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Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery



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Éditeur :

Springer


Collection :

Springer Theses

Paru le : 2014-11-07



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Description

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.
Pages
68 pages
Collection
Springer Theses
Parution
2014-11-07
Marque
Springer
EAN papier
9783319120805
EAN EPUB
9783319120812
Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
6
Taille du fichier
2427 Ko
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Prix
94,94 €

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