Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery (Paperback, Softcover reprint of the original 1st ed. 2015)

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:	September 2016
First published:	2015
Authors:	Nasrin Nasrollahi
Dimensions:	235 x 155 x 5mm (L x W x T)
Format:	Paperback
Pages:	68
Edition:	Softcover reprint of the original 1st ed. 2015
ISBN-13:	978-3-319-36332-5
Categories:	Books > Professional & Technical > Environmental engineering & technology > General Books > Science & Mathematics > Physics > Applied physics & special topics > Geophysics Books > Earth & environment > Earth sciences > Meteorology > General Promotions
LSN:	3-319-36332-8
Barcode:	9783319363325

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