1984-2022 Yılları Arasında Beymelek Plajı ve Beymelek Lagünü Kıyı Şeridi Değişimleri, Antalya, Türkiye
Year 2024,
Issue: 13, 40 - 51, 15.10.2024
Hatice Kılar
,
Olgu Aydın
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.
Ethical Statement
Çalışmanın hazırlanmasında herhangi bir kurumdan maddi manevi destek alınmamıştır.
References
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- 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
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- 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
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- 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
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Temporal Shoreline Changes From 1984 to 2022 Along Beymelek Beach and Beymelek Lagoon, Antalya, Türkiye
Year 2024,
Issue: 13, 40 - 51, 15.10.2024
Hatice Kılar
,
Olgu Aydın
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.
References
- 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
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