Assessment of the changes in shoreline using digital shoreline analysis system: a case study of Kızılırmak Delta in northern Turkey from 1951 to 2017

Ataol, Murat; Kale, Mustafa Murat; Tekkanat, İlyas Sadık

doi:10.1007/s12665-019-8591-7

Cited by 31 publications

(11 citation statements)

References 21 publications

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“…Studies showing temporal changes in the Ramsar Sites of Turkey are quite limited [51][52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70], and a study has not yet been conducted at a national scale. With this study, all of the Ramsar sites of Turkey were given with their various features, the Inland Ramsar sites from 1985 to 2020 were examined, and the results were compared.…”

Section: Criteriamentioning

confidence: 99%

Analysis of the Temporal Changes of Inland Ramsar Sites in Turkey Using Google Earth Engine

Dervisoglu

2021

IJGI

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Ramsar Convention (RC) is the first of modern intergovernmental agreement on the conscious use and conservation of natural resources. It provides a platform for contracting parties working together to develop the best available data, advice, and policy recommendations to increase awareness of the benefits of wetlands in nature and society. Turkey became a party of the RC in 1994, and in the years 1994 to 2013, 14 wetlands that reached the Ramsar criteria were recognized as Ramsar sites (RS). With this study, all inland RS in Turkey from 1985 to 2020 were examined, and changes in the water surface areas were evaluated on the GEE cloud computing platform using Landsat satellite images and the NDWI index. The closest meteorological station data to each RS were evaluated and associated with the surface area changes. The reasons for the changes in these areas, besides the meteorological effects, have been scrutinized using management plans and publications. As a result, inland wetlands decreased at different rates from 1985 to 2020, with a total loss of 31.38% and 21571.0 ha for the spring months. Since the designation dates of RS, the total amount of water surface area reduction was 27.35 %, constituting 17,758.90 ha.

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Section: Criteriamentioning

confidence: 99%

Analysis of the Temporal Changes of Inland Ramsar Sites in Turkey Using Google Earth Engine

Dervisoglu

2021

IJGI

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“…Shoreline data can be obtained from different sources, such as historical maps, aerial photography, Light Detection and Ranging (LIDAR) and differentialGlobal Positioning Systems (dGPS) surveys (e.g., [4][5][6][7][8]), video and satellite imagery (e.g., [9][10][11][12][13][14][15][16]) and recently, crowd-sourced smartphone images taken at CoastSnap stations [17]. The analysis of historical shoreline changes can combine several sources (e.g., [18][19][20][21][22]). Several factors influence its dynamics (e.g., waves, tides, human activities), which make them one of the most important features in coastal planning [23].…”

Section: Introductionmentioning

confidence: 99%

“…One advantage of using DSAS in coastal change analysis is that it can calculate the rate of change of shoreline time-series, evaluating and resolving the nature of shoreline dynamics and changing trends [39]. Besides, DSAS has numerous applications in studies of coastal behavior and shoreline dynamics, such as historical trend analysis [8,16,18,19,[40][41][42][43][44] and expected future shoreline morphology (e.g., [45,46]).…”

Section: Introductionmentioning

confidence: 99%

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

Lima

Fernández-Fernández

Espinoza

et al. 2021

IJGI

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This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS graphical modeler for calculating the shoreline change with the end point rate method. The EPR4Q tries to fill the gaps in user-friendly and free open-source tools for shoreline analysis in a geographic information system environment since the most used software—Digital Shoreline Analysis System (DSAS)—although being a free extension, it is created for commercial software. Additionally, the best free, open-source option to calculate EPR is called Analyzing Moving Boundaries Using R (AMBUR); since it is a robust and powerful tool, the complexity can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR with different types of shorelines found in nature, extracted from the US Geological Survey Open-File. The obtained results of each tool were compared with Pearson’s correlation coefficient. The validation results indicate that the EPR4Q tool acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, proving that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

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“…Shoreline data can be obtained from different sources such as historical maps, aerial photography, Light Detection and Ranging (LIDAR) and differential Global Positioning Systems (dGPS) surveys (e.g., [4][5][6][7][8]), video and satellite imagery [e.g., [9][10][11][12][13][14][15][16] and recently, crowd-sourced smartphone images taken at CoastSnap stations [17]. The analysis of historical shoreline changes can combine several sources (e.g., [18][19][20][21][22]). Several factors influence its dynamics (e.g., waves, tides, human activities), which make them one of the most important features in coastal planning [23].…”

Section: Introductionmentioning

confidence: 99%

“…One advantage of using DSAS in coastal change analysis is that it can calculate the rate of change of shoreline time-series, evaluating and resolving the nature of shoreline dynamics and changing trends [39]. Besides, DSAS has numerous applications in studies of coastal behavior and shoreline dynamics such as historical trend analysis [8,16,18,19,[40][41][42][43][44], and expected future shoreline morphology (e.g., [45,46]).…”

Section: Introductionmentioning

confidence: 99%

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

Lima¹,

Fernández-Fernández²,

Espinoza³

et al. 2021

Preprint

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This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS Graphical Modeler to calculate the shoreline change by End Point Rate method. The EPR4Q tries to fill the gap of user-friendly and free open-source tool for shoreline analysis in Geographic Information System environment, since the most used software - Digital Shoreline Analysis System (DSAS) - although is a free extension, is suited for commercial software. Besides, the best free open-source option to calculate EPR called Analyzing Moving Boundaries Using R (AMBUR), since it is a robust and powerful tool, the complexity and heavy processes can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR on different examples of shorelines found in nature, extracted from the U.S. Geological Survey Open-File. The obtained results of each tool were compared with Pearson correlation coefficient. The validation results indicate that the EPR4Q tool created acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, guarantying that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

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Assessment of the changes in shoreline using digital shoreline analysis system: a case study of Kızılırmak Delta in northern Turkey from 1951 to 2017

Cited by 31 publications

References 21 publications

Analysis of the Temporal Changes of Inland Ramsar Sites in Turkey Using Google Earth Engine

Analysis of the Temporal Changes of Inland Ramsar Sites in Turkey Using Google Earth Engine

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

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