ecosystem management but also for a meaningful delineation of the high-water mark, which is used as a benchmark for coastal spatial planning in South Africa. This research aimed to use hyper-temporal Sentinel-2 imagery to extract ecological zones on the coast of KwaZulu-Natal, South Africa. A total of 613 images, collected between 2019 and 2023, were classified into four distinct coastal ecological zones—vegetation, bare, surf, and water—using a Random Forest model. Across all classifications, the percentage of each of the four classes’ occurrence per pixel over time was determined. This enabled the identification of ecosystem locations, spatially static ecosystem boundaries, and the occurrence of ecosystem boundaries with a more dynamic location over time, such as the non-permanent vegetation zone of the foredune area as well as the intertidal zone. The overall accuracy of the model was 98.13%, while the Kappa coefficient was 0.975, with user’s and producer’s accuracies ranging between 93.02% and 100%. These results indicate that cloud-based analysis of Sentinel-2 time series holds potential not just for delineating coastal ecosystem boundaries, but also for enhancing the understanding of spatio-temporal dynamics between them, to inform meaningful environmental management, spatial planning, and climate adaptation strategies. Full article

Historically, urban development has always been centered on coastal areas, with access to waterbodies—seas, rivers and canals—being a significant advantage for movement and trade. With most of the world’s megapolises located on coasts, land reclamation offers a solution for the expansion of city centers which are otherwise restricted by the coastline. This study aims to define the current understanding of urban regeneration and development on reclaimed lands, addressing the basic questions of what, why and how. This study aims to assess urban regeneration on reclaimed coastal land based on the principles of sustainable development defined by existing studies. The literature review establishes a theoretical framework and defines performance-based benchmarks for identifying spatial indicators of urban development. Composite indicators, namely open space coverage, land use mix, the percentage of coast for people, accessibility to public transportation and amenities, the availability of pedestrian paths and cycling tracks and adequate road networks, are considered for this framework. The conclusions are drawn based on the results of an analysis of spatial layout using a GIS as a tool to map and empirically measure each indicator. The framework is validated using a major land reclamation project, West Bay, in the coastal urban area of Doha in Qatar. The results determine that West Bay has achieved a good level of sustainability, although there are areas that could be enhanced to improve the overall sustainability of urban development further. These findings can serve as a guide for policymakers and various stakeholders for sustainable urban planning on reclaimed coastal lands. Full article

The rapid growth of phytoplankton and microalgae has presented considerable environmental and societal challenges to the sustainable development of human society. Given the inherent limitations of satellite-based algal bloom detection techniques that rely on chlorophyll and fluorescence methods, this study proposes a method that employs hyperspectral data to calculate water chromatic indices (WCIs), including hue, saturation (S), dominant wavelength (λd), and integrated apparent visual wavelength (IAVW), to identify algal blooms. A global in situ hyperspectral dataset was constructed, comprising 13,110 entries, of which 9595 were for normal waters and 3515 for algal bloom waters. The findings of our investigation indicate statistically significant discrepancies in chromaticity parameters between normal and algal bloom waters, with a p-value of 0.05. It has been demonstrated that different algal blooms exhibit distinct chromatic characteristics. For algae of the same type, the chromaticity parameters increase exponentially with chlorophyll concentration for hue and λd, while S shows low correlation and IAVW displays a good linear relationship with chlorophyll concentration. The application of this method to the Bohai Sea (coastal) and Taihu Lake (inland water) for the extraction of algal blooms revealed a clear separation in chromaticity parameters between normal and algal bloom waters. Moreover, the method can be applied to satellite data, offering an alternative approach for the detection of algal blooms based on satellite data. The indices can serve as ground truth values for colorimetric indices and provide a benchmark for the validation of satellite chromatic products. Full article

The atmosphere over the ocean is an important research field that involves multiple aspects such as climate change, atmospheric pollution, weather forecasting, and marine ecosystems. It is of great significance for global sustainable development. Satellites provide a wide range of measurements of marine aerosol optical properties and are very important to the study of aerosol characteristics over the ocean. In this study, aerosol optical depth (AOD) data from seventeen AERONET (Aerosol Robotic Network) stations were used as benchmark data to comprehensively evaluate the data accuracy of six aerosol optical thickness products from 2013 to 2020, including MODIS (Moderate-resolution Imaging Spectrometer), VIIRS (Visible Infrared Imaging Radiometer Suite), MISR (Multi-Angle Imaging Spectrometer), OMAERO (OMI/Aura Multi-wavelength algorithm), OMAERUV (OMI/Aura Near UV algorithm), and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in the East Asian Ocean. In the East Asia Sea, VIIRS AOD products generally have a higher correlation coefficient (R), expected error within ratio (EE within), lower root mean square error (RMSE), and median bias (MB) than MODIS AOD products. The retrieval accuracy of AOD data from VIIRS is the highest in spring. MISR showed a higher EE than other products in the East Asian Ocean but also exhibited systematic underestimation. In most cases, the OMAERUV AOD product data are of better quality than OMAERO, and OMAERO overestimates AOD throughout the year. The CALIPSO AOD product showed an apparent underestimation of the AOD in different seasons (EE Below = 58.98%), but when the AOD range is small (0 < AOD < 0.1), the CALIPSO data accuracy is higher compared with other satellite products under small AOD range. In the South China Sea, VIIRS has higher data accuracy than MISR, while in the Bohai-Yellow Sea, East China Sea, Sea of Japan, and the western Pacific Ocean, MISR has the best data accuracy. MODIS and VIIRS show similar trends in R, EE within, MB, and RMSE under the influence of AOD, Angstrom exponent (AE), and precipitable water. The study on the temporal and spatial distribution of AOD in the East Asian Ocean shows that the annual variation of AOD is different in different sea areas, and the ocean in the coastal area is greatly affected by land-based pollution. In contrast, the AOD values in the offshore areas are lower, and the aerosol type is mainly clean marine type aerosol. These findings can help researchers in the East Asian Ocean choose the most accurate and reliable satellite AOD data product to better study atmospheric aerosols’ impact and trends. Full article

Systematic literature reviews provide the foundation for evidence-based research in a particular field of study. In this regard, the systematic review of the relationship between coastal management strategies and coastal infrastructure typologies provides an opportunity to benchmark local coastal adaptation policies against contemporary global practices, technologies, and sustainability. However, systematic reviews of coastal infrastructure in Ghana and West Africa at large are limited. To close this research gap, we conducted a systematic literature review of the global implementation of coastal management strategies and coastal infrastructure and provided a synopsis of coastal management in Ghana. To achieve this, we searched the Scopus Database for literature on coastal management approaches and infrastructure typologies. Forty-eight peer-reviewed publications met the inclusion criteria for full-text analysis. The results indicate a significant global shift from purely grey infrastructure toward integrating green and grey infrastructure. However, despite contemporary global advances, coastal infrastructure in developing contexts—particularly in Ghana—remains mostly static, using reactive, hold the line strategies, and grey infrastructure. As sea-level rise continues to intensify coastal hazards globally, increasing the demand for coastal protection, researching coastal management policies and coastal infrastructure is essential to support the hybridization of grey and green infrastructure and encourage transitions to adaptive coastal management instead of continuous coastal hardening using grey infrastructure. Full article

As the continuous improvement of the quality of innovation becomes increasingly significant for balanced regional development in China, it is critical to provide insights into the sustainability of regional innovation in China from the viewpoint of value. This study estimates regional innovation values based on an improved regional innovation value model incorporating patent values and a regional innovation indicator system. Data for invention patents as well as regional innovation indicators in 282 cities from 1987 to 2019 in China are utilized for estimation. Based on the estimated parameters and Monte Carlo simulation, city-level innovation values are calculated as benchmarks, along with provincial and regional innovation values, to analyze the patterns of the spatial distribution and agglomeration of regional innovation value. The findings are as follows. (1) The regional innovation value model provides an effective way to measure regional innovation in terms of value. (2) The regional innovation values are unevenly distributed; cities with higher innovation values are clustered in Eastern China, while most other cities have much lower innovation values. (3) The innovation values in Eastern China are notably higher, and the differences in innovation values between Eastern China and other regions are large and show a trend of first widening and then narrowing during the sample period. (4) The sustainability of regional innovation is not widely achieved, since highly concentrated innovation value is found in only a few regions in the eastern coastal areas. These findings suggest that promoting China’s innovation capacity and the sustainable development of technological innovation requires continually implementing innovation-driven development strategies, cultivating high-value innovation, optimizing industrial transfer, improving the layout of the national research infrastructure, giving full play to spatial spillover effects, and promoting interregional innovation information exchange in order to achieve the balanced and sustainable development of regional innovation. Full article

Industrial agglomeration is currently an important mode of industrial organisation in China’s regional economic development. Many provinces rely on their favourable resource and location advantages to formulate corresponding industrial agglomeration policies. Industrial agglomeration policies produce agglomeration effects, which enable enterprises in the agglomeration area to gain external advantages such as labour, resources and technology, effectively improving productivity and promoting sustainable local economic development. Based on the inter-provincial industry panel data from 2008 to 2017, the static benchmark regression model and dynamic GMM model are constructed to study the relationship between industrial agglomeration, labour productivity and exports, and to explore their interaction mechanism and practical effects. The study shows that, firstly, industrial agglomeration in China significantly contributes to industrial exports. However, in the long run, industrial agglomeration has a positive and then negative effect on industrial exports, with an inverted U-shaped curve. Secondly, the relationship between industrial agglomeration and industrial exports is negatively influenced by labour productivity. Finally, based on the perspective of regional heterogeneity, the impact of industrial agglomeration on exports is not significant in industrial base regions, but shows a significant promotion relationship in non-industrial base regions. Moreover, the impact of industrial agglomeration on industrial exports is not significantly different between coastal port regions and non-coastal port regions. Based on the research results, this paper puts forward targeted policy recommendations such as changing the competition model, increasing the introduction of talent and adjusting the industrial structure. Full article

Local wisdom is frequently used by communities in managing their coastal resources without a precise measure of sustainability. As a result, the government must develop a standard for determining the wisdom of these practices. This study aimed to create such a standard, followed by a trial to evaluate management practices in Pangandaran coastal tourism. This qualitative case study included a literature review, direct observations, and in-depth interviews with fish farmers and fishers. They are standardizing instrument criteria for sustainable fishery resource management-defined wisdom. Such wisdom is divided into fundamental thinking (factual knowledge) and management practices (procedural knowledge). Each consists of five criteria: ecosystem and resource management, planning, governance, technology, and social and economic development. Each criterion has a specific rating indicator and parameter. The results show differences in the level of wisdom between the fish farmer and the fishers. Regarding basic thinking, fishers’ wisdom level is weak in three out of five criteria. Fishers reach a moderate wisdom level concerning fishing gear and technical criteria and a strong level on social and economic criteria. In contrast, the fish farmer is moderate to strong for four criteria and weak for the resources and ecosystems criterion. Regarding management practices, in general, fish farmers and fishers have the same level of wisdom. Both are weak in the ecosystem and resources, planning, and institutional criteria, while the fishing gear criteria reach moderate levels and the socio-economic criteria reach high levels. Full article

Small accommodation businesses dominate the rural hospitality industry, producing simple or complex tourist products and services in order to be sustainable and competitive. In this paper, a two-stage data envelopment analysis (DEA) model was applied in a representative sample of 151 small accommodation businesses in non-coastal areas in the region of Central Macedonia in Greece. In the first stage, DEA-bootstrapping is applied to estimate point and interval efficiency ratios of accommodation businesses and identify the benchmark accommodations. The double bootstrapping truncated procedure of Simar and Wilson is implemented in the second stage to investigate the role of five business factors in terms of efficiency. The findings suggest that small accommodation businesses, although they are based in areas where tourist resources abound, are inefficient. Moreover, the results of the truncated regression method showed that the business’s size, the operating days, and the variety of activities (simple/complex) affect business’s inefficiency. On the contrary, the business’s age and their engagement in agriculture or not do not affect business’s efficiency. The results are important for rural entrepreneurs and policy makers, and they will also be useful for the adaptation of businesses to increase their efficiency. Full article

In 2015, the United Nations General Assembly identified 17 Sustainable Development Goals (SDGs) to be achieved by the year 2030. The study’s main objective is to identify the necessary conditions and potential for ensuring both the sustainability and competitiveness of tourism in seaside and marine resorts located in or at coastal and marine protected areas on the example of Karklė (Lithuania). Based on the results of a benchmarking study of five South Baltic resorts using the Delphi technique, the survey team identified the main deficiencies of Karklė as a seaside and marine resort of an international scale. We address the deficiencies by applying a geographical information system as a decision-support tool for the Littoral Regional Park where Karklė is located. We conclude that for ensuring both the sustainability and competitiveness of tourism in seaside and marine resorts, it is expedient to combine the Delphi-based tourism benchmarking with integrated coastal management and maritime spatial planning, for which GIS is an indispensable tool. Full article

Measuring and forecasting changes in coastal and deep-water ecosystems and climates requires sustained long-term measurements from marine observation systems. One of the key considerations in analyzing data from marine observatories is quality assurance (QA). The data acquired by these infrastructures accumulates into Giga and Terabytes per year, necessitating an accurate automatic identification of false samples. A particular challenge in the QA of oceanographic datasets is the avoidance of disqualification of data samples that, while appearing as outliers, actually represent real short-term phenomena, that are of importance. In this paper, we present a novel cross-sensor QA approach that validates the disqualification decision of a data sample from an examined dataset by comparing it to samples from related datasets. This group of related datasets is chosen so as to reflect upon the same oceanographic phenomena that enable some prediction of the examined dataset. In our approach, a disqualification is validated if the detected anomaly is present only in the examined dataset, but not in its related datasets. Results for a surface water temperature dataset recorded by our Texas A&M—Haifa Eastern Mediterranean Marine Observatory (THEMO)—over a period of 7 months, show an improved trade-off between accurate and false disqualification rates when compared to two standard benchmark schemes. Full article

Chiayi County is located in the largest alluvial plain of Taiwan with extensive aquaculture and rice farming sustained by water extracted from groundwater wells. Chiayi is a typical aquaculture area affected by land subsidence, yet such lands worldwide combine to provide nearly 90% of global aquaculture products, greatly reducing oceanic overfishing problems. This study uses precision leveling, multi-layer compaction monitoring well (MLCW) and spaceborne SAR interferometry (InSAR) to examine the cause and effect of land subsidence in Chiayi associated with groundwater extractions and changes. Heights at benchmarks in a leveling network are measured annually and soil compactions at 24–26 layers up to 300-m depths at 7 MLCWs are collected at one-month intervals. Over 2007–2011, 15 ALOS/PALSAR images are processed by the method of TCPInSAR to produce subsidence rates. All sensors show that land subsidence occur in most parts of Chiayi, with rates reaching 4.5 cm/year around its coast, a result of groundwater pumping from shallow to deep aquifers. MLCWs detect mm-accuracy seasonal soil compactions coinciding with groundwater level fluctuations and causing dynamic compactions. Compactions near Taiwan High Speed Rail may reduce the strength of the rail’s supporting columns to degrade its safety. The SAR images yield subsidence rates consistent with those from leveling and compaction wells after corrections for systematic errors by the leveling result. Subsidence in Chiayi’s coastal area leads to relative sea level rises at rates up to 15 times larger than the global eustatic sea level rising rate, a risk typical for world’s aquaculture-rich regions. At the fish pond-covered Budai Township, InSAR identifies subsidence spots not detected by leveling, providing crucial geo-information for a sustainable land management for aquaculture industry. Full article