Araştırma Makalesi

Temporal Shoreline Changes From 1984 to 2022 Along Beymelek Beach and Beymelek Lagoon, Antalya, Türkiye

Sayı: 13 15 Ekim 2024

Hatice Kılar ^*, Olgu Aydın

PDF İndir

Jeomorfolojik Araştırmalar Dergisi

TR EN

1984-2022 Yılları Arasında Beymelek Plajı ve Beymelek Lagünü Kıyı Şeridi Değişimleri, Antalya, Türkiye

Öz

Coastal zones are important transition zones between land and sea, and the shoreline is subject to dynamic change on both spatial and temporal scales. Accurate measurement and modelling of the shoreline is therefore essential for coastal sustainability and coastal zone management. In this study, the shoreline change of Beymelek Beach and Beymelek Lagoon was analyzed over both short and long periods by using End Point Rate (EPR), Net Shoreline Movement (NSM) and Linear Regression Rate (LRR) statistics from the Digital Shoreline Analyses System (DSAS) tool. The long-term shoreline statistics of the Beymelek Beach indicates that the maximum shoreline accretion was 128.4 m for NSM and 4.3 m/yr for EPR, while the maximum shoreline erosion was -62.6 m for NSM, and -1.8 m/yr for LRR in 1984 and 2022. The maximum shoreline erosion rate of Beymelek Lagoon was -148.5 m for NSM and the maximum shoreline accretion was 5.3 m for NSM between 1984 and 2022. As a result, Beymelek Beach and Beymelek Lagoon have experienced significant shoreline changes over both short and long time periods. Therefore, determining the shoreline change in the study area is crucial for making efficient decisions about the coastal zone and contributing to its sustainability.

Anahtar Kelimeler

Shoreline change , Beymelek Beach , Beymelek Lagoon , Digital Shoreline Analysis System (DSAS) , and Geographic Information System (GIS)

Temporal Shoreline Changes From 1984 to 2022 Along Beymelek Beach and Beymelek Lagoon, Antalya, Türkiye

Abstract

Coastal zones are important transition zones between land and sea, and the shoreline is subject to dynamic change on both spatial and temporal scales. Accurate measurement and modelling of the shoreline is therefore essential for coastal sustainability and coastal zone management. In this study, the shoreline change of Beymelek Beach and Beymelek Lagoon was analyzed over both short and long periods by using End Point Rate (EPR), Net Shoreline Movement (NSM) and Linear Regression Rate (LRR) statistics from the Digital Shoreline Analyses System (DSAS) tool. The long-term shoreline statistics of the Beymelek Beach indicates that the maximum shoreline accretion was 128.4 m for NSM and 4.3 m/yr for EPR, while the maximum shoreline erosion was -62.6 m for NSM, and -1.8 m/yr for LRR in 1984 and 2022. The maximum shoreline erosion rate of Beymelek Lagoon was -148.5 m for NSM and the maximum shoreline accretion was 5.3 m for NSM between 1984 and 2022. As a result, Beymelek Beach and Beymelek Lagoon have experienced significant shoreline changes over both short and long time periods. Therefore, determining the shoreline change in the study area is crucial for making efficient decisions about the coastal zone and contributing to its sustainability.

Keywords

Shoreline change , Beymelek Beach , Beymelek Lagoon , Digital Shoreline Analysis System (DSAS) , and Geographic Information System (GIS)

Kaynakça

Abou Samra, R. M., & Ali, R. R. (2021). Applying DSAS tool to detect coastal changes along Nile Delta, Egypt. Egyptian Journal of Remote Sensing and Space Science, 24(3), 463–470. https://doi.org/10.1016/j.ejrs.2020.11.002
Aladwani, N. S. (2022). Shoreline change rate dynamics analysis and prediction of future positions using satellite imagery for the southern coast of Kuwait: A case study. Oceanologia, xxxx. https://doi.org/10.1016/j.oceano.2022.02.002
Anthony, E. J. (2015). Wave influence in the construction, shaping and destruction of river deltas: A review. Marine Geology, 361, 53–78. https://doi.org/10.1016/j.margeo.2014.12.004
Arun Kumar, A., & Kunte, P. D. (2012). Coastal vulnerability assessment for Chennai, east coast of India using geospatial techniques. Natural Hazards, 64(1), 853–872. https://doi.org/10.1007/s11069-012-0276-4
Ataol, M., & Kale, M. M. (2022). Shoreline changes in the river mouths of the Ceyhan Delta. Arabian Journal of Geosciences, 15(2). https://doi.org/10.1007/s12517-022-09516-2
Ataol, M., Kale, M. M., & Tekkanat, İ. S. (2019). Assessment of the changes in shoreline using digital shoreline analysis system : a case study of Kızılırmak Delta in northern Turkey from 1951 to 2017. https://doi.org/10.1007/s12665-019-8591-7
Avcı, P., Bayarı, C. S., & Özyurt, N. N. (2021). Assessing the effect of climate change on groundwater use in Demre coastal aquifer (Antalya, Turkey), coupled use of climate scenarios and numerical flow modeling. Environmental Earth Sciences, 80(6), 1–18. https://doi.org/10.1007/s12665-021-09517-6
Bera, R. (2019). Quantitative analysis of erosion and accretion (1975 – 2017) using DSAS — A study on Indian Sundarbans. Regional Studies in Marine Science, 28, 100583. https://doi.org/10.1016/j.rsma.2019.100583
Bheeroo, R. A., Chandrasekar, N., Kaliraj, S., & Magesh, N. S. (2016). Shoreline change rate and erosion risk assessment along the Trou Aux Biches–Mont Choisy beach on the northwest coast of Mauritius using GIS-DSAS technique. Environmental Earth Sciences, 75(5), 1–12. https://doi.org/10.1007/s12665-016-5311-4
Boukhennaf, A., & Mezouar, K. (2023). Long and short-term evolution of the Algerian coastline using remote sensing and GIS technology. Regional Studies in Marine Science, 61, 102893. https://doi.org/10.1016/j.rsma.2023.102893

Cai, H., Li, C., Luan, X., Ai, B., Yan, L., & Wen, Z. (2022). Analysis of the spatiotemporal evolution of the coastline of Jiaozhou Bay and its driving factors. Ocean and Coastal Management, 226(October 2020). https://doi.org/10.1016/j.ocecoaman.2022.106246
Ciritci, D., & Türk, T. (2019). Automatic Detection of Shoreline Change by Geographical Information System (GIS) and Remote Sensing in the Göksu Delta, Turkey. Journal of the Indian Society of Remote Sensing, 47(2), 233–243. https://doi.org/10.1007/s12524-019-00947-1
Dai, C., Howat, I. M., Larour, E., & Husby, E. (2019). Remote Sensing of Environment Coastline extraction from repeat high resolution satellite imagery. Remote Sensing of Environment, 229(November 2018), 260–270. https://doi.org/10.1016/j.rse.2019.04.010
Darwish, K., & Smith, S. (2023). Landsat-Based Assessment of Morphological Changes along the Sinai Mediterranean Coast between 1990 and 2020. Remote Sensing, 15(5). https://doi.org/10.3390/rs15051392
Duru, U. (2017). Shoreline change assessment using multi-temporal satellite images: a case study of Lake Sapanca, NW Turkey. Environ Monit Assess, 189(8). https://doi.org/10.1007/s10661-017-6112-2
Esmail, M., Mahmod, W. E., & Fath, H. (2019). Assessment and prediction of shoreline change using multi-temporal satellite images and statistics: Case study of Damietta coast, Egypt. Applied Ocean Research, 82(March 2018), 274–282. https://doi.org/10.1016/j.apor.2018.11.009
Ferreira, T. A. B., Aquino da Silva, A. G., Reyes Perez, Y. A., Stattegger, K., & Vital, H. (2021). Evaluation of decadal shoreline changes along the Parnaíba Delta (NE Brazil) using satellite images and statistical methods. Ocean and Coastal Management, 202(August 2020). https://doi.org/10.1016/j.ocecoaman.2020.105513
Godwyn-Paulson, P., Jonathan, M. P., Roy, P. D., Rodríguez-Espinosa, P. F., Muthusankar, G., Muñoz-Sevilla, N. P., & Lakshumanan, C. (2021). Evolution of southern Mexican Pacific coastline: Responses to meteo-oceanographic and physiographic conditions. Regional Studies in Marine Science, 47(2021), 101914. https://doi.org/10.1016/j.rsma.2021.101914
Görmüş, T., Ayat, B., Aydoğan, B., & Tătui, F. (2021). Basin scale spatiotemporal analysis of shoreline change in the Black Sea. Estuarine, Coastal and Shelf Science, 252(May 2020). https://doi.org/10.1016/j.ecss.2021.107247
Himmelstoss, E. A., Henderson, R. E., Kratzmann, M. G., & Farris, A. S. (2021). Digital Shoreline Analysis System ( DSAS ) Version 5.1 User Guide: U.S. Geological Survey Open-File Report 2021–1091. U.S. Geological Survey, 104.
Ilkiliç, C., & Aydin, H. (2015). Wind power potential and usage in the coastal regions of Turkey. Renewable and Sustainable Energy Reviews, 44, 78–86. https://doi.org/10.1016/j.rser.2014.12.010
Kazı, H., & Karabulut, M. (2023). Monitoring the shoreline changes of the Göksu Delta (Türkiye) using geographical information technologıes and predictions for the near future. Lnternational Journal of Geography and Geography Education, 50, 329–352. https://doi.org/10.32003/igge.1304403
Kılar, H. (2023). Shoreline change assessment using DSAS technique: A case study on the coast of Meriç Delta (NW Türkiye). Regional Studies in Marine Science, 57. https://doi.org/10.1016/j.rsma.2022.102737
Kılar, H., & Çiçek, İ. (2018). Makale Basıma Uygun Tarihi: 11.03. COĞRAFBi̇li̇mleDergi̇si̇ Cbd, 16(1), 89–104.
Kılar, H., & Çiçek, İ. (2019). Kıyı Çizgisinin Gelecekteki Konumunun Belirlenmesinin Önemi: Göksu Deltası Örneği, Mersin (Türkiye). Coğrafi Bilimler Dergisi, 17(1), 193–216. https://doi.org/10.33688/aucbd.559328
Kuleli, T. (2010). Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey. Environmental Monitoring and Assessment, 167(1–4), 387–397. https://doi.org/10.1007/s10661-009-1057-8
Kuleli, T., Guneroglu, A., Karsli, F., & Dihkan, M. (2011). Automatic detection of shoreline change on coastal Ramsar wetlands of Turkey. Ocean Engineering, 38(10), 1141–1149. https://doi.org/10.1016/j.oceaneng.2011.05.006
Kumar, A. and Jayappa, K. S. (2009). Long and Short-Term Shoreline Changes Along Mangalore Coast, India. Int. J. Environ. Res., 3(2), 177–188.
Kumar Das, S., Sajan, B., Ojha, C., & Soren, S. (2021). Shoreline change behavior study of Jambudwip island of Indian Sundarban using DSAS model. Egyptian Journal of Remote Sensing and Space Science, 24(3), 961–970. https://doi.org/10.1016/j.ejrs.2021.09.004
Kumaravel, S., Ramkumar, T., Gurunanam, B., Suresh, M., & Dharanirajan, K. (2013). An Application of Remote Sensing and GIS Based Shoreline Change Studies-A Case Study in the Cuddalore District, East Coast of Tamilnadu, South India. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2, 2278–3075. http://www.gisdevelopment.net/magazine/
Li, R., Di, K., & Ma, R. (2001). A comparative study of shoreline mapping techniques. GIS for Coastal Zone Management, August 2004, 27–34. https://doi.org/10.1201/9781420023428-9
Muskananfola, M. R., & Febrianto, S. (2020). Spatio-temporal analysis of shoreline change along the coast of Sayung Demak , Indonesia using Digital Shoreline Analysis System. Regional Studies in Marine Science, 34, 101060. https://doi.org/10.1016/j.rsma.2020.101060
Nassar, K., Mahmod, W. E., Fath, H., Masria, A., Nadaoka, K., & Negm, A. (2019). Shoreline change detection using DSAS technique: Case of North Sinai coast, Egypt. Marine Georesources and Geotechnology, 37(1), 81–95. https://doi.org/10.1080/1064119X.2018.1448912
Nie, H., Tao, J., & Du, M. (2012). Study on coastal zone sustainable development and its application. Applied Mechanics and Materials, 170–173, 2280–2283. https://doi.org/10.4028/www.scientific.net/AMM.170-173.2280
Özpolat, E., & Demir, T. (2019). The spatiotemporal shoreline dynamics of a delta under natural and anthropogenic conditions from 1950 to 2018 : A dramatic case from the Eastern Mediterranean The spatiotemporal shoreline dynamics of a delta under natural and anthropogenic conditions from. Ocean and Coastal Management, 180(November), 104910. https://doi.org/10.1016/j.ocecoaman.2019.104910
Ozturk, D., & Sesli, F. A. (2015). Shoreline change analysis of the Kizilirmak Lagoon Series. Ocean and Coastal Management, 118, 290–308. https://doi.org/10.1016/j.ocecoaman.2015.03.009
Pardo-Pascual, J. E., Almonacid-Caballer, J., Ruiz, L. A., & Palomar-Vázquez, J. (2012). Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment, 123, 1–11. https://doi.org/10.1016/j.rse.2012.02.024
Qiao, G., Mi, H., Wang, W., Tong, X., Li, Z., Li, T., Liu, S., & Hong, Y. (2018). 55-year (1960–2015) spatiotemporal shoreline change analysis using historical DISP and Landsat time series data in Shanghai. International Journal of Applied Earth Observation and Geoinformation, 68(March 2017), 238–251. https://doi.org/10.1016/j.jag.2018.02.009
Rahbani, M., & Ghaderi, D. (2024). Long term investigation on shoreline changes of an Island, inside a Gulf (Hormuz Island). Regional Studies in Marine Science, 71(June 2023), 103399. https://doi.org/10.1016/j.rsma.2024.103399
Sam, C., & Balasubramanian, G. (2022). Geodesy and Geodynamics Coastal transgression and regression from 1980 to 2020 and shoreline forecasting for 2030 and 2040 , using DSAS along the southern coastal tip of Peninsular India. Geodesy and Geodynamics, June, 1–10. https://doi.org/10.1016/j.geog.2022.04.004
Shailesh Nayak. (2002). Use of satellite data in coastal zone programmes. Indian Cartographer, 5, 147–157. Siyal, A. A., Solangi, G. S., Siyal, Z. ul A., Siyal, P., Babar, M. M., & Ansari, K. (2022). Shoreline change assessment of Indus delta using GIS-DSAS and satellite data. Regional Studies in Marine Science, 53, 102405. https://doi.org/10.1016/j.rsma.2022.102405
Thieler, E. R., & Danforth, W. W. (2016). Historical Shoreline Mapping ( II ): Application of the Digital Shoreline Mapping and Analysis Systems ( DSMS / DSAS ) to Shoreline Change Mapping in Puerto Rico Stable URL : http://www.jstor.org/stable/4298256 REFERENCES Linked references are available o. Journal of Coastal Research, 10(3), 600–620.
Uzun, M. (2023). Riva (İstanbul) Kıyılarında Doğal ve Antropojenik Etkenlerle Değişen Kıyı Çizgisinin DSAS Aracı ile Analizi. Jeomorfolojik Araştırmalar Dergisi, 2023(11), 95–113. https://doi.org/10.46453/jader.1335105
Van, T. T., & Binh, T. T. (2008). Shoreline Change Detection To Serve Sustainable. International Symposium on Geoinformatics for Spatial Infrastructure Development in Earth and Allied Sciences, 1–6.
Viaña-Borja, S. P., & Ortega-Sánchez, M. (2019). Automatic methodology to detect the coastline from Landsat images with a new water index assessed on three different Spanish Mediterranean deltas. Remote Sensing, 11(18). https://doi.org/10.3390/rs11182186
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025–3033. https://doi.org/10.1080/01431160600589179
Yan, J., Miao, C., Su, F., & Zhao, Y. (2024). Ecological Informatics Association mining of coastline change and land use patterns to enhance conservation. Ecological Informatics, 80(February), 102544. https://doi.org/10.1016/j.ecoinf.2024.102544
Yiğit, A. Y., Kaya, Y., & Şenol, H. İ. (2022). Monitoring the change of Turkey’s tourism city Antalya’s Konyaaltı shoreline with multi-source satellite and meteorological data. Applied Geomatics, 14(2), 223–236. https://doi.org/10.1007/s12518-022-00431-5

Ayrıntılar

Birincil Dil

İngilizce

Konular

Coğrafi Bilgi Sistemleri

Bölüm

Araştırma Makalesi

Yazarlar

Hatice Kılar ^*
0000-0002-2423-4712
Türkiye

Olgu Aydın
Türkiye

Erken Görünüm Tarihi

12 Eylül 2024

Yayımlanma Tarihi

15 Ekim 2024

Gönderilme Tarihi

7 Haziran 2024

Kabul Tarihi

3 Eylül 2024

Yayımlandığı Sayı

Yıl 2024 Sayı: 13

DOI

https://doi.org/10.46453/jader.1497770

IZ

https://izlik.org/JA34RK69RT

APA

Kılar, H., & Aydın, O. (2024). Temporal Shoreline Changes From 1984 to 2022 Along Beymelek Beach and Beymelek Lagoon, Antalya, Türkiye. Jeomorfolojik Araştırmalar Dergisi, 13, 40-51. https://doi.org/10.46453/jader.1497770

Jeomorfolojik Araştırmalar Dergisi ( JADER ) / Journal of Geomorphological Researches

TR Dizin - Crossref - Google Scholar tarafından taranmaktadır.

Jeomorfoloji Derneği / Turkish Society for Geomorphology ( www.jd.org.tr )

Arşiv

Sayı: 13 , 15.10.2024

Makale İstatistikleri

Toplam Görüntülenme Sayısı
Toplam İndirilme Sayısı
Toplam Favorilere Ekleme Sayısı

Makale Dosyaları

Tam Metin

Paylaş