Detection of tropical cyclone genesis via quantitative satellite ocean surface wind pattern and intensity analyses using decision trees

Microwave remote sensing can be used to measure ocean surface winds, which can be used to detect tropical cyclone (TC) formation in an objective and quantitative way. This study develops a new model using WindSat data and a machine learning approach. Dynamic and hydrologic indices are quantified fro...

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Vydáno v:	Remote sensing of environment Ročník 183; s. 205 - 214
Hlavní autoři:	Park, Myung-Sook, Kim, Minsang, Lee, Myong-In, Im, Jungho, Park, Seonyoung
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Inc 15.09.2016
Témata:	algorithms artificial intelligence Circulation convection Cyclones decision support systems Decision trees Disturbances Dynamic pattern and intensity recognition Dynamics Formations hurricanes hydrology Machine learning methodology Microwave sea surface wind Ocean surface rain Rainfall remote sensing satellites Tropical cyclone wind speed Dynamic pattern and intensity recognition Microwave sea surface wind Tropical cyclone Machine learning
ISSN:	0034-4257, 1879-0704
On-line přístup:	Získat plný text
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