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

Nasrollahi, Nasrin

 
9783319363325: Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery
Brossura
ISBN 10: 3319363328 ISBN 13: 9783319363325
Casa editrice: Springer, 2016

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer
Data di pubblicazione
2016
Lingua
Inglese
ISBN 10 
3319363328
ISBN 13 
9783319363325
Rilegatura
Copertina flessibile
Numero di pagine
92
Contatto del produttore
non disponibile
Persona responsabile
ProductSafety@springernature.com
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Altre edizioni note dello stesso titolo

9783319120805: Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery

Edizione in evidenza

ISBN 10:  3319120808 ISBN 13:  9783319120805
Casa editrice: Springer Nature, 2014
Rilegato