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Uzaktan algılama ve CBS teknikleri kullanılarak Seyfe Gölü (Kırşehir) yüzey alanının zamansal değişiminin analizi

Year 2021, Volume: 11 Issue: 4, 1115 - 1128, 15.10.2021
https://doi.org/10.17714/gumusfenbil.848873

Abstract

Bu çalışmanın amacı çok bantlı uydu görüntüleri ile Seyfe Gölü yüzey alanının zamansal değişiminin Uzaktan Algılama (UA) ve Coğrafi Bilgi Sistemleri (CBS) teknikleri ile incelenmesidir. Çalışma alanı olan Seyfe Gölü, 1447 km2 lik yüzey drenaj alanına sahip Seyfe Havzasında yer almaktadır. Kapalı bir havzada yer alan göl alanının beslenimi yağış, yüzeysel akış ve akifer birimlerden beslenim ile gerçekleşmektedir. Gölün boşalımı ise, göl yüzeyinden buharlaşma ve drenaj kanalları ile gerçekleşmektedir. Bu çalışmada 1985-2020 yılları arasındaki Landsat çok bantlı uydu görüntüleri (Landsat 5 TM, Landsat 8 OLI/TIRS) kullanılmıştır ve her beş yıl için bir görüntü seçilmiştir. Uydu görüntülerinden türetilen Modifiye Edilmiş Normalize Fark Su İndeksi (MNDWI) yöntemi kullanılarak farklı yıllarda göl yüzey alanındaki değişimler hesaplanmıştır. 1985-2020 yılları arasında MNDWI yöntemi ile maksimum ve minimum göl alanları sırasıyla 66.87 km2 ve 1.86 km2 olarak hesaplanmıştır. 35 yılık süreçte, göl alanında % 93.78’lik bir azalma olduğu belirlenmiştir. Batimetri çalışmaları kapsamında ise; Devlet Su İşleri (DSİ) tarafından 2015 yılında hazırlanan göl hidrografik haritasındaki göl tabanı seviye ölçümlerinden göl batimetri haritası oluşturulmuştur. Göl alanının kot, hacim ve alan ilişkisinin belirlenmesine yönelik analizler gerçekleştirilmiştir. Oluşturulan göl batimetri haritasına göre; maksimum derinlik göl alanının kuzeyinde 1.95 m olarak hesaplanmıştır.

Supporting Institution

Herhangi bir kurumdan finansal bir destek alınmamıştır.

References

  • Ali, M., Dirawan, G., Hasim, A. and Abidin, M. (2019). Detection of changes in surface water bodies urban area with NDWI and MNDWI methods. International Journal on Advanced Science, Engineering and Information Technology, 9, 946. https://doi.org/10.18517/ijaseit.9.3.8692
  • Bao, Y. and Zhang, X. (2011). The study of lakes dynamic change based on RS and GIS-take Dalinor Lake as an example. Procedia Environmental Sciences, 10, 2376-2384. https://doi.org/10.1016/j.proenv.2011.09.370
  • Chang, B., He, K., Li, R., Sheng, Z. and Wang, H. (2017). Linkage of climatic factors and human activities with water level fluctuations in Qinghai Lake in the northeastern Tibetan Plateau, China. Water, 9(7), 552. https://doi.org/10.3390/w9070552
  • Deus, D. and Gloaguen R. (2013). Remote sensing analysis of lake dynamics in semi-arid regions: implication for water resource management. Lake Manyara, East African Rift, northern Tanzania. Water, 5(2), 698-727. https://doi.org/10.3390/w5020698
  • Dost, R. J. J. and Mannaerts, C. M. (2008). Generation of lake bathymetry using sonar, satellite imagery and GIS. J. Dangermond (Ed.), ESRI 2008: Proceedings of the 2008 ESRI International User Conference, (pp. 1-5.), Redmond: ESRI.
  • DSİ, (2004). Seyfe Ovası hidrojeolojik revize etüt raporu. Kayseri: Devlet Su İşleri XII Bölge Müdürlüğü, Jeoteknik Hizmetler ve Yeraltı Suları Dairesi Başkanlığı.
  • DSİ, (2015). Seyfe Gölü hidrografik haritası. Ankara: Devlet Su İşleri Etüt, Planlama ve Tahsisler Dairesi Başkanlığı.
  • El Asmar, H., Hereher, M. and Kafrawy, S. (2013). Surface area change detection of the Burullus Lagoon, north of the Nile Delta, Egypt, using water indices: a remote sensing approach. The Egyptian Journal of Remote Sensing and Space Science, 16(1), 119-123. https://doi.org/10.1016/j.ejrs.2013.04.004
  • Fang Fang, Z., Bing, Z., Jun Sheng, L., Qian, S., Yuan Feng, W. and Yang, S. (2011). Comparative analysis of automatic water identification method based on multispectral remote sensing. Procedia Environmental Sciences, 11, 1482-1487. https://doi.org/10.1016/j.aqpro.2015.02.095
  • Howari, F., Sherif, M., Singh, V. and Alasam Alzaabi, M. (2007). Application of GIS and Remote Sensing techniques in identification, assessment and development of groundwater resources. Thangarajan, M. (Eds.), Groundwater. (pp. 1-25.). Germany, Netherlands: Springer.
  • Gao, B. C. (1996). NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257-266. https://doi.org/10.1016/S0034-4257(96)00067-3
  • Gautam, V., Gaurav, P., Murugan, P. and Annadurai, M. (2015). Assessment of surface water dynamics in Bangalore using WRI, NDWI, MNDWI, supervised classification and K-T transformation, Aquatic Procedia, 4, 739-746.
  • Gülci, S., Gülci, N. ve Yüksel, K. (2019). Aslantaş Baraj Gölü ve çevresinin su yüzey alanı ve arazi örtüsü değişiminin Landsat uydu görüntüleri kullanılarak izlenmesi. Journal of the Institute of Science and Technology, 9(1), 100-110. https://doi.org/10.21597/jist.419221
  • Haibo, Y., Zongmin. W., Hongling, Z. and Yu, G. (2011). Water body extraction methods study based on RS and GIS. Procedia Environmental Sciences, 10, 2619-2624. https://doi.org/10.1016/j.proenv.2011.09.407
  • Kiage, L. and Douglas, P. (2019). Linkages between land cover change, lake shrinkage, and sublacustrine influence determined from remote sensing of select Rift Valley Lakes in Kenya. Science of the Total Environment, 709, 136022. https://doi.org/10.1016/j.scitotenv.2019.136022
  • McFeeters, S. K. (1996). The use of normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17, 1425-1432. https://doi.org/10.1080/01431169608948714
  • Mutlu, A., Kazancı, B., Özçeti̇n, A. ve Sarıyılmaz, F. (2020). Akşehir Gölü zamansal değişiminin bant oranlama yöntemleri ile belirlenmesi. Türkiye Uzaktan Algılama Dergisi, 2(1), 22-28. https://dergipark.org.tr/tr/pub/tuzal/issue/52699/650018
  • Naik, B. and Anuradha, B. (2018). Extraction of water-body area from high-resolution Landsat imagery. International Journal of Electrical and Computer Engineering, 8, 4111. https://doi.org/10.11591/ijece.v8i6.pp.4111-4119
  • Nandi, D., Chowdhury, R., Mohapatra, J., Mohanta, K. and Ray, D. (2019). Automatic delineation of water bodies using multiple spectral indices. International Journal of Scientific Research in Science, Engineering and Technology, 4, 498-512.
  • Reis, S. ve Yılmaz, H.M. (2008). Temporal monitoring of water level changes in Seyfe Lake using remote sensing. Hydrological Processes, 22, 4448-4454. https://doi.org/10.1002/hyp.7047
  • Sayhan, H. (2001). Seyfe Gölü eski seviyelerinin Kuvaterner jeomorfolojisi açısından etüdü. Gazi Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 2(2), 55-73. URL-1, https://bolge9.tarimorman.gov.tr/Menu/85/Kirsehir-Seyfe-Golu-Ramsar-Alani. 12 Temmuz 2021.
  • URL-2, https://earthexplorer.usgs.gov. 12 Temmuz 2021.
  • Xu, H. (2006). Modification of normalized difference water index (NDWI) to enhance open water features in remote sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033. https://doi.org/10.1080/01431160600589179
  • Yaman, M. ve Yigit Avdan, Z. (2018). Uydu görüntüleri kullanılarak su kütlesi değişiminin izlenmesi: Seyfe Gölü örneği. 2018 VII. Uzaktan Algılama ve CBS Sempozyumu (UZAL-CBS), Eskişehir.
  • Zhai, K., Wu, X., Qin, Y. and Du, P. (2015). Comparison of surface water extraction performances of different classic water indices using OLI and TM imageries in different situations. Geo-spatial Information Science, 18, 32-42. https://doi.org/10.1080/10095020.2015.1017911
  • Zhou, W., Li, Z., Ji, S., Hua, C. and Fan, W. (2015). A new index model NDVI-MNDWI for water object extraction in hybrid area. Bian, F., Xie, Y. (eds), Communications in Computer and Information Science (s. 513-519.). Berlin: Springer. https://doi.org/10.1007/978-3-662-45737-5_51

Analysis of temporal changes on the surface area of the Seyfe Lake (Kırşehir) using Remote sensing and GIS techniques

Year 2021, Volume: 11 Issue: 4, 1115 - 1128, 15.10.2021
https://doi.org/10.17714/gumusfenbil.848873

Abstract

The aim of the study is to investigate temporal changes on the surface area of the Seyfe Lake with multispectral satellite images by using Remote Sensing (RS) and Geographical Information Systems (GIS) techniques. Lake Seyfe, a study area, is located in the Seyfe Basin with a catchment area of 1447 km2. The closed basin of Seyfe Lake is recharge by precipitation, surface runoff and from surrounding aquifer units. Discharge of the lake takes place through evaporation and drainage channels. Landsat multispectral satellite images (Landsat 5 TM and Landsat 8 OLI/TIRS) are used in this study; with one scene selected for every five years ranging between 1985-2020. The Modified Normalized Difference Water Index (MNDWI) method is used to delineate the lake boundaries and the changes in the lake surface area for the respective years calculated. Based on the MNDWI method, maximum and minimum surface area measurements of the Seyfe Lake are found to be 66.86 km2 and 1.86 km2, respectively in between 1985-2020. It was determined that the lake surface area decreased by 93.78 % during this 35 year period. Within the scope of bathymetry studies; the elevation of the lake bottom is derived from the hydrographic map of the lake area prepared by General Directorate of State Hydraulic Works (DSI) in 2015. Analyses were carried out to establish the relationship between elevation, surface area and volume of the lake body. According to the bathymetric map, maximum depth was calculated in the northern part of the lake and is around 1.95 m.

References

  • Ali, M., Dirawan, G., Hasim, A. and Abidin, M. (2019). Detection of changes in surface water bodies urban area with NDWI and MNDWI methods. International Journal on Advanced Science, Engineering and Information Technology, 9, 946. https://doi.org/10.18517/ijaseit.9.3.8692
  • Bao, Y. and Zhang, X. (2011). The study of lakes dynamic change based on RS and GIS-take Dalinor Lake as an example. Procedia Environmental Sciences, 10, 2376-2384. https://doi.org/10.1016/j.proenv.2011.09.370
  • Chang, B., He, K., Li, R., Sheng, Z. and Wang, H. (2017). Linkage of climatic factors and human activities with water level fluctuations in Qinghai Lake in the northeastern Tibetan Plateau, China. Water, 9(7), 552. https://doi.org/10.3390/w9070552
  • Deus, D. and Gloaguen R. (2013). Remote sensing analysis of lake dynamics in semi-arid regions: implication for water resource management. Lake Manyara, East African Rift, northern Tanzania. Water, 5(2), 698-727. https://doi.org/10.3390/w5020698
  • Dost, R. J. J. and Mannaerts, C. M. (2008). Generation of lake bathymetry using sonar, satellite imagery and GIS. J. Dangermond (Ed.), ESRI 2008: Proceedings of the 2008 ESRI International User Conference, (pp. 1-5.), Redmond: ESRI.
  • DSİ, (2004). Seyfe Ovası hidrojeolojik revize etüt raporu. Kayseri: Devlet Su İşleri XII Bölge Müdürlüğü, Jeoteknik Hizmetler ve Yeraltı Suları Dairesi Başkanlığı.
  • DSİ, (2015). Seyfe Gölü hidrografik haritası. Ankara: Devlet Su İşleri Etüt, Planlama ve Tahsisler Dairesi Başkanlığı.
  • El Asmar, H., Hereher, M. and Kafrawy, S. (2013). Surface area change detection of the Burullus Lagoon, north of the Nile Delta, Egypt, using water indices: a remote sensing approach. The Egyptian Journal of Remote Sensing and Space Science, 16(1), 119-123. https://doi.org/10.1016/j.ejrs.2013.04.004
  • Fang Fang, Z., Bing, Z., Jun Sheng, L., Qian, S., Yuan Feng, W. and Yang, S. (2011). Comparative analysis of automatic water identification method based on multispectral remote sensing. Procedia Environmental Sciences, 11, 1482-1487. https://doi.org/10.1016/j.aqpro.2015.02.095
  • Howari, F., Sherif, M., Singh, V. and Alasam Alzaabi, M. (2007). Application of GIS and Remote Sensing techniques in identification, assessment and development of groundwater resources. Thangarajan, M. (Eds.), Groundwater. (pp. 1-25.). Germany, Netherlands: Springer.
  • Gao, B. C. (1996). NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257-266. https://doi.org/10.1016/S0034-4257(96)00067-3
  • Gautam, V., Gaurav, P., Murugan, P. and Annadurai, M. (2015). Assessment of surface water dynamics in Bangalore using WRI, NDWI, MNDWI, supervised classification and K-T transformation, Aquatic Procedia, 4, 739-746.
  • Gülci, S., Gülci, N. ve Yüksel, K. (2019). Aslantaş Baraj Gölü ve çevresinin su yüzey alanı ve arazi örtüsü değişiminin Landsat uydu görüntüleri kullanılarak izlenmesi. Journal of the Institute of Science and Technology, 9(1), 100-110. https://doi.org/10.21597/jist.419221
  • Haibo, Y., Zongmin. W., Hongling, Z. and Yu, G. (2011). Water body extraction methods study based on RS and GIS. Procedia Environmental Sciences, 10, 2619-2624. https://doi.org/10.1016/j.proenv.2011.09.407
  • Kiage, L. and Douglas, P. (2019). Linkages between land cover change, lake shrinkage, and sublacustrine influence determined from remote sensing of select Rift Valley Lakes in Kenya. Science of the Total Environment, 709, 136022. https://doi.org/10.1016/j.scitotenv.2019.136022
  • McFeeters, S. K. (1996). The use of normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17, 1425-1432. https://doi.org/10.1080/01431169608948714
  • Mutlu, A., Kazancı, B., Özçeti̇n, A. ve Sarıyılmaz, F. (2020). Akşehir Gölü zamansal değişiminin bant oranlama yöntemleri ile belirlenmesi. Türkiye Uzaktan Algılama Dergisi, 2(1), 22-28. https://dergipark.org.tr/tr/pub/tuzal/issue/52699/650018
  • Naik, B. and Anuradha, B. (2018). Extraction of water-body area from high-resolution Landsat imagery. International Journal of Electrical and Computer Engineering, 8, 4111. https://doi.org/10.11591/ijece.v8i6.pp.4111-4119
  • Nandi, D., Chowdhury, R., Mohapatra, J., Mohanta, K. and Ray, D. (2019). Automatic delineation of water bodies using multiple spectral indices. International Journal of Scientific Research in Science, Engineering and Technology, 4, 498-512.
  • Reis, S. ve Yılmaz, H.M. (2008). Temporal monitoring of water level changes in Seyfe Lake using remote sensing. Hydrological Processes, 22, 4448-4454. https://doi.org/10.1002/hyp.7047
  • Sayhan, H. (2001). Seyfe Gölü eski seviyelerinin Kuvaterner jeomorfolojisi açısından etüdü. Gazi Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 2(2), 55-73. URL-1, https://bolge9.tarimorman.gov.tr/Menu/85/Kirsehir-Seyfe-Golu-Ramsar-Alani. 12 Temmuz 2021.
  • URL-2, https://earthexplorer.usgs.gov. 12 Temmuz 2021.
  • Xu, H. (2006). Modification of normalized difference water index (NDWI) to enhance open water features in remote sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033. https://doi.org/10.1080/01431160600589179
  • Yaman, M. ve Yigit Avdan, Z. (2018). Uydu görüntüleri kullanılarak su kütlesi değişiminin izlenmesi: Seyfe Gölü örneği. 2018 VII. Uzaktan Algılama ve CBS Sempozyumu (UZAL-CBS), Eskişehir.
  • Zhai, K., Wu, X., Qin, Y. and Du, P. (2015). Comparison of surface water extraction performances of different classic water indices using OLI and TM imageries in different situations. Geo-spatial Information Science, 18, 32-42. https://doi.org/10.1080/10095020.2015.1017911
  • Zhou, W., Li, Z., Ji, S., Hua, C. and Fan, W. (2015). A new index model NDVI-MNDWI for water object extraction in hybrid area. Bian, F., Xie, Y. (eds), Communications in Computer and Information Science (s. 513-519.). Berlin: Springer. https://doi.org/10.1007/978-3-662-45737-5_51
There are 26 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Cansu Yurteri 0000-0002-4944-0168

Türker Kurttaş 0000-0003-1426-566X

Publication Date October 15, 2021
Submission Date December 29, 2020
Acceptance Date July 16, 2021
Published in Issue Year 2021 Volume: 11 Issue: 4

Cite

APA Yurteri, C., & Kurttaş, T. (2021). Uzaktan algılama ve CBS teknikleri kullanılarak Seyfe Gölü (Kırşehir) yüzey alanının zamansal değişiminin analizi. Gümüşhane Üniversitesi Fen Bilimleri Dergisi, 11(4), 1115-1128. https://doi.org/10.17714/gumusfenbil.848873