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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| creator | Priftis, G. Freitag, B. Ramasubramanian, M. Gurung, I. Maskey, M. Ramachandran, R. |
| description | 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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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.</abstract><cop>Marshall Space Flight Center</cop><oa>free_for_read</oa></addata></record> |
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| subjects | Earth Resources And Remote Sensing |
| title | Pixel-Based Model For High Latitude Dust Detection |
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