Positioning Tropical Cyclone Center in a Single Satellite Image Using Vector Field Analysis

Yang, Jinfeng; Wang, Haoren

doi:10.1007/978-3-642-38466-0_5

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…The theoretical analysis and experimental results show that this method is reasonable and effective. Yang et al [8] combined pattern matching with the vector field analysis to determine the TC center position. The proposed method is very efficient for the TCs, which have clear spiral structure.…”

Section: Introductionmentioning

confidence: 99%

Tropical Cyclone Center Determination Algorithm by Texture and Gradient of Infrared Satellite Image

Zhang¹,

Luo²,

Chen³

et al. 2019

Understanding of Atmospheric Systems With Efficient Numerical Methods for Observation and Prediction

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A novel algorithm for tropical cyclone (TC) center determination is presented by using texture and gradient of infrared satellite image from geostationary satellite. Except those latter disappearing TC satellite images that are little valuable to a TC center determination, generally other periods of TC, all have an inner core. And the centers are generally determined in the inner core. Based on this, an efficient TC center determination algorithm is designed. First, the inner core of a TC is obtained. Then, according to the texture and gradient information of the inner core, the center location of the TC is determined. The effectiveness of the proposed TC center determination algorithm is verified by using Chinese FY-2C stationary infrared satellite image. And the location result is compared with that of the "tropical cyclone yearbook," which was compiled by Shanghai Typhoon Institute of China Meteorological Administration. Experimental results show that the proposed algorithm can provide a new technique that can automatically determine the center location for a TC based on infrared satellite image.

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Section: Introductionmentioning

confidence: 99%

Tropical Cyclone Center Determination Algorithm by Texture and Gradient of Infrared Satellite Image

Zhang¹,

Luo²,

Chen³

et al. 2019

Understanding of Atmospheric Systems With Efficient Numerical Methods for Observation and Prediction

View full text Add to dashboard Cite

show abstract

“…The existing typhoon center location methods mainly include [1]: cloud pattern recognition [2], wind field structure analysis [3], temperature/humidity structure retrieval [4], tempo-spatial movement matching [5], objective tropical cyclones location system [6] and so on. Among them, the cloud pattern recognition methods mainly include Dvorak technology (DT), mathematical morphology/feature extraction method and intelligent learning method.…”

Section: Introductionmentioning

confidence: 99%

Typhoon center location algorithm based on fractal feature and gradient of infrared satellite cloud image

2014

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An efficient algorithm for typhoon center location is proposed using fractal feature and gradient of infrared satellite cloud image. The centers are generally located in this region for a typhoon except the latter disappearing typhoon. The characteristics of dense cloud region are smoother texture and higher gray values than those of marginal clouds. So the window analysis method is used to select an appropriate cloud region. The window whose difference value between the sum of the gray-gradient co-occurrence matrix and fractal dimension is the biggest is chosen as the dense cloud region.The temperature gradient of the region, which is near typhoon center except typhoon eye, is small. Thus the gradient information is strengthened and is calculated by canny operator. Then we use a window to traverse the dense cloud region. If there is a closed curve, the region of curve is considered as the typhoon center region. Otherwise, the region in which there is the most texture intersection and the biggest density is considered as the typhoon center region. Finally, the geometric center of the center region is determined as the typhoon center location. The effectiveness is test by Chinese FY-2C stationary satellite cloud image. And the result is compared with the typhoon center location in the "tropical cyclone yearbook" which was compiled by Shanghai typhoon institute of China meteorological administration.Experimental results show that the high location accuracy can be obtained.

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Multi-channel Satellite Cloud Image Fusion in the Shearlet Transform Domain and Its Influence on Typhoon Center Location

Zhang

Chen

Ma³

2017

Lecture Notes in Computer Science

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Positioning Tropical Cyclone Center in a Single Satellite Image Using Vector Field Analysis

Cited by 4 publications

References 12 publications

Tropical Cyclone Center Determination Algorithm by Texture and Gradient of Infrared Satellite Image

Tropical Cyclone Center Determination Algorithm by Texture and Gradient of Infrared Satellite Image

Typhoon center location algorithm based on fractal feature and gradient of infrared satellite cloud image

Multi-channel Satellite Cloud Image Fusion in the Shearlet Transform Domain and Its Influence on Typhoon Center Location

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