FULL-PHYSICS INVERSE LEARNING MACHINE FOR SATELLITE REMOTE SENSING OF OZONE PROFILE SHAPES AND TROPOSPHERIC COLUMNS
Characterizing vertical distributions of ozone from nadir-viewing satellite measurements is known to be challenging, particularly the ozone information in the troposphere. A novel retrieval algorithm called Full-Physics Inverse Learning Machine (FP-ILM), has been developed at DLR in order to estimat...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-04-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-3/1995/2018/isprs-archives-XLII-3-1995-2018.pdf |