Pixel-Based Model For High Latitude Dust Detection

Pixel-Based Model For High Latitude Dust Detection

Dust has implications on the energy budget, ocean biodiversity, and economy at regional and global scales. Dust detection relies on spectral sensitivity at visible (RGB) and infrared wavelengths. Radiative properties of high latitude dust and the background surface albedo in these regions (>40°N,...

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Bibliographische Detailangaben
Hauptverfasser: Priftis, G., Freitag, B., Ramasubramanian, M., Gurung, I., Maskey, M., Ramachandran, R.
Format: Bild
Sprache:eng
Schlagworte:
Earth Resources And Remote Sensing
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Beschreibung
Zusammenfassung:Dust has implications on the energy budget, ocean biodiversity, and economy at regional and global scales. Dust detection relies on spectral sensitivity at visible (RGB) and infrared wavelengths. Radiative properties of high latitude dust and the background surface albedo in these regions (>40°N, >40°S) complicate current dust detection methods. Leveraging supervised machine learning (ML) methods, we propose a new method accounting for regional differences of dust occurrence.