Albedo Retrieval From Sentinel-2 by New Narrow-to-Broadband Conversion Coefficients

Bonafoni S., ŞEKERTEKİN A.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, cilt.17, sa.9, ss.1618-1622, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 9
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1109/lgrs.2020.2967085
  • Dergi Adı: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, Geobase, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1618-1622
  • Anahtar Kelimeler: Land surface, Spatial resolution, Earth, Remote sensing, Estimation, Sensors, Satellite broadcasting, Albedo, narrow-to broadband conversion, Sentinel-2, Surface Radiation Budget Network (SURFRAD), urban environment, LAND-SURFACE ALBEDO, REFLECTANCE, SATELLITE, NADIR
  • Çukurova Üniversitesi Adresli: Evet

Özet

Surface albedo in the rural and urban environment is one of the most influencing parameters in the evaluation of the radiative forcing of the land surface. Satellite remote sensing is an efficient tool for surface broadband albedo estimation with various spatial resolutions. Different retrieval algorithms were proposed and tested in the literature. This letter focuses on the narrow-to-broadband conversion algorithm applied to Sentinel-2 reflective data, using its best spatial resolution (10 m). New narrow-to-broadband coefficients for albedo retrieval were computed. Their accuracy was tested with ground-based measurements in two different environments and compared with another algorithm introduced in the literature. The application of these coefficients for the albedo estimation requires the assumption of Lambertian surface and clear sky conditions. The first test was performed on six field stations of the Surface Radiation Budget Network (SURFRAD), and the second test was carried out within an urban area (Perugia, Central Italy), to better evaluate the impact of the spatial resolution on the albedo estimation from spaceborne sensors. The obtained root mean square error (RMSE) for the two tests presented very good values for both algorithms (around 0.02), with a slightly better performance of the proposed coefficients, especially for the higher albedo values. In the urban test, the retrieved albedo from Sentinel-2 with a 10-m pixel size provided considerably better results than the Landsat 8 estimation (30-m), highlighting the benefit of using a finer resolution in heterogeneous environments.