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Title
Abstract
Introduction
Study Area-Karwar
Methodology
Shoreline Change Detection Analysis
Results and Discussion
References
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Earth Sciences
Geology

Shoreline analysis using Landsat-8 satellite image

Profile image of basavanand dodamanibasavanand dodamani

2018, ISH Journal of Hydraulic Engineering

https://doi.org/10.1080/09715010.2018.1556569
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10 pages

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Abstract

The shoreline is a boundary between wet and dry part of the beach, and it is dynamic in nature. Natural and human factors are always influencing shoreline configuration. One of the important natural events which are responsible for the shoreline configuration along the Karnataka coast is southwest monsoon, and hence there is a change in shoreline position between pre-and post-monsoon. For the present research work, Karwar beach with two beaches, Rabindranath Tagore beach and Devabagh beach along Karnataka coast, West coast of India were selected as study area. Landsat-8 satellite images for the years 2013-2017 were used in the present study and processed for May and October of every year, using ERDAS imagine 2014 and ArcGIS 10.3 tools to generate shoreline configuration maps. Finally, the comparison was made between 2013 and 2017 years, and the results indicate that the Devbagh beach during pre-monsoon season has an average shoreline change rate of −7.54 m/yr (EPR) and −5.57 m/yr (LRR) and during postmonsoon season it is 0.34 m/yr (EPR) and −0.46 m/yr (LRR). Similarly, Rabindranath Tagore beach during pre-monsoon seasons has an average shoreline change rate of 0.004 m/yr (EPR) and 1.67 m/yr (LRR), and in post-monsoon season, it is −5.77 m/yr (EPR) and −6.55 m/yr (LRR) respectively. The total uncertainty error was estimated and found to be AE 5.00 m/yr.

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    Soil erosion is considered as one of the major causes of land degradation and reservoir sedimentation. Therefore, modeling of runoff and sediment yield at the catchment level is necessary. In this study, an attempt was made to simulate runoff and sediment yield of hydrologically similar basins of Kali River and Aghanashini River which joins west coast of India. A conceptual, continuous time and semidistributed SWAT2012 (Soil and Water Assessment Tool) model was selected for the modeling purpose. For the last two decades, Kali river basin experienced a very high rate of soil erosion due to various developmental activities in the basin. Therefore, it is essential to identify the soil loss within the basin. There are five dams constructed across the Kali river basin for various purposes. The presence of these reservoirs regulates stream flow and thus sediment load in the basin. However, the free movement of water across the Aghanashini river catchment leads to the unobstructed passage of sediments to the river mouth, as the catchment is not disturbed by the reservoir. This study deals with the impacts of the dams on stream flow, sediment load and the response of shoreline. Digital Shoreline Analysis System (DSAS) tool was used to analyze the shoreline changes. Simulated and observed values of runoff are compared, and calibration and validation were done for the basins using SWAT-CUP. Analysis of calibration and validation results shows that the model has a good performance. Therefore, the SWAT model can be used to conduct further studies in these study areas. Sediment yield obtained at the catchment outlet was 1.07 t/ha/year and 4.58 t/ha/year for Kali and Aghanashini basins, respectively. Less

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    Bibliometric Analysis of Data Sources and Tools for Shoreline Change Analysis and Detection
    Johnson Ankrah

    Sustainability

    The world has a long record of shoreline and related erosion problems due to the impacts of climate change/variability in sea level rise. This has made coastal systems and large inland water environments vulnerable, thereby activating research concern globally. This study is a bibliometric analysis of the global scientific production of data sources and tools for shoreline change analysis and detection. The bibliometric mapping method (bibliometric R and VOSviewer package) was utilized to analyze 1578 scientific documents (1968–2022) retrieved from Scopus and Web of Science databases. There is a chance that in the selection process one or more important scientific papers might be omitted due to the selection criteria. Thus, there could be a bias in the present results due to the search criteria here employed. The results revealed that the U.S.A. is the country with the most scientific production (16.9%) on the subject. Again, more country collaborations exist among the developed cou...

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

    Sustainability

    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...

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    Mapping Forest Cover and Estimating Soil Organic Matter by GIS-Data and an Empirical Model at the Subnational Level in Mexico
    Rosalía Castelán

    Forests

    Forests play an essential role in climate change as they are the terrestrial ecosystems that store the highest C content in their soils and biomass. Despite this, the lack of information at the subnational level hinders their proper management and conservation. This study aimed to identify the extension and distribution of forests and to develop an empirical model for the spatial prediction of soil organic matter (SOM) in Ixtacamaxtitlan, Puebla, Mexico, based on environmental variables generated through Geographical Information Systems. A supervised classification in Landsat 8 images was used to define the forest cover, and environmental variables related to topography, climate and vegetation were generated. Finally, a Multiple Linear Regression model validated with the leave-one-out cross-validation method was used to examine the relationships between the covariates and the SOM and estimate its content in forest. The results show that the forest cover extension is 41%, with an ove...

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