Temporal Dynamics of Lake Burdur’s Water Surface Area: A Two-Decade Remote Sensing Analysis and Future Forecasts


Erdem K. C., BAKIRMAN T., BAYRAM B.

Mersin Photogrammetry Journal, cilt.7, sa.1, ss.22-28, 2025 (Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 1
  • Basım Tarihi: 2025
  • Doi Numarası: 10.53093/mephoj.1628742
  • Dergi Adı: Mersin Photogrammetry Journal
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.22-28
  • Anahtar Kelimeler: AWEIsh, Google Earth Engine, Lake Burdur, NDWI, Remote Sensing
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Factors such as global warming, climate change, increasing population, and industrialization cause spatial and temporal changes in surface water resources. Burdur Lake, which is located in Turkey’s Lakes Region and has a tectonic origin with a closed basin characteristic, is one of the significant water resources affected by these changes. The aim of this study is to analyze the change in the surface water area of Burdur Lake between 2003 and 2023 and to provide data that will contribute to the sustainable management of the lake by making predictions for the future. In this context, the Normalized Difference Water Index (NDWI) and the Automated Water Extraction Index for shaded areas (AWEIsh) were applied to Landsat 5 and Landsat 8 satellite images. In order to increase spatial accuracy, short-term supporting analyses were also carried out using Sentinel-2 images. Based on the analysis results obtained with both methods, linear regression models were created; surface water area predictions for the years 2028 and 2033 were made, and the model accuracy was also tested. According to the NDWI method, the surface water area loss for the 2003–2023 period was calculated as 22.82%, and it is projected to reach 34.6% by 2033. According to the AWEIsh method, the water loss for the same period was calculated as 22.41%, and the estimate for 2033 was determined as 33.8%. The short-term analysis results based on Sentinel-2 data showed similarity with the Landsat data. The consistent results obtained with images and indices of different resolutions increase the reliability of the analyses; furthermore, they demonstrate that remote sensing–based approaches are an effective tool for predicting water loss in Burdur Lake.