Spatial Gap-Filling of Himawari-8 Hourly AOD Products Using Machine Learning with Model-Based AOD and Meteorological Data: A Focus on the Korean Peninsula
Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps tha...
Zapisane w:
| Główni autorzy: | , , , |
|---|---|
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
MDPI AG
2024-11-01
|
| Seria: | Remote Sensing |
| Hasła przedmiotowe: | |
| Dostęp online: | https://www.mdpi.com/2072-4292/16/23/4400 |
| Etykiety: |
Nie ma etykietki, Dołącz pierwszą etykiete!
|