Thermal anomaly detection of industrial zones with MNF and ICA


Arslan E.

Turkish Journal of Geosciences, cilt.2, sa.1, ss.18-26, 2021 (Hakemli Dergi)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2 Sayı: 1
  • Basım Tarihi: 2021
  • Doi Numarası: 10.48053/turkgeo.811887
  • Dergi Adı: Turkish Journal of Geosciences
  • Derginin Tarandığı İndeksler: Asos İndeks
  • Sayfa Sayıları: ss.18-26
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Hayır

Özet

Thermal anomalies can be detected with the help of the imagery provided by the satellite systems such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). ASTER provides five thermal bands for the effective analysis of thermal anomalies. In order to achieve this goal, considering the physical phenomena, many satellite signal processing methods and algorithms can be used. In this study, depending on the studied area, heat characteristics and extent are presented by using four days of data from daytime and nighttime scenes. In order to define the thermal anomalies for the studied area, Land Surface Temperature (LST) was estimated by inverse Planck function approach for all TIR bands. Minimum Noise Fraction (MNF) and Independent Component Analysis (ICA) methods were applied on all thermal infrared (TIR) bands. The results of MNF and ICA components show location of the thermal anomalies for industrial complexes especially in nighttime scenes.