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NASA NTRS · 20190030822

Pixel-Based Model For High Latitude Dust Detection

Priftis, G.·Freitag, B.·Ramasubramanian, M.·Gurung, I.·Maskey, M.·Ramachandran, R.
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Abstract

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.

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Priftis, G., Freitag, B., Ramasubramanian, M., Gurung, I., Maskey, M., Ramachandran, R.. 2019-09-10. Pixel-Based Model For High Latitude Dust Detection. https://ntrs.nasa.gov/citations/20190030822

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NASA NTRS2019

Pixel Based Model For High Latitude Dust Detection

Current methods of dust detection rely on spectral sensitivity at visible (RGB) and infrared wavelengths. However, their application on different regions needs to be tuned to mitigate errors associated with background properties. High latitude dust (HLD) regions are characterized by surface with variable albedos and land cover, thus further complicating the dust detection. Leveraging supervised machine learning (ML) methods, we propose a new method accounting for regional differences of dust occurrence.

High latitude dust↗