Published 2023-09-30
Keywords
- River Course,
- Vegetation Region,
- Unsupervised Classification,
- NDWI,
- NDVI
How to Cite
Copyright (c) 2023 Advanced Geomatics
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Abstract
Rivers meet the agricultural and energy needs of people and living things. In addition, it is the most important external factor and process in the shaping of the surface where we live. Turkey is a very rich country in terms of rivers and wetlands in general. Göksu River, which is located in the south of Turkey and is one of the important rivers of the region, has been selected as the study area. Göksu is a river flowing through the provinces of Antalya, Konya, Karaman and Mersin in Turkey with a length of 260 km and a basin area of approximately 10,000 km2. Göksu originates from the Middle Taurus Mountains in two arms. The southern branch originates from the Geyik Mountains, and the northern branch originates from the Haydar Mountains and merges within the borders of the Mut District. From its confluence, the river takes the name Göksu, and then it empties into the Mediterranean Sea in the south of Silifke District. This study aims to investigate the temporal changes of Göksu River by using remote sensing methods. In the study, the Normalized Difference Water Index (NDWI) was used for the extraction of water bodies. In addition, the Normalized Difference Vegetation Index (NDVI) was used to study the temporal changes of forest and agricultural areas along the river line.
References
- Balçık, F. B., & Göksel, Ç. (2009). SPOT 5 ve Farklı Görüntü Birleştirme Algoritmaları, 12. Türkiye Harita Bilimsel ve Teknik Kurultayı, 11, 15.
- Chavez Jr, P. S. (1988). An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote sensing of environment, 24(3), 459-479.
- Cüce, H., & Bakan, G. (2009). Sürdürülebilir Su Kaynakları Yönetimi Açısından Uzaktan Algılama ve Coğrafi Bilgi Sistemlerinin Önemi. TMMOB Coğrafi Bilgi Sistemleri Kongresi, 2(06).
- Doğan, İ. (2008). Uzaktan algılama verileri ile kıyı çizgisi değişiminin zamansal olarak belirlenmesi: Alaçatı örneği. Master Thesis, Yıldız Technical University, Graduate School of Science and Engineering, İstanbul, Türkiye.
- Gülci, S., Gülci, N., & Yüksel, K. (2019). Monitoring water surface area and land cover change by using Landsat imagery for Aslantaş Dam Lake and its vicinity. Journal of the Institute of Science and Technology, 9(1), 100-110.
- Kaplan, G., Avdan, U., Avdan, Z. Y., & D Yildiz, N. (2016). Landsat uydu görüntüleri kullanılarak kuraklık izlenmesi (Akşehir gölü örneği). 6. Uzaktan Algilama-CBS Sempozyumu. Adana, Türkiye.
- Kayalik, M., & Çorumluoğlu, Ö. (2022). SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. International Journal of Environment and Geoinformatics, 9(4), 35-45.
- Liang, S. (2005). Quantitative remote sensing of land surfaces. John Wiley & Sons.
- Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
- Örmeci, C., & Ekercin, S. (2005). Uzaktan Algilama Tekniği ile Tuz Gölünde Su Kalitesi Değişim Analizi, 10. Türkiye Harita Bilimsel ve Teknik Kurultayı, Ankara, Türkiye.
- Özçalık, H., Torun, A. T., & Bilgilioğlu, S. S. (2020). Landsat uydu görüntüleri kullanılarak Mogan Gölü’nün su yüzeyi ve arazi örtü değişiminin belirlenmesi. Türkiye Uzaktan Algılama Dergisi, 2(2), 77-84.
- 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.