Shoreline Change Rate of the Barrier Islands in Nakdong River Estuary over the Southern Part of Korea

2016 ◽  
Vol 75 (sp1) ◽  
pp. 248-252
Author(s):  
Sang-Hun Jeong ◽  
Boo-Keun Khim ◽  
Yeong-Heon Jo ◽  
Beack-Oon Kim ◽  
Sang-Ryong Lee ◽  
...  
Keyword(s):  
River Estuary ◽  
Barrier Islands ◽  
Shoreline Change ◽  
Nakdong River ◽  
Change Rate ◽  
Shoreline Change Rate

scholarly journals Shoreline-change Rates of the Barrier Islands in Nakdong River Estuary Using Aerial Photography and SPOT-5 Image

2013 ◽  
Vol 35 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Sang-Hun Jeong ◽  
Boo-Keun Khim ◽  
Beack-Oon Kim ◽  
Sang-Ryong Lee
Keyword(s):  
Aerial Photography ◽  
River Estuary ◽  
Barrier Islands ◽  
Shoreline Change ◽  
Nakdong River ◽  
Spot 5

scholarly journals Shoreline Change and its Impact on Land use Pattern and Vice Versa – A Critical Analysis in and Around Digha Area between 2000 and 2018 using Geospatial Techniques

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Anindita Nath ◽  
Bappaditya Koley ◽  
Subhajit Saraswati ◽  
Basudeb Bhatta ◽  
Bidhan Chandra Ray
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Shallow Water ◽  
High Tide ◽  
Shoreline Change ◽  
Sustainable Land Use ◽  
Mitigation Measures ◽  
Land Use Pattern ◽  
Change Rate ◽  
Shoreline Change Rate

The shoreline is a very unpredictable, uncertain, and forever changing landscape for any coastal process. Due to erosional and accretional activities, the shoreline has continuously fluctuated with the continual process of waves and tides. Shore boundaries are determined by the shoreline at its furthest towards the sea (low tide) and extreme towards land (high tide). The present research aimed to identify the temporal alterations of shoreline and changes in land-cover between the areas of Rasulpur to Subarnarekha estuary, east coast of India with 70.04 km length of shoreline. An area amounting to 143sq.km had been selected for showing the land-cover changing and this area had witnessed the rapid growth of population and increasing industrial activities causing an unsurpassable impact on the environment. The present study used three multi dated imageries for land use/ land cover (LULC) map and seven multi-resolution satellite images were applied to estimate the long-term shoreline change rate by dividing the coastal area into three “littoral zones” (LZ). The Digital shoreline analysis system (DSAS) was applied to identify the shoreline change rate of the year 2000 to 2018. Several statistical methods, linear regression rate (LRR), net shoreline movement (NSM), End Point Rate (EPR) were used to find out the erosion and accretion rate. The result showed that maximum erosion had been found in LZ III, rate of -2.22 m/year. Maximum accretion had been identified in LZ I, at the rate of 35.5 m/year. The LULC showed that maximum vegetation area had been decreased in the year of 2010 (14.21sq.km) but 38.96sq.km vegetation area had increased in 2018. The prominent increase had been identified in built up and shallow water. Built up had been expanded from 25.59sq.km (2000) to 41.26sq.km (2018). Shallow water was increased from 5.53sq.km (2000) to 18.90sq.km (2018). Sand and soil showed a decreasing pattern from 2000 – 2018. The outcome acquired from the present study will play a significant role to estimate the shoreline migration rate and will be helpful for sustainable land use management. The shoreline change rate will be also useful for coastal planners to adopt mitigation measures.

scholarly journals The Predictive Accuracy of Shoreline Change Rate Methods and Alongshore Beach Variation on Maui, Hawaii

2007 ◽  
Vol 231 ◽  
pp. 87-105 ◽  
Author(s):  
Ayesha S. Genz ◽  
Charles H. Fletcher ◽  
Robert A. Dunn ◽  
L. Neil Frazer ◽  
John J. Rooney
Keyword(s):  
Predictive Accuracy ◽  
Shoreline Change ◽  
Change Rate ◽  
Shoreline Change Rate

scholarly journals Coastal Vulnerability Mapping using Remote Sensing and GIS Techniques in Tuticorin Coast of Tamil Nadu, India

2019 ◽  
pp. 1-12
Author(s):  
B. Santhosh Kumar ◽  
A. Balukkarasu ◽  
K. Tamilarasan
Keyword(s):  
Satellite Data ◽  
Tamil Nadu ◽  
Shoreline Change ◽  
The United States ◽  
Disaster Mitigation ◽  
United States Geological Survey ◽  
Coastal Vulnerability ◽  
Change Rate ◽  
Shoreline Change Rate ◽  
Erosion And Accretion

The southern part of the Indian peninsula of Tamil Nadu coast is potentially more vulnerable to hazards. This research aims to classify the coastal vulnerable zones of the Tuticorin, Tamil Nadu using Coastal Vulnerability Index (CVI). The multi-spectral satellite data of Landsat series was used for shoreline change analysis from 1978 to 2017. The Digital Shoreline Analysis System (DSAS) software extension was used to calculate the shoreline rate-of-change statistics from multiple historic shoreline positions developed by the United States Geological Survey. The study reveals significant erosion and accretion demarcated based on DSAS computed values along the coastal stretch. The six physical variables characterizing the vulnerability of the coast, including the geomorphology, shoreline change rate (m/yr), coastal slope (deg), relative sea-level change (mm/yr), mean wave height (m) and mean tide range (m). The geomorphology map was created using Landsat OLI satellite data in 1: 50,000 scale. The Shoreline change rate was calculated using temporal satellite data. Based on the CVI value, low vulnerable to very high vulnerable areas were identified. Besides, Vembar, Periyasamypuram, Vaippar, Kallurni, Pattanamarudur areas were identified in erosion. The Muttayyapuram coast has accretion by the consequence of sediment transport from the Thamiraparani estuary. The coastal zones are highly fragile for dynamic nature and resource. The sources of anthropogenic and natural processes are accelerating the erosion and accretion along the coast. Hence the vulnerability map prepared for the southeast coast of India and it can be most helpful for stakeholders and future coastal disaster mitigation and management.

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