Paper Info
Title
Automatically Locate Tropical Cyclone Centers Using Top Cloud Motion Data Derived From Geostationary Satellite Images
Abstract
This article presents a novel technique for automatically locating tropical cyclone (TC) centers based on top cloud motions in consecutive geostationary satellite images. The high imaging rate and spatial resolution images of the Gaofen-4 geostationary satellite enable us to derive pixel-wise top cloud motion data of TCs, and from the data, TC spiral centers can be accurately determined based on an entirely different principle from those based on static image features. First, a physical motion field decomposition is proposed to eliminate scene shift and TC migration in the motion data without requiring any auxiliary geolocation data. This decomposition does not generate the artifacts that appear in the results of the previously published motion field decomposition. Then, an algorithm of a motion direction-based index embedded in a pyramid searching structure is fully designed to automatically and effectively locate the TC centers. The test shows that the TC concentric motions are more clearly revealed after the proposed motion field decomposition and the located centers are in good agreement with the cloud pattern centers in a visual sense and also with the best track data sets of four meteorological agencies.
Year
DOI
Venue
2019
10.1109/TGRS.2019.2931795
IEEE Transactions on Geoscience and Remote Sensing
Keywords
Field
DocType
Tropical cyclones,Spirals,Satellites,Sensors,Cloud computing,Spatial resolution,Clouds
Remote sensing,Tropical cyclone,Mathematics,Geostationary orbit,Cloud computing
Journal
Volume
Issue
ISSN
57
12
0196-2892
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Gang Zheng110919.51
Jianguo Liu210.68
Jingsong Yang301.35
Xiaofeng Li433679.94