Analysis of Manyas Lake Surface Area and Shoreline Change Over Various Periods with DSAS Tool

Yıl 2024, , 35 - 56, 30.06.2024

Murat Uzun

https://doi.org/10.51489/tuzal.1443490

Öz

In this study, the shoreline and lake surface area changes of Lake Manyas were analysed by using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques for long term (1980-2020) and annual (2022) with DSAS tool. In the study, a formula was created using NDWI, MDWI, WRI water indices and NDVI, RVI, NDMI, GCI vegetation indices over Landsat satellite images of 1980, 1985, 1990, 1995, 2000, 2000, 2005, 2005, 2010, 2015, 2020 and all months of 2022, and shoreline extraction was performed. Then, shoreline and lake surface area change were analysed over different periods with NSM, EPR, SCE, LRR statistics in DSAS tool. According to the results of the analyses, the average shoreline changes between 1980 and 2020 was 139 m according to NSM statistics, 3,5 m/year according to EPR, 243.1 m according to SCE and 3.4 m/year according to LRR. While the shoreline extended a maximum of 1599 m, the minimum value was -403 m. From 1980 to 2020, 5.85 km2 coastal accumulation, 1.03 km2 coastal erosion and 146.5 km2 permanent lake surface area data were determined on the surface area and shores of Lake Manyas. According to the monthly data of Lake Manyas for 2022, the shoreline is advancing by 18 m on average. Due to the natural dynamic process and the productive structure of the wetland system, the lake surface area reaches its widest size in April with 149.01 km2 and its narrowest area is 146.05 km2 in August. On the southern shores of Lake Manyas, reedbed development and coastal accumulation are intensely experienced with the progression of the Manyas Stream delta, while coastal erosion is observed on the northern shores.

Anahtar Kelimeler

DSAS, Manyas Lake, Shoreline Change, Remote Sensing, GIS

Manyas Gölü Yüzey Alanı ve Kıyı Çizgisi Değişiminin Çeşitli Periyotlar Üzerinden DSAS Aracı ile Analizi

Öz

Bu çalışmada Manyas Gölü’nün kıyı çizgisi ve göl yüzey alanı değişimi, Coğrafi Bilgi Sistemleri (CBS) ve Uzaktan Algılama (UA) teknikleri kullanılarak, uzun dönemli (1980-2020) ve yıllık (2022) olarak DSAS aracı ile analiz edilmiştir. Çalışmada 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020 yıllarına ait ve 2022 yılının bütün aylarına ait Landsat uydu görüntüleri üzerinden NDWI, MDWI, WRI su indeksleri ve NDVI, RVI, NDMI, GCI bitki indeksleri kullanılarak formül oluşturulmuş, kıyı çizgisi çıkarımı yapılmıştır. Daha sonra DSAS aracındaki NSM, EPR, SCE, LRR istatistikleri ile kıyı çizgisi ve göl yüzey alanı değişimi farklı periyotlar üzerinden analiz edilmiştir. Analiz bulgularına göre 1980-2020 yılları arasında ortalama kıyı çizgisi değişimi NSM istatistiğinde 139 m, EPR’ye göre 3,5 m/yıl, SCE’ye göre 243,1 m ve LRR’ye göre 3,4 m/yıl olarak saptanmıştır. Kıyı çizgisi maksimum 1599 m ilerken minimum değer olarak -403 m gerilemiştir. Manyas Gölü yüzey alanı ve kıyılarında 1980’den 2020 yılına kadar 5,85 km2 kıyı birikimi, 1,03 km2 kıyı erozyonu ve 146,5 km2 daimî göl yüzey alanı verisi tespit edilmiştir. Manyas Gölü 2022 yılı aylık verilerine göre kıyı çizgisi ortalama 18 m ilerlemektedir. Doğal dinamik süreç ve sulak alan sisteminin üretken yapısı nedeniyle göl yüzey alanı en geniş boyutuna nisan ayında 149,01 km2 ile ulaşmakta, ağustos ayında ise en dar alanı 146,05 km2 olarak görülmektedir. Manyas Gölü güney kıyılarında sazlık alan gelişimi ve Manyas Çayı deltasının ilerlemesi ile kıyı birikimi yoğun şekilde yaşanırken, kuzey kıyılarda kıyı aşınımı gözlemlenmiştir.

Anahtar Kelimeler

DSAS, Manyas Gölü, Kıyı Çizgisi Değişimi, Uzaktan Algılama, CBS

Kaynakça

• Akdeniz, H. B. & İnam, Ş. (2023). Spatio-temporal analysis of shoreline changes and future forecasting: the case of Küçük Menderes Delta, Türkiye. Journal of Coastal Conservation, 27, 34. https://doi.org/10.1007/s11852-023-00966-8
• Aksoy, T., Serhat, S. A. R. I., & Çabuk, A. (2019). Sulak alanların yönetimi kapsamında su indeksinin uzaktan algılama ile tespiti, Göller Yöresi (in Turkish). GSI Journals Serie B: Advancements in Business and Economics, 2(1), 35-48.
• Alevkayalı, Ç., Atayeter, Y., Yayla, O, Bilgin, T. & Akpınar, H. (2023). Long-term coastline changes and climate relationship in Burdur Lake: Spatio-temporal trends and forecasts. Turkish Geographical Review, 82, 37-50. https://doi.org/10.17211/tcd.1287976
• 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. Environ Earth Sci, 78, 579. https://doi.org/10.1007/s12665-019-8591-7
• Ataol, M. & Onmuş, O. (2021). Wetland loss in Turkey over a hundred years: implications for conservation and management. Ecosystem Health and Sustainability, 7(1), 1-13. https://dx.doi.org/10.1080/20964129.2021.1930587
• Aydın, F., Erlat, E. & Türkeş, M. (2020). Impact of climate variability on the surface of Lake Tuz (Turkey), 1985–2016. Reg Environ Change, 20, 68. https://doi.org/10.1007/s10113-020-01656-z
• Bahadır, M. (2013). Determination of Spatial Changes of Akşehir Lake with Remote Perception Techniques. Marmara Geographical Review, 28, 246-275.
• Bombino, G., Barbaro, G., D'Agostino, D., Denisi, P., Foti, G., Labate, A. & Zimbone, S. M. (2022). Shoreline change and coastal erosion: the role of check dams. first indications from a case study in Calabria, Southern Italy. CATENA, 217. https://doi.org/10.1016/j.catena.2022.106494
• Bird, E. (2008). Coastal geomorphology: An introduction Second edition. John Wiley & Sons.
• Çoban, H., Koç, Ş. & Kale, M. M. (2020). Shoreline changes (1984 – 2019) in the Çoruh delta (Georgia/Batumi). International Journal of Geography and Geography Education (IGGE), 42, 589-601. https://doi.org/10.32003/igge.741573
• Darwish, K., Smith, S. E., Torab, M., Monsef, H. & Hussein, O. (2017). Geomorphological Changes along the Nile Delta Coastline between 1945 and 2015 Detected Using Satellite Remote Sensing and GIS. J. Coast. Res, 33(4): 786–794. http://dx.doi.org/10.2112/JCOASTRES-D-16-00056.1
• Davidson-Arnott, R. (2010). Introduction to Coastal Processes and Geomorphology. University Press Cambridge.
• Davidson, N. C. & Finlayson, C. M. (2018). Extent, Regional Distribution and Changes in Area of Different Classes of Wetlands.” Marine and Freshwater Research, 69, 1525–1533. http://dx.doi.org/10.1071/MF17377
• Dereli, M. A. & Tercan, E. (2020). Assessment of Shoreline Changes using Historical Satellite Images and Geospatial Analysis along the Lake Salda in Turkey. Earth Sci Inform,13, 709–718. https://doi.org/10.1007/s12145-020-00460-x
• Dinç, G. (2023). Unveiling shoreline dynamics and remarkable accretion rates in Lake Eğirdir (Turkey) using DSAS. The implications of climate change on lakes. Tema. Journal of Land Use, Mobility and Environment, 95-108. http://dx.doi.org/10.6092/1970-9870/10111
• Duru, U. (2017). Shoreline change assessment using multi-temporal satellite images: a case study of Lake Sapanca, NW Turkey. Environ Monit Assess, 189, 385. https://doi.org/10.1007/s10661-017-6112-2
• Erinç, S. (1986). Kıyılardan Yararlanmada Hukuki Düzenlemelere Jeomorfolojinin Katkısı. Jeomorfolojisi Dergisi, 14, 1-5 (in Turkish).
• Erol, O. (1989). Türkiye’de Kıyıların Doğal Niteliği, Kıyı ve Kıyı Varlıklarının Korunmasına İlişkin Kıyı Kanunu ve Uygulamaları Konusunda Jeomorfolojik Yaklaşım. İstanbul Üniversitesi Deniz Bilimleri ve Coğrafya Enstitüsü, 6, 15-46 (in Turkish).
• Gao, B. C. (1996). NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58(3), 257–266. https://doi.org/10.1016/S0034-4257(96)00067-3
• Gómez-Pazo, A., Payo, A., Paz-Delgado, M. V. & Delgadillo-Calzadilla, M. A. (2022). Open digital shoreline analysis system: ODSAS v1. 0. Journal of Marine Science and Engineering, 10(1), 26. https://doi.org/10.3390/jmse10010026
• Grottolli, H. Biausque, M. Jackson, D. & Cooper, J. A. (2023). Long-term drivers of shoreline change over two centuries on a headland-embayment beach. Earth Surface Processes and Landforms,, 1-21. https://doi.org/10.1002/esp.5641
• Hakkou, M., Maanan, M., Belrhaba, T., El khalidi, K., El Ouai, D. & Benmohammadi, A. (2018). Multi-decadal assessment of shoreline changes using geospatial tools and automatic computation in Kenitra coast, Morocco. Ocean & Coastal Management, 163, 232–239. https://doi.org/10.1016/j.ocecoaman.2018.07.003
• Himmelstoss, E. A., Henderson, R. E., Kratzmann, M. G. & Farris, A. S. (2018). Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide (No. 2018-1179). US Geological Survey.
• Hossain, S. Yasir, M. Wang, P. Ullah, S. Jahan, M., Hui, S. & Zhao, Z., (2021). Automatic shoreline extraction and change detection: A study on the southeast coast of Bangladesh. Marine Geology, 441, 1-15. https://doi.org/10.1016/j.margeo.2021.106628
• Hoşgören, M. Y. (1994). Lakes of Turkey. Turkish Geographical Review, 29, 19-51.
• Hu, X. & Wang, Y. (2020). Coastline Fractal Dimension of Mainland, Island, and Estuaries Using Multi-temporal Landsat Remote Sensing Data from 1978 to 2018: A Case Study of the Pearl River Estuary Area. Remote Sensing, 12, 2482. https://doi.org/10.3390/rs12152482
• Janki, S., Klop, K. W., Dooper, I. M., Weimar, W., Ijzermans, J. N. & Kok, N. F. (2015). More than a decade after live donor nephrectomy: a prospective cohort study. Transplant International, 28(11), 1268-1275. https://doi.org/10.1111/tri.12589
• Kale, M. M., Ataol, M. & Tekkanat, İ. S. (2019). Assessment of shoreline alterations using a Digital Shoreline Analysis System: a case study of changes in the Yeşilırmak Delta in northern Turkey from 1953 to 2017. Environ Monit Assess, 191, 398. https://doi.org/10.1007/s10661-019-7535-8
• Kaya, Y., Sanli, F. B. & Abdikan, S. (2023). Determination of long-term volume change in lakes by integration of UAV and satellite data: the case of Lake Burdur in Türkiye. Environ Sci Pollut Res, 30, 117729–117747. https://doi.org/10.1007/s11356-023-30369-z
• Kazı, H. & Karabulut, M. (2023). Monitoring the shoreline changes of the Göksu Delta (Türkiye) using geographical information technologies and predictions for the near future. International Journal of Geography and Geography Education, 50, 329-352. https://doi.org/10.32003/igge.1304403
• Khorshiddoust, A. M., Patel, N., Khalilzadeh, E. Bostanaba, A. S. & Tajbar, S., (2022). A comparative study of the surface level changes of Urmia Lake and Aral Lake during the period of 1988 to 2018 using satellite images. Front. Earth Science. https://doi.org/10.1007/s11707-022-1010-5
• Kılar, H. & Çiçek, İ. (2018). Shoreline Change Analysis in Göksu Delta by Using DSAS. Turkish Journal of Geographical Sciences, 16(1), 89-104. https://doi.org/10.1501/Cogbil_0000000192
• 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, 102737. https://doi.org/10.1016/j.rsma.2022.102737
• Kuleli, T. (2010). Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey Environ. Monit. Assess., 167, 387–397. https://doi.org/10.1007/s10661-009-1057-8
• Lazuardi, Z., Karim, A. & Sugianto, S. (2022). Analisis Perubahan Garis Pantai Menggunakan Digital Shoreline Analysis System (DSAS) di Pesisir Timur Kota Sabang. Jurnal Ilmiah Mahasiswa Pertanian, 7(1), 662-676.
• Maltby, E. & Barker, T. (2009). The Wetlands Handbook. John Wiley & Sons. ISBN:978-0-632-05255-4.
• McDonald, A. J., Gemmell, F. M. & Lewis, P. E. (1998). Investigation of the utility of spectral vegetation indices for determining information on coniferous forests. Remote Sensing of Environment, 66(3), 250-272. https://doi.org/10.1016/S0034-4257(98)00057-1
• McFeeters, S. K. (1996). The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features, International Journal of Remote Sensing, 17:7, 1425-1432, http://doi.org/10.1080/01431169608948714
• Myneni, R. B., Hall, F. G., Sellers, P. J. & Marshak, A. L. (1995). The interpretation of spectral vegetation indexes. IEEE Transactions on Geoscience and remote Sensing, 33(2), 481-486. https://doi.org/10.1016/0034-4257(94)00073-V
• Murray, J., Adam, E., Woodborne, S., Miller, D., Xulu, S. & Evans, M. (2023). Monitoring shoreline changes along the southwestern coast of South Africa from 1937 to 2020 using varied remote sensing data and approaches. Remote Sensing, 15(2), 317. https://doi.org/10.3390/rs15020317
• 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 & Geotechnology, 37(1), 81-95. https://doi.org/10.1080/1064119X.2018.1448912
• 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
• Paz-Delgado, M. V., Payo, A., Gómez-Pazo, A., Beck, A. L. & Savastano, S. (2022). Shoreline Change from Optical and Sar Satellite Imagery at Macro-Tidal Estuarine, Cliffed Open-Coast and Gravel Pocket-Beach Environments. Journal of Marine Science and Engineering, 10(5), 561. https://doi.org/10.3390/jmse10050561
• Pouye, I., Adjoussi, D.P., Ndione, J.A., Sall, A. (2023). Topography, Slope and Geomorphology’s Influences on Shoreline Dynamics along Dakar’s Southern Coast, Senegal. Coasts, 2023(3), 93–112. https://doi.org/10.3390/coasts3010006
• Richardson, A. J. & Wiegand, C. L. (1977). Distinguishing vegetation from soil background information. Photogrammetric engineering and remote sensing, 43(12), 1541-1552.
• Sakaoğlu, E. & Çepni, O. (2022). Türkiye’deki Tektonik Kökenli Ramsar Göllerinin Uzaktan Algılama Teknikleri ile Analizi (in Turikish). İksad Pulished House. ISBN: 978-625-8377-54-5.
• Samra, R. M. & Ali, R. R. (2021). Applying DSAS tool to detect coastal changes along Nile Delta, Egypt. The Egyptian Journal of Remote Sensing and Space Science, 24(3-1), 463-470. https://doi.org/10.1016/j.ejrs.2020.11.002
• Shen, L. & Li, C. (2010) Water body extraction from Landsat ETM+ imagery using adaboost algorithm 18th International Conference on Geoinformatics, IEEE (2010), 1-4. https://doi.org/10.1109/GEOINFORMATICS.010.5567762
• Sikder, M. S., Wang, J., Allen, G. H., Sheng, Y., Yamazaki, D., Song, C., Ding, M., Crétaux, J. F. & Pavelsky, T. M. (2023). Lake-TopoCat: a global lake drainage topology and catchment database, Earth Syst. Sci. Data, 15, 3483–3511, https://doi.org/10.5194/essd-15-3483-2023
• Singh, K. V., Setia, R., Sahoo, S., Prasad, A. & Pateriya, B. (2015). Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level. Geocarto International, 1-12. https://doi.org/10.1080/10106049.2014.965757
• Siyal, A. A., Solangi, G. S., 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, 102405 http://dx.doi.org/10.1016/j.rsma.2022.10245
• Song, Y., Shen, Y., Xie, R. & Li, J. (2021). A DSAS-based study of central shoreline change in Jiangsu over 45 years. Anthropocene Coasts, 4(1), 115-128. http://dx.doi.org/10.1139/anc-2020-0001
• Şenol, H. İ., Kaya, Y., Yiğit, A. Y. & Yakar, M. (2023). Extraction and geospatial analysis of the Hersek Lagoon shoreline with Sentinel-2 satellite data. Survey Review, 1–16. https://doi.org/10.1080/00396265.2023.2257969
• Tağıl, Ş. & Cürebal, İ. (2005). Remote Sensing and GIS Monitoring of Coastline in Altınova Coast Turkey. Fırat University Journal of Social Sciennces, 15(2), 51-68.
• Tian, H., Xu, K., Goes, J. I., Liu, Q., Gomes, H. d. R. & Yang, M. (2020). Shoreline Changes Along the Coast of Mainland China—Time to Pause and Reflect? ISPRS Int. J. Geo-Inf, 9, 572. https://doi.org/10.3390/ijgi9100572
• Topçu, H. & Atatanır, L. (2021). Determination of temporal changes in Bafa and Azap Lake Surface Areas. Akademik Ziraat Dergisi, 10(1), 115-122. https://doi.org/10.29278/azd.792589
• Topuz, M. (2018) Investigations Occurred Changes in The Coastal Line of Sarikum Lagoon (Sinop) by Using the Remote Sensing Techniques. International Journal of Social Science, 71, 481-493. http://dx.doi.org/10.9761/JASSS7853
• Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
• Turoğlu, H. (2009). The Coastal Law (number 3621) and Its Applied Problems. Turkish Geographical Review, 53, 31-40.
• Turoğlu, H. (2017). Deniz ve Göllerde Kıyı, Yasal ve Bilimsel Boyutlarıyla Kıyı, Jeomorfoloji Derneği Yayını, 1 (in Turkish).
• Uzun, M. (2021). Human-Induced Geomorphological Changes and Processes on the Coasts of the Gulf of Izmit. Journal of Geomorphological Researches, 7, 61-81. https://doi.org/10.46453/jader.983465
• Uzun, S. M. (2023) Analysis of Changing Shoreline with Natural and Anthropogenic Factors in Riva (Istanbul) Coast with Dsas Tool. Journal of Geomorphological Researches, 2023(11), 95-113. https://doi.org/10.46453/jader.1335105
• 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
• Woolway, R. I., Kraemer, B. M., Lenters, J. D., Merchant, C. J., O'Reilly, C. M. & Sharma, S. (2020). Global lake responses to climate change. Nature Reviews Earth & Environment, 1, 388–403, https://doi.org/10.1038/s43017-020-0067-5
• Wu, Q., Miao, S., Huang, H., Guo, M., Zhang, L., Yang, L. & Zhou, C. (2022). Quantitative Analysis on Coastline Changes of Yangtze River Delta based on High Spatial Resolution Remote Sensing Images. Remote Sensing, 14, 310. https://doi.org/10.3390/rs14020310
• Yasir, M., Hui, S., Hongxia, Z., Hossain, S., Fan, H., Zhang, Li. & Jixiang, Z. (2021). A Spatiotemporal Change Detection Analysis of Coastline Data in Qingdao, East China. Hindawi Scientific Programming, 1-10. https://doi.org/10.1155/2021/6632450
• Zuzek, P. J., Nairn, R. B. & Thieme, S. J. (2003). Spatial and Temporal Considerations for Calculating Shoreline Change Rates in the Great Lakes Basin. Journal of Coastal Research, 125–146.