Long-and short-term variations in shore morphology of Van Island in gulf of Mannar using remote sensing images and DSAS analysis

David, T. Immanuvel; Mukesh, M. V.; Kumaravel, S.; Sabeen, H. M.

doi:10.1007/s12517-016-2772-4

Cited by 14 publications

(1 citation statement)

References 15 publications

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“…The TM, ETM+, and OLI sensors offer a medium spatial resolution of 30 m and combined repetitive coverage of 8 days [45][46][47]. The integration of Landsat images with GIS techniques and shoreline analysis tools such as the Digital Shoreline Analysis System (DSAS) has been broadly used to analyze and monitor shoreline changes in many parts of the world including the Mediterranean coast [45], the Gulf of Mannar [48], and the Eastern Coast of Algeria [49]. This tool provides an automated method for the calculation of rate-of-change statistics and allows for the assessment of their robustness [35,50].…”

Section: Introductionmentioning

confidence: 99%

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

Zoysa,

Basnayake,

Samarasinghe

et al. 2023

Sustainability

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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.

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