INVESTIGATION OF NDSI-BASED SNOW COVER CHANGE AND TEMPORAL DYNAMICS OF THE ERZURUM PALANDOKEN MOUNTAINS USING MODIS DATA

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Koca C., Yılmaz O. S., Kaymaz Ç. K.

INTERNATIONAL ERZURUM SCIENTIFIC RESEARCH CONGRESS, Erzurum, Türkiye, 24 - 26 Nisan 2026, ss.54-65, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Erzurum
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.54-65
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Atatürk Üniversitesi Adresli: Evet

Özet

In this study, the snow cover area and Normalized Difference Snow Index (NDSI) changes of the Palandöken Mountains, located in the Erzurum province, were analyzed between 2010 and 2025 using MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data. NASA’s MODIS/061/MOD10A1 product was utilized in the study, and the analyses were conducted on the

Google Earth Engine (GEE) platform. NDSI values obtained from daily satellite imagery were statistically compiled on a monthly and annual basis; snow cover area calculations were performed over a total study area of 182,551 hectares. For the 2010–2025 period, the annual average snow cover area was calculated as 174,259 hectares. The lowest values were identified in 2022, with a snow cover area of 129,307 hectares and an NDSI value of 64.7, while the highest values were obtained in 2016, with 181,538 hectares of snow cover and an NDSI value of 71.9. The decrease observed particularly in 2022 is thought to be associated with climatic variability. The Pearson correlation coefficient calculated between the annual snow cover area and NDSI values is 0.719, revealing a strong and positive relationship between the two variables. Monthly analyses observed that snow cover begins in October, reaches its peak during the January–February–March period with NDSI values between approximately 70 and 79, and declines rapidly as of May–June. The highest monthly NDSI value was measured in February 2016 at 79.8. The findings demonstrate that MODIS-based NDSI analysis is an effective tool for long-term monitoring of snow cover dynamics in high-altitude mountainous areas. This study provides a significant reference for the evaluation of snow resources in the Palandöken Mountains in terms of water resources management and climate change studies.