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Tropical Cyclone Determination using Infrared Satellite Image

Journal: International Journal of Trend in Scientific Research and Development (Vol.3, No. 5)

Publication Date:

Authors : ;

Page : 2464-2467

Keywords : satellite image; tropical cyclone; FCM;

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Abstract

Many sub continents in the world have the region that are affected by the cyclone in every year. To prevent the loss of life and their assets, cyclone prediction is a major role because of directly related to the lives and household of human being. Satellite images provide an excellent view of clouds which can be used in weather forecasting and especially Infrared Red IR satellite images play in many environmental applications. To find the tropical cyclone TC center, the basic stage is to extract the main cloud of the cyclone. In manual segmentation, selection of the storm region is complicated, time consuming task and it also need the human experts for every time processing. The semi and fully automatic storm detection is sophisticated and difficult process because of the overlapping between boundaries of the cloud. Fuzzy C means FCM clustering and morphological image processing is applied for segmentation each infrared satellite images. The effectiveness is tested for infrared cyclone image over Kalpana satellite which is obtained from the INSAT satellite of India. 45 tropical cyclones are occurred during the period 1989 2014 over Bay of Bengal. Cyclones Nargis that mainly affected to Myanmar in 2 May 2008 as case study. Experimental results show that the high location accuracy can be obtained. Thu Zar Hsan | Myint Myint Sein "Tropical Cyclone Determination using Infrared Satellite Image" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27934.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/27934/tropical-cyclone-determination-using-infrared-satellite-image/thu-zar-hsan

Last modified: 2019-09-10 16:25:31