A Spatial temporal classification analysis and visualization of tropical cyclone tracks in Bay of Bengal using GIS

A Spatial temporal classification analysis and visualization of tropical cyclone tracks in Bay of Bengal using GIS | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Spatial temporal classification analysis and visualization of tropical cyclone tracks in Bay of Bengal using GIS Vanitha N, Rene Robin C R, Doreen Hephzibah Miriam D This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-509304/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Tropical cyclones (TC) are among the most devastating forms of natural hazards and the east coast of India is more prone to TC landfall causing significant socio-economic impacts. The Bay of Bengal (BoB) which forms the eastern sub basin of North Indian Ocean experiences the seasonally reversing monsoon, depression and TCs. In this study TC best track dataset of NIO basin over the period 1960–2016 from the IBTrACKs archive maintained by NOAA are used. In this work Firefly optimization is coupled with FCM for TC tracks classification. The classical FCM uses random initialization of cluster centroid often gets trapped in local optimal problem. The firefly algorithm is applied on the FCM for the cluster centroid computation, in this way improving the efficiency of FCM algorithm. The obtained classes are then projected in the visualization space. Visualizations are generated using the GIS environment to gain insight into the spatial distribution of TC tracks over decades. This study aims to develop a comprehensive assessment of variability in tropical cyclones with respect to ENSO modulated events, inter decadal variability and track sinuosity. In this paper we attempt to convey the cognitive results of comparative visualizations of TC tracks over Arabian Sea and Bay of Bengal sub basin during the strong, very strong El Niño and La Niña events. Finally we use Parallel Coordinate Plot (PCP) a visualization technique to demonstrate the correlation patterns of the TC parameters. Climate Analysis and Modeling Visualization Tropical Cyclone tracks Classification Parallel coordinate Plots Full Text Declaration Note: The designations employed and the presentation of the material on the included maps do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. These maps have been provided by the authors. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-509304","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":31940463,"identity":"6e3e3d51-14b0-4906-a408-45b0819d1928","order_by":0,"name":"Vanitha N","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYJCCA4wNEIYEA4MNkGJsPEBQy0GEljSQlgaCWhiQtByGGIJPtcHxswcPf9xhxyA/I/fgjY97ztutbT8MtKXGJhqnljN5CQcOnklmMLiRl2w549nt5G1nEoFajqXlNuDQItmQY3DgYBszg4FEjpk0z4HbyWYHgFoYGw7j1tL/BqSlHugwoJY/B84lm51/iF8LvwTYFqCvbwC1MBw4YGd2g4At/BJAW862HecxOPPG2LLnQHKC2Q2gLQl4/MLGn2P8obKtWk6+Pcfwxo8DdvZm59MfPvhQY4NTCwzwwBiJYJUJBJSjAHtSFI+CUTAKRsHIAAD8umjOhdCo9AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3149-7983","institution":"Sri Sai Ram Engineering College","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Vanitha","middleName":"","lastName":"N","suffix":""},{"id":31940464,"identity":"4d7ec237-56d4-4315-95e1-2ce9e2106940","order_by":1,"name":"Rene Robin C R","email":"","orcid":"","institution":"Sri Sai Ram Engineering College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rene","middleName":"Robin C","lastName":"R","suffix":""},{"id":31940465,"identity":"8f2bfd14-ad40-446d-bb4c-0cd85bac0319","order_by":2,"name":"Doreen Hephzibah Miriam D","email":"","orcid":"","institution":"Computational Intelligence Research Foundation","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Doreen","middleName":"Hephzibah Miriam","lastName":"D","suffix":""}],"badges":[],"createdAt":"2021-05-09 18:09:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-509304/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-509304/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13642282,"identity":"039f545a-5998-4dad-ab2d-9c15e9f214e0","added_by":"auto","created_at":"2021-09-17 09:06:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1122817,"visible":true,"origin":"","legend":"","description":"","filename":"SpatioTemporalClassificationandVisualizationofTC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-509304/v1_covered.pdf"},{"id":10162168,"identity":"ceb87be3-8af8-449c-a7bc-57b3bb96a7ce","added_by":"auto","created_at":"2021-06-09 14:57:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1119282,"visible":true,"origin":"","legend":"","description":"","filename":"SpatioTemporalClassificationandVisualizationofTC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-509304/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"A Spatial temporal classification analysis and visualization of tropical cyclone tracks in Bay of Bengal using GIS","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-509304/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."},{"header":"Declaration","content":"\u003cp\u003eNote: The designations employed and the presentation of the material on the included maps do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. 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The Bay of Bengal (BoB) which forms the eastern sub basin of North Indian Ocean experiences the seasonally reversing monsoon, depression and TCs. In this study TC best track dataset of NIO basin over the period 1960\u0026ndash;2016 from the IBTrACKs archive maintained by NOAA are used. In this work Firefly optimization is coupled with FCM for TC tracks classification. The classical FCM uses random initialization of cluster centroid often gets trapped in local optimal problem. The firefly algorithm is applied on the FCM for the cluster centroid computation, in this way improving the efficiency of FCM algorithm. The obtained classes are then projected in the visualization space. Visualizations are generated using the GIS environment to gain insight into the spatial distribution of TC tracks over decades. This study aims to develop a comprehensive assessment of variability in tropical cyclones with respect to ENSO modulated events, inter decadal variability and track sinuosity. 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