Assessing Historical Shoreline Change and Forecasting Future Trends Along Monrovia’s Coastline, Liberia

Geospatial analysis of shoreline and areal dynamics in the Ganges deltaic island of Bangladesh using the GIS-DSAS technique

The Prokopos Lagoon is part of the Kotychi Strofilias National Wetlands Park, which is supervised by the Ministry of Environment, Energy and Climate Change of Greece. The lagoon is situated at the northwestern coast of the Peloponnese and is protected by the Ramsar Convention. It is an important ecosystem with ecological services providing habitats for many plants and animals and essential goods and services for humans as well. No previous relevant studies for the wider wetland area are available, and given that lagoons are important ecosystems, their diachronic evolution should be under constant monitoring. Using remote sensing techniques in Geographic Information System (GIS) environment, alterations in critical parameters could be measured and applied for the protection of the area. The present study examines the spatiotemporal changes of the water extent of the Prokopos Lagoon, estimating landscape metrics and several morphometric parameters and indices related to the geomorphological features of the lagoon for the 1945–2021 period. Moreover, the adjacent shoreline was studied for each past decade evolution from 1945 to present, and it is discussed to whether there is a relationship between shoreline changes and the lagoon. High resolution satellite images and air photos at scale 1:30,000 were used to digitize the shorelines and the polygons of the lagoon’s surface. Linear Regression Rates (LRR), Net Shoreline Movement (NSM), End Point Rate (EPR) and Shoreline Change Envelope (SCE) provided by the Digital Shoreline Analysis System (DSAS) were used to determine the changes. Finally, future shoreline positions for 2021 and 2031 are estimated, while based on statistic models, we found that in the coastal area, the erosion–accretion cycle is predicted to be completed in 2031, after almost 86 years since 1945.

Shoreline change assessment of Indus delta using GIS-DSAS and satellite data

Over the last decades, wave energy and coastal currents have continuously reshaped the northern coast of Eretan, Indramayu Regency, along the Java Sea. This study analyzes spatiotemporal shoreline changes and tidal conditions from 1994 to 2024 using a quantitative approach. Landsat satellite imagery is processed through the Google Earth Engine (GEE) platform and shoreline displacement is quantified with the Digital Shoreline Analysis System (DSAS), applying the End Point Rate (EPR) and Net Shoreline Movement (NSM) methods. The results show that coastal abrasion dominates the region, retreating the shoreline by an average of - 12.88933 m, with an average rate of -235.208 m/yr. In contrast, localized accretion is identified that advances the shoreline by an average of 22.87667 m/yr, with a rate of 604.1829 m/yr. These findings demonstrate the geomorphic instability of the Eretan coastline and offer a scientific basis for designing integrated coastal management strategies and regional policies in northern Indramayu.

This study was performed along the shorelines of Lake Salda in Turkey during the elapsed period from 1975 to 2019 in order to detect shoreline changes. Within this framework, geographic information system, digital shoreline analysis system, Modified Normalized Difference Water Index, and multi-temporal satellite images were utilized. The measurement of shoreline displacement was mainly divided into six analysis regions. In digital shoreline analysis system, several statistical parameters such as end point rate, linear regression rate, shoreline change envelope, and net shoreline movement were computed to measure the rates of shoreline displacement in terms of erosion and accretion. The maximum shoreline change between 1975 and 2019 was determined as 556.45 m by shoreline change envelope parameter. The maximum shoreline change was 16.35 m/year by end point rate parameter and 12.91 m/year by linear regression rate parameter. While erosion has been observed in 3rd, 4th and 6th segments, accretion has been observed in other segments. When all the transects were taken into consideration, an accretion observed. The results indicate that there is a decrease in area of the lake. Experiment results show that integrated use of multi-temporal satellite images and statistical parameters are very effective and useful for shoreline change analysis. It is thought that the structures such as irrigation pond and dam that are built on the streams that recharge the lake and average rainfall and average temperature conditions are the main reasons of the fluctuations and changes in the shorelines.

Lee, Y.K.; Eom, J.; Do, J.D.; Kim, B.J., and Ryu, J.H., 2019. Shoreline movement monitoring and geomorphologic changes of beaches using lidar UAVs images on the coast of the East Sea, Korea. In: Jung, H.S.; Lee, S.; Ryu, J.H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 409-414. Coconut Creek (Florida), ISSN 0749-0208.Sandy beaches are important habitats for coastal organisms and act as buffer zones during coastal disasters. Most of the coastal zone along the eastern coast of Korea consists of sandy beaches. However, beach erosion has been accelerating in recent years. In this study, shoreline movement and topographical changes were analyzed in Uljin-gun on the East Sea coast of Korea using remotely sensed data from airborne Lidar and unmanned aerial vehicles (UAVs). The shoreline changes extracted were statistically quantified using net shoreline movement (NSM) and linear regression rate (LRR) in the digital shoreline analysis system (DSAS). Morphological changes were quantified based on a comparison of the digital surface maps (DSM) generated by Lidar and UAVs. Shoreline movement and morphological changes were analyzed over the short-term (February 2016 to February 2019) and long-term (June 2008 to June 2018). Seaward migration was dominant for 7.02 m, 1.64 m, and 9.22 m along three defined subareas over the long-term. Over the short-term, LRR results showed landward migration as 0.7 m and 1.10 m in two of the subareas. Morphological change showed erosion and accretion occurring at approximately 0.08 m3 and 0.42 m3, respectively. This reverse trend indicates that a detailed DSM can detect volumetric change due to relocation of the sediment around artificial construction.

This study concerned the assessment of changes in the coastline of Kavvayi beach and its nine islands in a tropical coastal wetland using remote sensing (RS) data and geographic information systems (GIS), as this sedimentary environment is still poorly characterized. The satellite data used were from LANDSAT images (30 m spatial resolution) (MSS—volume 5, TM, ETM, and ETM+ volume 6) for the period of the last 25 years (1990 to 2014). Band 5 in Landsat (MSS) and band 6 (ETM 24- OLI) were used because they clearly distinguish the boundaries between land and water. The Digital Shoreline Analysis System (DSAS) was used to understand shoreline changes such as erosion and accretion processes by calculating the net shift in shoreline (NSM), end point rate (EPR), and linear regression rate (LRR) for the period of 25 years. The results showed significant changes over the studied period, leading to erosion and accretion. Coastal processes had an impact in the period from 2005 to 2014, leading to the development of a new island in the northern part of the wetland due to the construction of a new breakwater. In addition, the causes of the shoreline changes on the islands, including anomalies and the formation of new structures in the wetland, were investigated and discussed. These analyses confirmed that the islands studied were subjected to marine transgression and vice versa. Among this, Kavvayi was subject to marine transgression over the period, and Achanthurti Island showed erosion to a lesser extent. This can be considered as a feature of wetlands in combating sea level rise at local levels and possible reasons for the changes along with the coastal zone management plans were also discussed.

Shoreline changes and its impact on the mangrove ecosystems of some islands of Indian Sundarbans, North-East coast of India

Assessment and prediction of shoreline change using multi-temporal satellite images and statistics: Case study of Damietta coast, Egypt

Exploring shoreline changes and their implications in coastal communities using GIS and remote sensing techniques: The case of eastern beaches of Unguja island, Tanzania

Assessing geomorphological changes in coastal lagoon inlet using geospatial tools: A case study Moulay Bousselham lagoon, Morocco

Climate change and rising sea level is transforming global coastlines as corroborated by significant changes in the position of shoreline witnessed through coastal erosion or accretion. Andhra Pradesh has the second longest (972 km) coastline in India. The present study analyzed shoreline change and its future prediction by employing satellite-derived data and geographic information system. End point rate (EPR) and linear regression rate (LRR) statistical tools in the Digital Shoreline Analysis System (DSAS) were used to estimate historical shoreline change rate between 1973 and 2015. Erosion and accretion of the coastline were delineated from Landsat satellite images for 1973, 1980, 1990, 2000, 2010, and 2015; subsequently, shoreline is predicted for short-term (2025) and long-term (2050) periods. The study showcased that the river mouths of Krishna and Godavari experienced higher rate of change in shoreline position influenced by the deltaic environment and fluvial processes. LRR model prediction depicts the average rate of shoreline change during 2015–2025 will be −4.64 m, while between 2015 and 2050 it will increase to −16.25 m. The study observed that the error between predicted and actual shoreline is higher in the river mouth and deltaic plains. Predicted shoreline position will provide baseline information for adaptation strategies and policy framework for coastal management.

The paper deals with a combination of the Digital Shoreline Analysis System (DSAS) and remote sensing, studying historical mangrove shoreline changes and mangrove zoning in the GiaoThuy coastal area of the Nam Dinh province, Vietnam. The results show an over-all mangrove area increase of 2,487 hectares during the years 2005-2014. This dynamics results from both degradation and increase of the mangroves. The calculated degradation rate is 1.41 m yr-1, and the growth rate is 1.26 m yr-1 on average. 4 different mangrove zones were delineated based on the End Point Rate (EPR) values of DSAS transects. The differential evolution of the mangroves in these zones is driven by socio-economic and environmental factors. The results contribute to practices of mangrove planning and management in a coastal area. Furthermore, historical mangrove shoreline change provides indicators to monitor coastal environmental changes for global warming, climate change, storm effects, sea level change, pollution, and sedimentation rates.References Alongi, D.M., 2008. Mangrove forests: Resilience, protection from tsunamis, and responses to global climate change. Estuarine, Coastal and Shelf Science, 76(1), 1-13. Cohen, M.C.L., Lara R.J., 2003. Temporal changes of mangrove vegetation boundaries in Amazonia: Application of GIS and remote sensing techniques. Wetland Ecology Management 11, 223-231. Ellison, J., 2000. How South Pacific mangroves may respond to predicted climate change and sea level rise. In: Gillespie A. and Burns W. (Eds.). Climate change in the South Pacific: Impacts and responses in Australia, New Zealand, and small islands states. Dordrecht, Netherlands: Kluwer Academic Publishers (Chapter 15), 289-301. Hegde, A.V., Akshaya B.J., 2015. Shoreline transformation study of Karnataka Coast: Geospatial Approach. Aquatic Procedia 4, 151-156. Lewis, R.R., 2005. Ecological engineering for successful management and restoration of mangrove forests. Ecological Engineering, 24(4SI), 403-418. Moussaid, J., Fora A.A., Zourarah B., Maanan M., Maanan M., 2015. Using automatic computation to analyze the rate of shoreline change on the Kenitra coast, Morocco.Ocean Engineering, 102(1), 71-77. Nguyen Hai Hoa, McAlpine C., Pullar D., Leisz S.J., Galina G., 2015. Drivers of coastal shoreline change: case study of Hon Dat coast, Kien Giang, Vietnam. Environmental Management, 55(5), 1093-1108. Oyedotun, T.D.T., 2014. Shoreline Geometry: DSAS as a tool for historical trend analysis. Geomorphological Techniques, Chapter 3(2.2), British Society for Geomorphology, 1-12. Pham Quang Son , Nguyen Duc Anh, 2016. Evolution of the coastal zone in Hai Hau district (Nam Dinh province) and nearest region over the last 100 years based on analysis topographic maps and multi-temporal remote sensing data. Vietnam Journal of Earth Sciences, 38(1), 118-130 (in Vietnamese). Rebelo, L.M., Finlayson C.M., Nagabhatla N., 2009. Remote sensing and GIS for wetland inventory, mapping and change analysis. Environmental Management, 90, 2144-2153. Sathirathai, S., Barbier E.B., 2001. Valuing mangrove conservation in southern Thailand. Contemporary Economic Policy, 19(2), 109-122. Sheik, M., Chandrasekar, 2011. A shoreline change analysis along the coast between Kanyakumari and Tuticorin, India, using digital shoreline analysis system. Geo-spatial Information Science, 14(4), 282. Thieler, E.R., Himmelstoss E.A., Zichichi J.L., Ergul A., 2009. Digital Shoreline Analysis System (DSAS) version 4.0 - An ArcGIS extension for calculating shoreline change.U.S. Geological Survey Open-File Report 2008-1278. Dang Van To, Phan Thi Phuong Thao, 2008. A shoreline analysis using DSAS in Nam Dinh coastal area. GeoInformatics, 4(1), 37-42. Tran Thi V., Xuan A Tien Thi., Phan Nguyen Hong, Dahdouh-Guebas F., Koedam N. , 2014. Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam. Biogeosciences ,11, 3781-3795. Vu Van Loi, 2016. Sedimentary facies and engineering geological characteristics of Holocene deposits in the coastal area of Tien Lang district, Hai Phong city. Vietnam Journal of Earth Sciences, 38(1), 108-117.

Jeong, S.H.; Khim, B.K..; Jo, Y.H., Kim, B.O., Lee, S.H. and Park, K.S., 2016. Shoreline change rate of the barrier islands in Nakdong River Estuary over the southern part of Korea. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 248–252. Coconut Creek (Florida), ISSN 0749-0208. Shoreline data of the barrier islands in the Nakdong River Estuary in Korea for the last three decades were assembled using six sets of aerial photographs and seven sets of satellite images. Canny Algorithm was applied to untreated data in order to obtain a wet-dry boundary as a proxy shoreline. Digital Shoreline Analysis System (DSAS 4.0) was used to estimate the rate of shoreline changes in terms of three statistical variables; End Point Rate (EPR), Linear Regression Rate (LRR) and Least Median of Squares (LMS). Based on Digital Shoreline Analysis, shoreline cha...

A Quang Nam coastline, located in the central of Vietnam, has been strongly affected by severe erosion and accretion due to climate change and human activities. Thus, understanding the causes and mechanisms of coastal morphology changes is essential to offer optimal coastal management and protection solutions. In this research, the Digital Shoreline Analysis System (DSAS) technique developed by the United States Geological Survey was adopted to calculate rate-of-change statistics from multiple historical coastline positions of Quang Nam province extracted from satellite images, i.e., Landsat and Sentinel images from 1990 to 2019. The coastal dynamic was digitized, visualized, and compared by two statistical parameters provided in DSAS, namely End Point Rate (EPR) and Linear Regression Rate (LRR). The final results reveal that the Quang Nam coast experienced remarkable phenomena of erosion and accumulation over the past three decades. The total number of erosional and accretional transects obtained from the EPR results are 401 and 414, with annual change rates of −1.7 and 0.77 m/year, respectively. The LRR parameter was also considered and illustrated a significant correlation with the EPR, as the obtained R2 value of 0.96. The lowest value of EPR over the period 1990–2019 is −42.4 m/year, highlighting the most significant erosion at the north of Cua Dai estuary, whereas coastline advance is recorded in the south segment. As a result, this study’s outcomes provide helpful information for better and sustainable coastal management in Quang Nam province of Vietnam.