This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.
Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.
The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
| ISBN: | 9783319363325 |
| Publication date: | 10th September 2016 |
| Author: | Nasrin Nasrollahi |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Paperback |
| Pagination: | 68 pages |
| Series: | Springer Theses |
| Genres: |
Meteorology and climatology Applied physics The environment |
This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space.
Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved.
The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.
Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery features in the following genres: Meteorology and climatology, Applied physics, The environment
Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery is available in Paperback, Hardback
Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery was written by Nasrin Nasrollahi and published by Springer an imprint of Springer International Publishing
Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery has 68 pages
Yes it is part of Springer Theses series