Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery (Hardcover, 2015 ed.)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Springer Theses
Release date:	November 2014
First published:	2015
Authors:	Nasrin Nasrollahi
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Hardcover
Pages:	68
Edition:	2015 ed.
ISBN-13:	978-3-319-12080-5
Categories:	Books > Science & Mathematics > Physics > Applied physics & special topics > Geophysics Books > Earth & environment > Earth sciences > Meteorology > General
LSN:	3-319-12080-8
Barcode:	9783319120805

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