Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery (Springer Theses) - Softcover

Nasrollahi, Nasrin

 
9783319363325: Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery (Springer Theses)
Softcover
ISBN 10: 3319363328 ISBN 13: 9783319363325
Publisher: Springer, 2016

Synopsis

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.

"synopsis" may belong to another edition of this title.

From the Back Cover

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.

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2016
Language
English
ISBN 10 
3319363328
ISBN 13 
9783319363325
Binding
Paperback
Number of pages
89

Other Popular Editions of the Same Title

9783319120805: Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery (Springer Theses)

Featured Edition

ISBN 10:  3319120808 ISBN 13:  9783319120805
Publisher: Springer, 2014
Hardcover