DETERMINING AND MONITORING THE WATER QUALITY OF KIZILIRMAK RIVER OF TURKEY: FIRST RESULTS


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Gursoy O., Birdal A. C., Ozyonar F., Kasaka E.

36th International Symposium on Remote Sensing of the Environment (ISRSE), Berlin, Almanya, 11 - 15 Mayıs 2015, cilt.47, ss.1469-1474 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 47
  • Doi Numarası: 10.5194/isprsarchives-xl-7-w3-1469-2015
  • Basıldığı Şehir: Berlin
  • Basıldığı Ülke: Almanya
  • Sayfa Sayıları: ss.1469-1474
  • Anahtar Kelimeler: Water Resources Management, Hyperspectral Imaging, CHRIS Proba, Spectroradiometric Ground Measurements, Water Quality Assessment, Kizilirmak River
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

Water resources are getting more and more important with each passing day in case of survival of humanity. For this reason, assessing water resources' quality and also monitoring them have attracted lots of attention in the recent years. Remote sensing has been growing widely in the last decade and its resources are very usable when it comes to water resources management. In this study, by using remote sensing technology, satellite images that have 350 to 1050 nanometres wavelength band sensors ( e. g. CHRIS Proba) are used to determine the quality of the Kizilirmak River's water. Kizilirmak River is born and also pours out to sea in country limits of Turkey. It is the longest river of the country by the length of 1355 kilometres. Through the river's resources, ground based spectral measurements are made to identify the quality differences of the water at the test spots that have been determined before. In this context at Imranli, where the river contacts civilization for the first time, which is located in Sivas city of Turkey, samples are gathered in order to do ground based spectroradiometer measurements. These samples are gathered simultaneously with the image acquiring time of CHRIS Proba satellite. Spectral signatures that are obtained from ground measurements are used as reference data in order to classify CHRIS Proba satellite's hyperspectral images over the study area. Satellite images are classified based on Chemical Oxygen Demand ( COD), Turbidity and Electrical Conductivity ( EC) attributes. As a result, interpretations obtained from classified CHRIS Proba satellite hyperspectral images of the study area are presented.