A shoreline change analysis along the coast between Kanyakumari and Tuticorin, India, using digital shoreline analysis system

Mujabar, P. Sheik; Chandrasekar,

doi:10.1007/s11806-011-0551-7

Cited by 95 publications

(33 citation statements)

References 12 publications

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“…In order to calculate erosion/accretion rates, many statistical methods have been applied, such as end point rate (EPR), average of rates (AOR), minimum description length (MDL), jackknifing (JK), linear regression rate (LRR), reweighted least squares (RLS), weighted least squares (WLS), reweighted weighted least squares (RWLS), least absolute deviation (LAD), and weighted least absolute deviation (WLAD) (Dolan et al, 1991;Thieler et al, 1995;Crowell et al, 1997;Coyne et al, 1999;Honeycutt et al, 2001;Genz et al, 2007;Kuleli, 2010;Kuleli et al, 2011;Sheik and Chandrasekar, 2011). The two most frequently cited methods are EPR and LRR.…”

Section: Mangrove Shoreline Rate Calculationmentioning

confidence: 99%

Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam

et al. 2014

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Abstract. Mui Ca Mau at the southern tip of Vietnam supports a large area of mangroves and has a high value for biodiversity and scenic beauty. This area is affected by erosion along the East Sea and accretion along the Gulf of Thailand, leading to the loss of huge stretches of mangroves along the East Sea and, in some cases, loss of environmental and ecosystem services provided by mangroves. In this study, we used remotely sensed aerial (1953), Landsat (1979Landsat ( , 1988Landsat ( and 2000 and SPOT (1992SPOT ( , 1995SPOT ( , 2004SPOT ( , 2008SPOT ( , 2009SPOT ( and 2011 images and the Digital Shoreline Analysis System (DSAS) to quantify the rate of mangrove shoreline change for a 58 yr period. There were 1129 transects sampled at 100 m intervals along the mangrove shoreline and two statistical methods, namely end point rate (EPR) and linear regression rate (LRR), were used to calculate the rate of change of mangrove shorelines and distance from 1953 to 2011. The study confirms that erosion and accretion, respectively, are significant at the East Sea and Gulf of Thailand sides of Mui Ca Mau. The East Sea side had a mean erosion LRR of 33.24 m yr −1 . The accretion trend at the Gulf of Thailand side had an average rate of 40.65 m yr −1 . The results are important in predicting changes of coastal ecosystem boundaries and enable advanced planning for specific sections of coastline, to minimize or neutralize losses, to inform provincial rehabilitation efforts and reduce threats to coastal development and human safety.

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Section: Mangrove Shoreline Rate Calculationmentioning

confidence: 99%

Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam

et al. 2014

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“…The combination with DSAS statistics allows identifying indicators that discriminate between different mangrove zones. DSAS allows examining historical shorelines, which is an advantage as compared with the traditional ground survey techniques (Thieler et al, 2009). This study combines DSAS and remote sensing to describe historical mangrove shoreline changes and mangrove zoning.…”

Section: Discussionmentioning

confidence: 99%

“…Two DSAS versions are available: the DSAS extension of the Environmental System Research Institute (ESRI)'s ArcGIS software (Thieler et al, 2009), and the DSAS web. The DSAS software was selected because it runs faster than the web-based version.…”

Section: Digital Shoreline Analysis System (Dsas)mentioning

confidence: 99%

“…The system controls the following coastline characteristics: historical coastline dynamics, shoreline change, development and evolution of gulls, cliff retreat and erosion, shoreline measurement and modeling (Oyedotun, 2014). In this study, the End Point Rate (EPR) was chosen the statistical parameters describing the spatial patterns of shoreline change (Thieler et al, 2009). EPR measures mangrove shoreline change by dividing the distance of the mangrove shoreline between its initial (year 2005) and the most recent position of shoreline (year 2014).…”

Section: Digital Shoreline Analysis System (Dsas)mentioning

confidence: 99%

“…To this end, both aerial photos and satellite images were used. More recently the combination of remote sensing and GIS with spatial models as fractal analysis (Nguyen et al, 2015) or Digital Shoreline Analysis System (DSAS) (Thieler et al, 2009) was used. Because DSAS is effective for calculating changing rates of mangrove boundary changes incorporating an evidently -identified attribute position at separate times (Cohen and Lara, 2003;Sheik and Chandrasekar, 2011), it is able to provide a better understanding of the nature, dynamics and trend of mangrove shoreline change.…”

Section: Introductionmentioning

confidence: 99%

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A Digital Shoreline Analysis System (DSAS) applied on mangrove shoreline changes along the Giao Thuy coastal area (Nam Dinh, Vietnam) during 2005-2014

Thinh

Hens

2017

TCCKHVTD

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The paper deals with a combination of the Digital Shoreline Analysis System (DSAS) and remote sensing, studying historical mangrove shoreline changes and mangrove zoning in the Giao Thuy coastal area of the Nam Dinh province, Vietnam. The results show an over-all mangrove area increase of 2,487 hectares during the years 2005-2014. This dynamics results from both degradation and increase of the mangroves. The calculated degradation rate is 1.41 m yr -1 , and the growth rate is 1.26 m yr -1 on average. 4 different mangrove zones were delineated based on the End Point Rate (EPR) values of DSAS transects. The differential evolution of the mangroves in these zones is driven by socio-economic and environmental factors. The results contribute to practices of mangrove planning and management in a coastal area. Furthermore, historical mangrove shoreline change provides indicators to monitor coastal environmental changes for global warming, climate change, storm effects, sea level change, pollution, and sedimentation rates.

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A Study on Shore-Line Dynamics During and Post-construction of Breakwaters in Kasaragod Fishing Harbour

Chaitanya

Nasar

Paravath

2020

Lecture Notes in Civil Engineering

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A shoreline change analysis along the coast between Kanyakumari and Tuticorin, India, using digital shoreline analysis system

Cited by 95 publications

References 12 publications

Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam

Application of remote sensing and GIS for detection of long-term mangrove shoreline changes in Mui Ca Mau, Vietnam

A Digital Shoreline Analysis System (DSAS) applied on mangrove shoreline changes along the Giao Thuy coastal area (Nam Dinh, Vietnam) during 2005-2014

A Study on Shore-Line Dynamics During and Post-construction of Breakwaters in Kasaragod Fishing Harbour

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