Shoreline changes due to construction of groyne field in north of Chennai Port, India

2021 ◽  
Vol 193 (12) ◽  
Author(s):  
Vallam Sundar ◽  
Sannasi Annamalaisamy Sannasiraj ◽  
Sukanya Ramesh Babu ◽  
Gracy Margaret Mary Rajakan
Keyword(s):  
Author(s):  
Logesh Natarajan ◽  
Nagulan Sivagnanam ◽  
Tune Usha ◽  
Lakshumanan Chokkalingam ◽  
Sajimol Sundar ◽  
...  

Author(s):  
N. Shenbagaraj ◽  
K. Senthil kumar ◽  
A. Mohamed Rasheed ◽  
J. Leostalin ◽  
M. Naresh Kumar

2021 ◽  
Vol 13 (7) ◽  
pp. 1399
Author(s):  
Quang Nguyen Hao ◽  
Satoshi Takewaka

In this study, we analyze the influence of the Great East Japan Earthquake, which occurred on 11 March 2011, on the shoreline of the northern Ibaraki Coast. After the earthquake, the area experienced subsidence of approximately 0.4 m. Shoreline changes at eight sandy beaches along the coast are estimated using various satellite images, including the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), ALOS AVNIR-2 (Advanced Land Observing Satellite, Advanced Visible and Near-infrared Radiometer type 2), and Sentinel-2 (a multispectral sensor). Before the earthquake (for the period March 2001–January 2011), even though fluctuations in the shoreline position were observed, shorelines were quite stable, with the averaged change rates in the range of ±1.5 m/year. The shoreline suddenly retreated due to the earthquake by 20–40 m. Generally, the amount of retreat shows a strong correlation with the amount of land subsidence caused by the earthquake, and a moderate correlation with tsunami run-up height. The ground started to uplift gradually after the sudden subsidence, and shoreline positions advanced accordingly. The recovery speed of the beaches varied from +2.6 m/year to +6.6 m/year, depending on the beach conditions.


2019 ◽  
Vol 11 (24) ◽  
pp. 2893 ◽  
Author(s):  
Yi-Chun Lin ◽  
Yi-Ting Cheng ◽  
Tian Zhou ◽  
Radhika Ravi ◽  
Seyyed Hasheminasab ◽  
...  

Unmanned Aerial Vehicle (UAV)-based remote sensing techniques have demonstrated great potential for monitoring rapid shoreline changes. With image-based approaches utilizing Structure from Motion (SfM), high-resolution Digital Surface Models (DSM), and orthophotos can be generated efficiently using UAV imagery. However, image-based mapping yields relatively poor results in low textured areas as compared to those from LiDAR. This study demonstrates the applicability of UAV LiDAR for mapping coastal environments. A custom-built UAV-based mobile mapping system is used to simultaneously collect LiDAR and imagery data. The quality of LiDAR, as well as image-based point clouds, are investigated and compared over different geomorphic environments in terms of their point density, relative and absolute accuracy, and area coverage. The results suggest that both UAV LiDAR and image-based techniques provide high-resolution and high-quality topographic data, and the point clouds generated by both techniques are compatible within a 5 to 10 cm range. UAV LiDAR has a clear advantage in terms of large and uniform ground coverage over different geomorphic environments, higher point density, and ability to penetrate through vegetation to capture points below the canopy. Furthermore, UAV LiDAR-based data acquisitions are assessed for their applicability in monitoring shoreline changes over two actively eroding sandy beaches along southern Lake Michigan, Dune Acres, and Beverly Shores, through repeated field surveys. The results indicate a considerable volume loss and ridge point retreat over an extended period of one year (May 2018 to May 2019) as well as a short storm-induced period of one month (November 2018 to December 2018). The foredune ridge recession ranges from 0 m to 9 m. The average volume loss at Dune Acres is 18.2 cubic meters per meter and 12.2 cubic meters per meter within the one-year period and storm-induced period, respectively, highlighting the importance of episodic events in coastline changes. The average volume loss at Beverly Shores is 2.8 cubic meters per meter and 2.6 cubic meters per meter within the survey period and storm-induced period, respectively.


2021 ◽  
Vol 14 (11) ◽  
pp. 13-24
Author(s):  
Anh Tu Ngo ◽  
Stéphane Grivel ◽  
Thai Le Phan ◽  
Huu Xuan Nguyen ◽  
Trong Doi Nguyen

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.


Author(s):  
N.A. Anjita ◽  
G.S. Dwarakish

Study of morphological variations and the effects of oceanographic processes such as erosion and accretion at different temporal scales are important to understand the nature of the coast and the cyclic changes occurring during different seasons. The Udupi-Dakshina Kannada coast along the west coast of India exhibits a wide range of changes depending on the interactions of tide and wave energy, sediment supply and more importantly human intervention. In view of this, the present work has been carried out to study the changes in shoreline changes along the Udupi-Dakshina Kannada coast over a period of 29 years from 1990 to 2019. Remote Sensing and GIS techniques have been used to demarcate shorelines and calculate the shoreline change rates. Overall accretion and erosion rates were found to be 1.28 m/year and 0.91 m/year respectively along the coast. Highest accretion and erosion rates of 12.57 m/year and 5.34 m/year was noticed along the Dakshina Kannada coast. The study also suggests that multi-dated satellite data along with statistical techniques can be effectively used for prediction of shoreline changes. Keywords: remote sensing, GIS, Dakshina Kannada coast, oceanography, shoreline.


Author(s):  
Paul D. Komar ◽  
Jose Roman Lizarraga-Arciniega ◽  
Thomas A. Terich

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