Monitoring Shoreline Changes in the Gulf of Khambhat, India During 1966–2004 Using RESOURCESAT-1 LISS-III

2014 ◽  
Vol 1 (1) ◽  
pp. 27-37 ◽  
Author(s):  
Mukesh Gupta ◽  
Keyword(s):  
Shoreline Changes ◽  
Liss Iii

Shoreline changes over last five decades and predictions for 2030 and 2040: a case study from Cuddalore, southeast coast of India

2021 ◽  
Author(s):  
Logesh Natarajan ◽  
Nagulan Sivagnanam ◽  
Tune Usha ◽  
Lakshumanan Chokkalingam ◽  
Sajimol Sundar ◽  
...  
Keyword(s):  
Southeast Coast Of India ◽  
Shoreline Changes ◽  
Southeast Coast

Mapping and Electronic Publishing of Shoreline Changes using UAV Remote Sensing and GIS

2021 ◽  
Author(s):  
N. Shenbagaraj ◽  
K. Senthil kumar ◽  
A. Mohamed Rasheed ◽  
J. Leostalin ◽  
M. Naresh Kumar
Keyword(s):  
Remote Sensing ◽  
Electronic Publishing ◽  
Remote Sensing And Gis ◽  
Shoreline Changes

scholarly journals Shoreline Changes along Northern Ibaraki Coast after the Great East Japan Earthquake of 2011

2021 ◽  
Vol 13 (7) ◽  
pp. 1399
Author(s):  
Quang Nguyen Hao ◽  
Satoshi Takewaka
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
Sandy Beaches ◽  
Great East Japan Earthquake ◽  
Shoreline Changes ◽  
Run Up ◽  
Tsunami Run Up ◽  
Sentinel 2 ◽  
Infrared Radiometer

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.

scholarly journals Evaluation of UAV LiDAR for Mapping Coastal Environments

2019 ◽  
Vol 11 (24) ◽  
pp. 2893 ◽  
Author(s):  
Yi-Chun Lin ◽  
Yi-Ting Cheng ◽  
Tian Zhou ◽  
Radhika Ravi ◽  
Seyyed Hasheminasab ◽  
...  
Keyword(s):  
High Resolution ◽  
Lake Michigan ◽  
Point Clouds ◽  
Volume Loss ◽  
Coastal Environments ◽  
Average Volume ◽  
Survey Period ◽  
Shoreline Changes ◽  
Point Density ◽  
One Year

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.

Estimation of wheat leaf area index from IRS LISS-III data using Price model

2000 ◽  
Vol 21 (15) ◽  
pp. 2943-2949 ◽  
Author(s):  
A. Rastogi ◽  
N. Kalra ◽  
P. K. Agarwal ◽  
S. K. Sharma ◽  
R. C. Harit ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Price Model ◽  
Area Index ◽  
Wheat Leaf ◽  
Liss Iii

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.

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