scholarly journals Estuarine shoreline change analysis along The Ennore river mouth, south east coast of India, using digital shoreline analysis system

2019 ◽  
Vol 10 (3) ◽  
pp. 205-212 ◽  
Author(s):  
Nithu Raj ◽  
B. Gurugnanam ◽  
V. Sudhakar ◽  
Pereira Glitson Francis
Keyword(s):  
East Coast ◽  
River Mouth ◽  
Shoreline Change ◽  
Change Analysis ◽  
East Coast Of India ◽  
Digital Shoreline Analysis System ◽  
Estuarine Shoreline ◽  
Analysis System ◽  
Shoreline Change Analysis

scholarly journals Shoreline Change Analysis of Pontang Cape of Serang Regency of Banten Province

Omni-Akuatika ◽  
2020 ◽  
Vol 16 (2) ◽  
pp. 90
Author(s):  
Abdurrahman Al Farrizi ◽  
Ankiq Taofiqurohman ◽  
Subiyanto Subiyanto
Keyword(s):  
Coastal Zone ◽  
Shoreline Change ◽  
Sand Mining ◽  
Change Analysis ◽  
Factors Affecting ◽  
Shoreline Changes ◽  
Sea Sand ◽  
Digital Shoreline Analysis System ◽  
Analysis System ◽  
Shoreline Change Analysis

Coastal areas, being vulnerable to environmental problems, have one of the most frequent problems which are the change in the shorelines. Shoreline changes, namely abrasions, can cause problems such as land degradations or loss of land in a coastal zone. This problem occurs in many areas, one of which is Pontang Cape. This study aims to determine the distance and rate of shoreline changes that occured in the Cape and its surroundings, as well as explaining the analysis points based on similar studies that had been conducted. This research used ArcMap software and Digital Shoreline Analysis System (DSAS) toolset to determine the distance and rate of shoreline changes for 19 years (1999-2018). Based on the results, there were two shoreline segments where different phenomena of shoreline change took place, namely Banten Bay (accretion) and Pontang Cape-Lontar (abrasion). The most likely causes of changes in the shorelines are sediment runoffs from rivers that lead to bay and sediment transports that affect Banten Bay accretions, while sea sand mining and conversions of mangrove swamps into fishery ponds are factors affecting abrasions in Pontang Cape.Keywords: Abrasion, Accretion, Pontang Cape, Banten Bay, DSAS

scholarly journals SHORELINE CHANGE ANALYSIS USING DIGITAL SHORELINE ANALYSIS SYSTEM METHOD IN SOUTHEAST BALI ISLAND

2021 ◽  
Vol 15 (1) ◽  
pp. 61
Author(s):  
Fajar Lukman Hakim ◽  
Takahiro Osawa ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Wind Speed ◽  
Landsat Imagery ◽  
Shoreline Change ◽  
Change Analysis ◽  
Average Wind Speed ◽  
Shoreline Changes ◽  
Average Value ◽  
Australian Continent ◽  
Digital Shoreline Analysis System ◽  
Analysis System

Based on data from the Bali Public Works Office, in 1987 the abrasion reached 51.50 km, in 2003 it reached 86.5 km, and in 2006 it increased to 140 km. Coastline change research is needed for coastal environmental protection, mitigation, and sustainable development. The objectives of this research are: 1) To predict wind speed and direction for the last 30 years; 2) To measure changes in coastlines over the last 30 years (1989-2020); and 3) Comparison of changes in coastline in 4 periods 1989-2000; 2000-2010; 2010-2020 and 2016-2020. Digital Shoreline Analysis System (DSAS) is a method that works on ArcGIS software which is used to calculate shoreline changes based on time statistics and a geospatial basis. The results of the average EPR in 1989-2000 (Landsat imagery), the average abrasion value was -10.43 m/y and the average accretion value was 2.35 m/y; 2000-2010 the average value of EPR abrasion was -2.61 m/y and the average accretion value of 2.65 m/y; in 2010-2020 the average EPR abrasion value was -2.72 m/y and the average accretion value was 1.60 m/y while in 2016-2020 (Sentinel Image) the average abrasion value was -4.32 m/ y and the average value of its accretion is 4.50 m/y. The conclusion of this study 1) The average wind speed ranges from 0.2 to 6.4 m/s. Wind direction shows the dominance of the Australian continent (southeast). This shows that the east monsoon is more dominant than the west monsoon; 2) In the last 30 years (1989-2020) shoreline changes can be seen from the EPR graph with an average abrasion rate of -6.39 m/ y and an accretion rate of 3.15 m/y; and 3) Identification results from 1989-2000 the villages of Padangbai and Ketewel experienced extreme accretion and high abrasion; 2000-2010 Padangbai and Jumpai villages experienced high accretion and abrasion; In 2010-2020, Jumpai and Gunaksa Villages experienced high abrasion and moderate accretion, while 2016-2020 experienced high abrasion and accretion in Tangkas and Gunaksa Villages. For further research, it can include additional variables such as tide and wave data to get better results.Keywords: DSAS, NSM, EPR, Shoreline Changes, Abrasion, Accretion

Shoreline Change Detection and Forecast along the Yancheng Coast Using a Digital Shoreline Analysis System

Wetlands ◽  
2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dandan Yan ◽  
Xiuying Yao ◽  
Jingtai Li ◽  
Liping Qi ◽  
Zhaoqing Luan
Keyword(s):  
Change Detection ◽  
Shoreline Change ◽  
Digital Shoreline Analysis System ◽  
Analysis System

Rapid detection of changes in the riverbanks of Laigiang river of the South Central Coast Vietnam: A methodology based on Digital Shoreline Analysis System and Sentinel-2

2021 ◽  
Vol 14 (11) ◽  
pp. 13-24
Author(s):  
Anh Tu Ngo ◽  
Stéphane Grivel ◽  
Thai Le Phan ◽  
Huu Xuan Nguyen ◽  
Trong Doi Nguyen
Keyword(s):  
Linear Regression ◽  
Shoreline Change ◽  
The South ◽  
Central Coast ◽  
Shoreline Changes ◽  
South Central ◽  
Digital Shoreline Analysis System ◽  
Analysis System ◽  
End Point Rate ◽  
Sentinel 2

The research focuses on using Sentinel-2 that can be integrated with the Digital Shoreline Analysis System (DSAS) as an effective tool for the determination of changes in the riverbanks and using linear regression to predict shoreline changes. The research applied the assessment of shoreline changes in the period of 2015- 2020 and forecast to 2025 in Laigiang river of the South Central Coast region of Vietnam. Based on the DSAS tool, parameters such as Shoreline Change Envelope (SCE), Net Shoreline Movement (NSM), End Point Rate (EPR) and Linear Regression Rate (LRR) were determined. The analysis results show that the accretion process in the Laigiang river in the period of 2015-2020 with the accretion area ranges from 81.47 ha. Meanwhile, the area of shoreline erosion only fluctuates around 54.42 ha. The rhythm of evolution is a determinant element for this transitional system.

scholarly journals Assessment of shoreline positional uncertainty using remote sensing and GIS techniques: A case study from the east coast of India

2021 ◽  
Vol 71 (3) ◽  
pp. 249-263
Author(s):  
Kongeswaran Thangaraj ◽  
Sivakumar Karthikeyan
Keyword(s):  
Linear Regression ◽  
Coastal Zone ◽  
East Coast ◽  
Coastal Zone Management ◽  
Storm Surges ◽  
Shoreline Change ◽  
Coastal Protection ◽  
East Coast Of India ◽  
Zone Management ◽  
2004 Tsunami

The focus of this research was to assess the shoreline changes by comparing the satellite data from 1980 to 2020. The study area falls in the region between Kodiakarai and Nagapattinam of the east coast of India, which has frequently been distressed by storm surges and cyclones in the Bay of Bengal. The Digital Shoreline Analysis System (DSAS) detects and measures the erosional and accretional shoreline positions through the statistics of the Shoreline Change Envelope, Net Shoreline Movement, End Point Rate, Linear Regression Rate, and Weighted Linear Regression. The results show that the shoreline from Kodiakkarai to Nagapattinam suffered severe erosion of 17.7% in total with an average annual erosion rate of 3.4 m/year from 1980 to 2020 and the rate of erosion ranged between 0.1 m/year to 19.8 m/year. About 90.5% of the total shoreline was faced high erosion during the period between 2000 and 2010. The maximum erosion was about 1061 m from 2000 to 2010, the maximum accretion was found to be 1002 m in transects at Kodiakkarai during 2010 to 2020. After the effect of 2004 tsunami, the corresponding changes in littoral currents caused the drastic erosion and accretion in this shoreline. The DSAS prediction model shows that 19.3% of the current shoreline will erode in 2030. The maximum predicted erosion is 406 m at Kodiakkarai and the maximum predicted accretion is 148 m at Nagapattinam region. The coastal zone from Kodiakkarai to Nagapattinam needs special attention to prevent the erosion and it is recommended to build suitable coastal protection structures along the coast for sustainable development and to execute the coastal zone management for this region.

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