Sustainable Coastal Zone Management Research Articles

Correction: Strategic environmental assessment for sustainable coastal zone management in Saudi Arabia, aligning with vision 2030

Correction: Strategic environmental assessment for sustainable coastal zone management in Saudi Arabia, aligning with vision 2030

Strategic environmental assessment for sustainable coastal zone management in Saudi Arabia, aligning with vision 2030

AbstractThis research examines the role of Strategic Environmental Assessment (SEA) in promoting sustainable coastal zone management in Saudi Arabia, in alignment with Vision 2030. Focusing on key coastal regions, namely the Red Sea and Arabian Gulf, the study explores SEA’s capacity to guide development activities toward long-term environmental sustainability. Through a comparative analysis of SEA and traditional Environmental Impact Assessments (EIA), the study emphasizes SEA’s proactive, integrative, and participatory approach to decision-making. The findings illustrate how SEA enhances the strategic alignment of national environmental objectives by fostering resilient and sustainable strategies that balance development with conservation in Saudi Arabia’s coastal zones. Ultimately, SEA is identified as a crucial instrument in achieving Vision 2030’s sustainability goals, offering a pathway to safeguard coastal ecosystems while supporting economic growth.

Investigation of the applicability of the microwave image to complement the optical image for the preparation of a coastal configuration map

The coastal area, being the transition zone between the sea and land, is a country's most diverse and dynamic zone in terms of its environment and economy. A variety of economic activities revolve around this region. Mapping the dynamic coastal configuration is an essential tool for sustainable coastal zone management. Satellite remote sensing offers excellent resources for monitoring and mapping coastal zones. Microwave remote sensing images, in tandem with optical remote sensing imagery, can be used for mapping coastal configurations. However, both images have some limitations. In this context, the present article explores the integrated use of microwave images to supplement optical images to overcome these limitations and generate a coastline configuration map. Res. Agric. Livest. Fish. Vol. 11, No. 1, April 2024: 47-51

Assessment and spatialization of vulnerability of Benin coast to sea level rise using composite/blended approach

Climate change, particularly sea level rise, poses significant challenges to global coastal regions, necessitating a profound understanding of their vulnerability for effective mitigation and adaptation strategies. This study focuses on enhancing scientific insight into West African coastal vulnerability, aiming to assist policymakers and coastal managers in developing sustainable coastal zone management strategies. The methodology employed combines Geographic Information System (GIS) and remote sensing techniques with the Coastal Vulnerability Index (CVI) formula. Parameters such as slope, topography, distance to shoreline, population density, accessibility, land cover, and soil and vegetation types are assessed for their contribution to physical and socio-economic changes induced by sea level rise. These parameters undergo weighting using the Analytic Hierarchy Process (AHP). The socio-economic vulnerability is quantified using the Community-Based Risk Screening Tool-Adaptation and Livelihoods (CRiSTAL). The assessment of the Benin coast reveals significant vulnerability, with very high vulnerability (36.69–70.4, indicated by red cells) and high vulnerability (30.84–36.69, indicated by orange cells) observed in all coastal municipalities (Grand-Popo, Ouidah, Abomey-Calavi, Cotonou, Sèmè-Kpodji), encompassing 40 % and 21 % of the study area, respectively. Moderate (25.69–30.84) and low (10.87–25.69) vulnerability areas are situated at higher elevations inland, covering 35 % and 4 % of the total study area, respectively. No areas of very low vulnerability have been identified. This research contributes significantly to coastal management decisions, adaptation strategies, and climate change policies in Benin by advancing scientific understanding of coastal vulnerability and facilitating the development of sustainable strategies.

Detecting Shoreline Changes on the Beaches of Hainan Island (China) for the Period 2013–2023 Using Multi-Source Data

This study presents an in-depth analysis of the dynamic beach landscapes of Hainan Island, which is located at the southernmost tip of China. Home to over a hundred natural and predominantly sandy beaches, Hainan Island confronts significant challenges posed by frequent marine natural disasters and human activities. Addressing the urgent need for long-term studies of beach dynamics, this research involved the use of CoastSat to extract and analyze shoreline data from 20 representative beaches and calculate the slopes of 119 sandy beaches around the island for the period from 2013 to 2023. The objective was to delineate the patterns of beach evolution that contribute to the prevention of sediment loss, the mitigation of coastal hazards, and the promotion of sustainable coastal zone management. By employing multi-source remote sensing imagery and the CoastSat tool, this investigation validated slope measurements across selected beaches, demonstrating consistency between the calculated and actual distances despite minor anomalies. The effective use of the finite element solution (FES) in the 2014 global tidal model for tidal corrections further aligned the coastlines with the mean shoreline, underscoring CoastSat’s utility in enabling precise coastal studies. The analysis revealed significant seasonal variations in shoreline positions, with approximately half of the monitored sites showing a seaward progression in summer and a retreat in winter, which were linked to variations in wave height. The southern beaches exhibited distinct seasonal variations, which contrasted with the general trend due to differing wave impacts. The western and southern shores showed erosion, while the northern and eastern shores displayed accretion. The calculated slopes across the island indicated that the southern beaches had steeper slopes, while the northern areas exhibited more pronounced slope variations due to wave and tidal impacts. These findings highlight the critical role of integrated coastal management and erosion control strategies in safeguarding Hainan Island’s beaches. By understanding the mechanisms driving seasonal and regional shoreline changes, effective measures can be developed to mitigate the impacts of erosion and enhance the resilience of coastal ecosystems amidst changing environmental conditions. This research provides a foundational basis for future efforts aimed at the sustainable development and utilization of coastal resources on Hainan Island.

Nighttime light in China's coastal zone: The type classification approach using SDGSAT-1 Glimmer Imager

Nighttime Light (NTL) is highly concentrated in China's coastal zone, leading to negative health impacts on both humans and wildlife. Particularly, in recent years, the widespread adoption of broad-spectrum Light-Emitting Diode (LED) light, a low-carbon technology providing substantial increases in luminosity, has led to certain ecological consequences. Thus, information regarding spatial distribution and composition of different NTL types is essential for formulating sustainable strategies that balance nighttime public security, energy consumption, and ecosystem conservation. However, the availability of such information remains limited. To address this challenge and meet the demand, we developed two new light indices, namely the Ratio Red Light Index (RRLI) and Ratio Blue Light Index (RBLI), based on SDGSAT-1 Glimmer Imager (GLI) multispectral NTL data. We then proposed a threshold method and applied it to the entire coastal zone of China to identify White LED (WLED), Red LED (RLED), and Other lights (Other). Results showed the following. (1) In the coastal zone of China, the total lighting area was 20,517 km2, including 20,257 km2 of terrestrial lights and 260 km2 of offshore lights; (2) WLED light covered 67% (13,727 km2) of all lighting areas, while RLED lights accounted for only 1% (220 km2); (3) Guangdong had the largest lighting area (5221 km2), with the proportion of WLEDs being the highest among all coastal provinces (almost 90%); (4) The proportions of lighting areas were relatively low in Guangxi, Liaoning, and Hebei. This study represents the first attempt to identify NTL types over large regions at a finer spatial resolution. The approach proposed, including the light indices of RRLI and RBLI, as well as the defined thresholds, is universal and robust for use in NTL type classification. The developed lighting type map, containing comprehensive information on the spatial distribution and composition of NTL, could facilitate the sustainable management of China's coastal zones.

Application of Shore Sediments Accumulated in Navigation Channel for Restoration of Sandy Beaches around Pärnu City, SW Estonia, Baltic Sea

Sandy beaches high in recreation value make up 16% of the over 4000 km long shoreline of Estonia. The shore processes associated with climate change have remarkably accelerated over recent decades. Many sandy shores have suffered from strong erosion, including an excellent former beach at Valgeranna. The jetties, which were built in the 1860s to protect the navigation channel of Port Pärnu from clogging, have prevented natural sediment transport along the coast from south to north. At the same time, the sandy beach in Pärnu is expanding, and part of the sand accumulates with strong storms also in between the jetties, reducing the width of the shipping channel. The channel needs regular dredging, but, so far, the dredged sediment has been taken far away to the open sea and accumulated on the seabed. The current paper addresses the possibilities of using that sand for beach restoration in destructed and eroded areas. An overview of the applied methods and measurements during field studies is given. The results of modelling the processes of wave activity and sediment transport are discussed. The recycling of shore sediments is an important measure in sustainable coastal zone management. Different options and scenarios are analysed in order to find the most reasonable ways to bring sand back onto beaches and stabilize natural processes. Support from the state by working out respective laws and regulations would be motivating as well.

Time-Lapse Geophysical Measurements for Monitoring Coastal Groundwater Dynamics in an Unconfined Aquifer.

The coastal zone, which is the interface between land and sea, is hydrodynamically very active due to the complex interactions of various hydrological controls and variable-density fluids. These forces vary over time, resulting in a state of dynamic equilibrium in the system. The major hydrological processes in coastal aquifer systems are salt water intrusion and submarine groundwater discharge, which are interdependent. Monitoring these complex processes is crucial for sustainable coastal zone management but poses a significant research challenge. In this study, we demonstrate the effectiveness of non-invasive geophysical techniques, specifically the time-lapse electrical resistivity imaging method, in conjunction with groundwater monitoring, for monitoring coastal groundwater dynamics in an unconfined aquifer at varying time scales and hydrogeological settings present at formerly glaciated sites worldwide. We generated two-dimensional baseline salt water intrusion maps for the test site, located on the coast of Rhode Island, USA. The time-lapse electrical resistivity survey method enables the rapid estimation of fresh groundwater discharge. Our approach offers insight into the mechanisms and seasonably variable salt water-freshwater interactions in unconfined heterogeneous aquifers. Although the results are site-specific, their implications are broad and may stimulate other studies related to sea to land pollution (sea water intrusion) and land to sea pollution (groundwater discharge) in heterogeneous coastal aquifer settings.

Analysis of Multi-Temporal Shoreline Changes Due to a Harbor Using Remote Sensing Data and GIS Techniques

Coastal landforms are continuously shaped by natural and human-induced forces, exacerbating the associated coastal hazards and risks. Changes in the shoreline are a critical concern for sustainable coastal zone management. However, a limited amount of research has been carried out on the coastal belt of Sri Lanka. Thus, this study investigates the spatiotemporal evolution of the shoreline dynamics on the Oluvil coastline in the Ampara district in Sri Lanka for a two-decade period from 1991 to 2021, where the economically significant Oluvil Harbor exists by utilizing remote sensing and geographic information system (GIS) techniques. Shorelines for each year were delineated using Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager images. The Normalized Difference Water Index (NDWI) was applied as a spectral value index approach to differentiate land masses from water bodies. Subsequently, the Digital Shoreline Analysis System (DSAS) tool was used to assess shoreline changes, including Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR), and Linear Regression Rate (LRR). The results reveal that the Oluvil coast has undergone both accretion and erosion over the years, primarily due to harbor construction. The highest SCE values were calculated within the Oluvil harbor region, reaching 523.8 m. The highest NSM ranges were recorded as −317.1 to −81.3 m in the Oluvil area and 156.3–317.5 m in the harbor and its closest point in the southern direction. The maximum rate of EPR was observed to range from 3 m/year to 10.7 m/year towards the south of the harbor, and from −10.7 m/year to −3.0 m/year towards the north of the harbor. The results of the LRR analysis revealed that the rates of erosion anomaly range from −3 m/year to −10 m/year towards the north of the harbor, while the beach advances at a rate of 3 m/year to 14.3 m/year towards the south of the harbor. The study area has undergone erosion of 40 ha and accretion of 84.44 ha. These findings can serve as valuable input data for sustainable coastal zone management along the Oluvil coast in Sri Lanka, safeguarding the coastal habitats by mitigating further anthropogenic vulnerabilities.

Tracking changes in coastal land cover in the Yellow Sea, East Asia, using Sentinel-1 and Sentinel-2 time-series images and Google Earth Engine

Coastal zones are essential ecosystems due to their provision of invaluable ecosystem services. However, the geomorphologic characteristics of coastal zones are becoming more complex and changeable due to global warming, sea-level rise (SLR), and the intensification of anthropogenic activities. Therefore, accurate and timely knowledge of coastal land cover types (including tidal flats, coastal vegetation, and year-long water cover) is needed for coastal research and sustainable management. To date, land cover products for coastal areas are mainly derived from moderate resolution imaging spectroradiometer images, but few studies have used Sentinel-1 synthetic aperture radar (S1) and Sentinel-2 Multispectral Instrument (S2) images, which can provide more detailed maps. We developed a Rule-based Time Series Classification (RTSC) approach to map coastal land cover types at a 10 m resolution, combining S1/S2 time-series images (2015–2019) and Google Earth Engine (GEE). These products were developed for the coastal zone of the Yellow Sea (YS), East Asia, which is an essential ecosystem protecting a coastal population of 60 million people from storms and SLR effects. Accuracy assessment showed that the annual maps of coastal land cover had high overall accuracy. The coastal land cover types for the YS in 2019 comprised 3593.42 km2 of tidal flats, 28,506.98 km2 of coastal vegetation, and 5436.92 km2 of coastal year-long water. The interannual dynamics of the coastal land cover area in the YS during 2015–2019 were smaller. This study provides a promising method that combines S1/2 time series, a RTSC approach, and GEE to map coastal land cover areas at large scales. The 10 m resolution maps generated in this study are the most current dataset of coastal land cover types for the YS, and they potentially provide a basis for the sustainable management and conservation of this important coastal zone.

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal using a single radar altimeter and retracking technique due to the diversity and complexity of coastal waveforms. To solve this issue, we proposed an approach of estimating water level of the coastal zone in Beibu Gulf, China, by combination of waveform classifications and multiple sub-waveform retrackers. This paper stacked Random Forest (RF), XGBoost and CatBoost algorithms for building an ensemble learning (SEL) model to classify coastal waveforms, and further evaluated the performance of three retracking strategies in refining waveforms using Cryosat-2, SARAL, Sentinel-3 altimeters. We compared the estimation accuracy of the coastal water levels between the single altimeter and synergistic multi-altimeter, and combined Breaks for Additive Season and Trend (BFAST), Mann-Kendall mutation test (MK) with Long Short-Term Memory (LSTM) algorithms to track the historical change process of coastal water levels, and predict its future development trend. This paper found that: (1) The SEL algorithm achieved high-precision classification of different coastal waveforms with an average accuracy of 0.959, which outperformed three single machine learning algorithms. (2) Combination of Threshold Retracker and ALES+ Retracker (TR_ALES+) achieved the better retracking quality with an improvement of correlation coefficient (R, 0.089~0.475) and root mean square error (RMSE, 0.008∼ 0.029 m) when comparing to the Threshold Retracker & Primary Peak COG Retracker and Threshold Retracker & Primary Peak Threshold Retracker. (3) The coastal water levels of Cryosat-2, SARAL, Sentinel-3 and multi-altimeter were in good agreement (R>0.66, RMSE<0.135m) with Copernicus Climate Change Service (C3S) water level. (4) The coastal water levels of the Beibu Gulf displayed a slowly rising trend from 2011 to 2021 with an average annual growth rate of 8mm/a, its lowest water level focused on May-August, the peak of water level was in October-November, and the average annual growth rate of water level from 2022-2031 was about 0.6mm/a. These results can provide guidance for scientific monitoring and sustainable management of coastal zones.

Monitoring Wetland Landscape Evolution Using Landsat Time-Series Data: A Case Study of the Nantong Coast, China

Coastal wetlands not only have rich biodiversity and high productivity but also provide important ecological services. The monitoring of landscape changes can provide important support for the sustainable development of coastal zones. Landsat images from 1986 to 2017 were used to interpret the types of coastal wetlands in Nantong. A single dynamic degree and multiple landscape indices were calculated to analyze the rate of change and characteristics of each wetland type. The results demonstrate the following: (1) A Nantong wetland type system was established, which was divided into three major categories and eleven subcategories. (2) In general, natural wetlands, such as thatched and Suaedasalsa marshes, were extremely reduced, while artificial wetlands and non-wetlands with high human activity, such as breeding ponds, farmland, and construction land, increased significantly. (3) In the past 30 years, due to the influence of environmental pressures, such as population growth, land demand, and economic development, the major influencing factors of local landscape change have shifted from natural geographical factors to human activities and economic as well as social factors. Remote sensing wetland interpretation can be very helpful in monitoring the dynamic changes in coastal wetlands and can provide scientific support for the sustainable management of coastal zones.

Flood Resilience, Viability, and Growth Response to Seawater Immersion of Bermudagrass (Cynodon dactylon (L.) Pers.)

A holistic approach to sustainable coastal zone management assigns the development of nature-based and low-cost strategies for coastal protection during extreme meteorological events. This determines the growing interest in plant species with high salt tolerance, and the study of their flood resilience in order to determine their capacity for flooding and erosion control. Bermudagrass (Cynodon dactylon (L.) Pers.), with its vast rhizome system, has the major characteristic features of useful plant stabilisers of coastal sand dunes. This study aims to define the effects of flooding stress caused by storms on viability, survival ability, and growth response of bermudagrass in flooding simulations in order to define its flooding resilience. C. dactylon showed high resilience and tolerance to salt from seawater during flooding simulations. The Critical Decomposition Time of C. dactylon is estimated at 144 h, which is more than the maximum-duration flood recorded for the Bulgarian Black Sea Coast. Untreated rhizomes showed less viability than those treated with seawater in flooding simulations. Changes in resistance, viability, biomass, and vegetative allocation were more significant, with the water as an influencing factor. The temperature of seawater and duration of submergence had no significant effect. As a median value species between psammophytes from the Poaceae family and the Cyperaceae family, bermudagrass can be used as a model plant in flooding simulations.

Delineation of sensitive coastal zone of northern Ramanathapuram coast, Tamilnadu, India, using a GIS approach

This research aims to assess the sensitive coastal zones by analyzing the shoreline changes such as accretion and erosion in the eastern coastal part of Ramanathapuram District, Tamil Nadu, India. The study focused on Mandapam, Pirappanvalsai, Enmanamcondam, Nagachi, Terbogi, Athyuthu, Chitrakkottai, Pathengal, Attangarai, Alagankulam, and Devipattinam villages. Some of these areas are distinguished as highly sensitive ecological zone. The erosion of an area leads to irreplaceable disturbances to nature. Hence, erosion and accretion studies are top priorities when studying the coastal area. In addition to GIS technology, which has been widely used in the past 20 years, the End Point Rate (EPR) and Linear Regression Rate (LRR) analyses were conducted to better understand the shoreline changes. The stability of the coastal region was analyzed by observing the slope variations of the beach during the profile survey. In the study, we analyzed that the Quaternary deposits of sand are the dominant geological feature of the study area. Coral reefs and salt pans are highly distributed along the coastal stretch. The coast of Mandapam village has been detected as a highly sensitive region, with an average erosion rate of −3.1 m/yr and an average accretion rate of 1.22 m/yr, resulting in high erosion and low accretion. The coast is a steep coast with an average slope angle of 0.24°. This study provides insight into sustainable coastal zone management.

Emerging Downdrift Erosion by Twin Long-Range Jetties on an Open Mesotidal Muddy Coast, China

Downdrift shoreline recession associated with the construction of a shore-crossing hard structure represents one of coastal erosional hotspots that must be addressed for an integrated, sustainable coastal zone management. To prevent siltation within the navigation channel, two rubber-mounted jetties were installed at the Sheyang River mouth on the open mesotidal muddy coast in Jiangsu province, China, in October 2013. The north jetty is 7.9 km long, while the south jetty is 7.8 km long. The net longshore sediment transport is from the north to the south due to flood-tide dominance. As disclosed by high-resolution satellite images, a 36-km-long downdrift shoreline stretch had experienced remarkable retreats at alongshore varying rates by March 2019. The eroding shoreline planform does not resemble a classic “S” shape, a crescentic shape, or a parabolic shape but an irregularly indented curved shape. Transect topographic survey also reveals an almost immediate response of the downdrift coast from the original accretionary scenery to an erosional regime, with the erosion front translocating downcoast at a much faster speed than a normal speed of 1–1.5 km/yr. Using FVCOM and SWAN, 2DH process-based numerical simulations are performed to simulate the flow, the sediment transport, and the yearly-magnitude accretion/erosion distribution in the jetty-affected area by a representative tidal force and an annual-magnitude wave force. The results demonstrate that the reciprocal tidal flow is predominantly responsible for the muddy sediment accretions at downdrift intertidal and surf zones shallower than a 4.0-m isobath, whereas big wind waves play a decisive role in triggering and developing the downdrift erosional process. The predicted spatial extent of the downdrift erosional segment matches closely the actual eroding front. The loss of the net annual longshore sediment transport volume, i.e., 3.08 million m3 due to the blockage by the twin jetties is recovered from a much larger spatial extent than the 36-km-long retreating shoreline stretch. With regard to the Bruun model, the one-line model, the headland-bay model, and the 2DH numerical model, the potential maximum recession length and the planform shape of the downdrift erosional shoreline arc are further elaborated to gain new insights into the spatial and temporal impact of a hard structure on the adjacent shoreline and flat (beach).

Factors influencing coastal land cover change and corresponding impact on habitat quality in the North-western Coastline of Guinea-Bissau (NC-GB)

Coastal zones are transitional and inter-connected areas between marine and terrestrial ecosystems. Changes in coastal zones will inevitably have implications on coastal habitat quality which provide appropriate conditions for individual and population to live. Habitat quality is degraded either directly or indirectly as a result of land use increases and the intensification of natural hazards. Moreover, quantitative assessment studies to clarify the impact of coastal land cover change on habitat quality have rarely been implemented. Therefore, we first combined the Habitat Quality Model (HQM) with Digital Shoreline Analysis System (DSAS), to investigate the main factors influencing coastal habitat quality change and estimate the habitat degradation index over the four decades in the NC-GB. The results indicated that, between 1979 and 2020 a complicated series of land cover change occurred in the study area, affecting a total area of nearly 377 km2. All the coastal land cover displayed geomorphological alteration of 12.52% erosion, 39.61% accretion and moderate changes of 47.74%. The conversion of saltmarsh, coastal forest and mangroves into cultivated, residential and sand dune were the main responsible for coastal habitat quality change. Saltmarsh was the most degraded with 38% in 1979 to 51% in 2020, followed by coastal forests 25%–37% degraded. Mangroves showed significant improvement of 12%–5% degraded, respectively. The study concluded that anthropogenic factors were the main processes driving change in the quality of coastal habitats. Therefore, measures should be taken to control the two main land conversion such as cultivation and residential. These findings support the clear definition of priorities for sustainable coastal zone management, in order to decrease vulnerability and increase resilience of the coastal communities.

Coastal landform changes on the east coast of Sri Lanka using remote sensing and geographic information system (GIS) techniques

Coastal landforms are constantly changed due to both natural and anthropogenic forces. An attempt is made to analyze short-term coastal landform changes on the east coast of Sri Lanka using remote sensing and geographic information system (GIS) techniques. Such landform changes can be classified as either negative (e.g. erosion) or positive (e.g. accretion) impacts. Surface reflectance images of Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) were analyzed for extracting spatial and temporal changes, based on cross-shore profile analysis and geomorphic change detection. In this study, we developed a novel script model built-in ArcMap for image pre-processing and processing. This model covers six functioning areas of mosaic, land feature extraction, cloud layer generation, vectorization, cloud masking, and smoothing. The green band and mid-infrared images were selected due to the largest reflectance difference between water and non-water bodies. These images have proceeded with modified normalized difference water index (i.e. algorithm of the script model for extracting water and land features). We also quantified the landform changes such as net shoreline movement, shoreline change envelope, endpoint rate, and linear regression rate, using a digital shoreline analysis system (i.e. statistical software combined with ArcMap™). Therefore, landform changes were classified as erosion (>–2.5 m/year), minor seasonal changes (−2.5 m/year to +2.5 m/year), accretion (>+2.5 m/year), based on the annual variations of endpoint rate (i.e. the distance between the oldest and the youngest shorelines to particular time interval). We visualized spatial and temporal coastal landform changes along the east of Sri Lanka, and also identified short-term landform change drives such as tsunamis, cyclones, and anthropogenic activities (e.g. engineering constructions). These landform changes were observed with a global positioning system (GPS)-based field survey. The understanding of such impacts can be directly applied to sustainable coastal zone management.

ENVIRONMENTAL IMPACTS OF SHRIMP FARMING IN CHAKARIA UPAZILA OF COX’S BAZAR IN BANGLADESH

Aquaculture has become one of the fastest-growing economic sub-sectors of the Bangladesh economy, providing protein-rich food, the source of employment and foreign currency earnings. Therefore, shrimp farming is very much common in the brackish water which affects the coastal natural ecosystem and livelihood of the coastal communities, prticularly in Chakaria Upazila of Cox’s Bazar district. Due to rapid and unplanned growth of this farming, socio-ecological systesms has been changing. This study aims to assess shrimp farming’s environmental, social, and economic impacts in Chakaria upazila in Bangladesh. Soil sample was collected to determine the environmental impacts of shrimp farming. Besides, we selected the shrimp farmers, rice producers, and alternative shrimp-rice producers through simple random sampling. Purposive sampling was conducted to choose the other stakeholders. A semi-structured questionnaire was developed for interviewing different stakeholders. We found that, because of the high economic benefit, high production rate in short time, and availability of brackish water, the people in this Upazila are attracted to continue the shrimp farming. As a result, mangrove forest and agricultural land converted into shrimp farming. Our soil analysis showed that organic matter content in was low (0.25-3.56%). In addition to this, most people suffer from water-borne diseases during the flooding period. We also found clear evidene of shortage of safe drinking water due to salinity intrusion in grounwater. The tendency of raring livestock such as cow, goat, and buffalo decreased due to insufficient grazing land. The study also revealed that some internal conflicts exist between different stakeholders in Chakararia Upazila. Most local shrimp fry collectors collect fry from the tidal river and use an unscientific traditional method which was harmful for the other aquatic fish population. Poor quality of larvae supply from hatchery caused various diseases in cultivated ghers and ponds. The findings from this study provide useful information for sustainable coastal zone management in Bangladesh to build a more resilient coastal communities.

Tropical Coastal Land-Use and Land Cover Changes Impact on Ecosystem Service Value during Rapid Urbanization of Benin, West Africa.

West African coastal areas including the Beninese coastal zones have undergone an intensification of socio-economic activity in the last few decades that has been strongly driven by the effects of rapid urbanization. This has led to land-use and land cover changes that represent threats to the sustainability of various ecosystem functions. Such dynamics of land use and land cover changes pose challenges to coastal zone management. Correct assessment is vital for policymakers and planners to ensure efficient and sustainable use of the coastal ecosystem services, and it remains crucial to achieving sustainable coastal zone management. This study examines changes in land-use and land cover (LULC) and their impacts on ecosystem services value (ESV) fluctuations in the tropical coastal region of Benin, West Africa. We employed Globe Land 30 image data for the years 2010 and 2020, and the ESV fluctuations during the study period were evaluated using the benefit transfer approach (BTA) with corresponding local coefficients values and the GIS techniques. The results reveal that (1) in the current urbanizing coastal area, the LULC types have changed significantly, with obvious reductions in forest land and waterbodies and a considerable increase in artificial surfaces; (2) the total ESV decreased by 8.51% from USD 7.1557 million in 2010 to USD 6.5941 million in 2020; (3) the intensity of LULC in the coastal region has increased over the last 10 years; (4) regions with high land-use intensity have a high rate of ESV change; and (5) provisioning services are the greatest contributors of ESV (51% in 2010; 41% in 2020), followed by supporting services (37% in 2010; 35% in 2020) and regulating services (25% in 2010; 30% in 2020). Uncontrolled changes in LULC from forest land and waterbodies are the main causes of the loss in total ESV, necessitating urgent measures to improve the coastal ecosystem sustainability through effective planning and policies.

Development of a Shoreline Detection Method Using an Artificial Neural Network Based on Satellite SAR Imagery

Monitoring shoreline change is one of the essential tasks for sustainable coastal zone management. Due to its wide coverage and relatively high spatiotemporal monitoring resolutions, satellite imagery based on synthetic aperture radar (SAR) is considered a promising data source for shoreline monitoring. In this study, we developed a robust shoreline detection method based on satellite SAR imagery using an artificial neural network (NN). The method uses the feedforward NN to classify the pixels of SAR imagery into two categories, land and sea. The shoreline location is then determined as a boundary of these two groups of classified pixels. To enhance the performance of the present NN for land–sea classification, we introduced two different approaches in the settings of the input layer that account not only for the local characteristics of pixels but also for the spatial pixel patterns with a certain distance from the target pixel. Two different approaches were tested against SAR images, which were not used for model training, and the results showed classification accuracies higher than 95% in most SAR images. The extracted shorelines were compared with those obtained from eye detection. We found that the root mean square errors of the shoreline position were generally less than around 15 m. The developed method was further applied to two long coasts. The relatively high accuracy and low computational cost support the advantages of the present method for shoreline detection and monitoring. It should also be highlighted that the present method is calibration-free, and has robust applicability to the shoreline with arbitrary angles and profiles.