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Tracking severe weather storms in Doppler radar images
Author(s) -
Cheng D.,
Mercer R. E.,
Barron J. L.,
Joe P.
Publication year - 1998
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/(sici)1098-1098(1998)9:4<201::aid-ima3>3.0.co;2-e
Subject(s) - storm , fuzzy logic , computer science , radar , thresholding , meteorology , doppler radar , artificial intelligence , algorithm , computer vision , remote sensing , real time computing , image (mathematics) , geology , geography , telecommunications
We describe an automatic storm‐tracking system to help with the forecasting of severe storms. In this article, we present the concepts of fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, and fuzzy angle between two nonzero fuzzy vectors, that are used in our tracking algorithm. These concepts are used to overcome some of the limitations of our previous work, where fixed center‐of‐mass storm centers did not provide smooth tracks over time, while at the same time, their detection was very threshold sensitive. Our algorithm uses region splitting with dynamic thresholding to determine storm masses in Doppler radar intensity images. We represent the center of a hypothesized storm using a fuzzy point. These fuzzy storm centers are then tracked over time using an incremental relaxation algorithm. We have developed a visualization program using the X11 Athena toolkit for our storm visualization tool. The algorithm was tested on seven real radar image sequences obtained from the Atmospheric Environment Service radar station at King City, Ontario, Canada. We can obtain storm tracks that are long and smooth and which closely match an expert meteorologist's perception. © 1998 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 9, 201–213, 1998