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Title: :  Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning
PaperId: :  19285
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 1 2023
DUI:    16.0415/IJARIIE-19285
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Abhijna K CDayananda Sagar Academy Of Technology And Management
B G ShreyasDayananda Sagar Academy Of Technology And Management
BhargaviDayananda Sagar Academy Of Technology And Management
Dhanush Gowda SDayananda Sagar Academy Of Technology And Management
Dr. Madhumala R BDayananda Sagar Academy Of Technology And Management

Abstract

Computer Engineering
Satellite image classification, cyclone intensity prediction, satellite images, Deep Convolutional Neural Network (DCNN), Insat 3D IR, metadata
This survey paper is based on the review of Cyclone strength prediction utilizing INSAT-3D satellite photos, using review articles that were published from 2018 to 2022. A natural disaster is an unanticipated event that can harm the environment at any time and at any place. There are several natural disasters that cause harm to society and its citizens. disasters including earthquakes, cyclones, floods, tsunamis, wildfires, landslides, and volcanic eruptions. Some of the frequent natural calamities include avalanches, heat waves, and many others. Cyclones are enormous masses of air that move counterclockwise in the Northern Hemisphere and clockwise in the Southern Hemisphere as they revolve around a powerful center of low atmospheric pressure. A cyclone is, in general, a large storm that produces heavy rain and gusts. Tropical cyclones, often known as typhoons or hurricanes, are extremely powerful, destructive, intense circular storms that develop over warm tropical oceans. INSAT is one of the numerous geostationary satellites owned by India. INSAT stands for Indian National Satellite System, and ISRO launched this multipurpose Geostationary satellite to meet India's demands for search and rescue operations as well as telecommunications and broadcasting. Including brightness temperatures of several IR channels, temperature and humidity profiles, atmospheric stability indices and parameters, precipitable water, geo-potential height, and many other variables, the INSAT 3D satellite accurately records cyclones and their evolution. This study's objective is to assess the cyclone's intensity utilizing the generated sequence of images.

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IJARIIE Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. "Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 1 2023 Page 1695-1699
MLA Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. "Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning." International Journal Of Advance Research And Innovative Ideas In Education 9.1(2023) : 1695-1699.
APA Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, & Dr. Madhumala R B. (2023). Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning. International Journal Of Advance Research And Innovative Ideas In Education, 9(1), 1695-1699.
Chicago Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. "Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 1 (2023) : 1695-1699.
Oxford Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. 'Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 1, 2023, p. 1695-1699. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Cyclone_Intensity_Estimation_Using_INSAT_3D_IR_Imagery_and_deep_learning_ijariie19285.pdf (Accessed : 22 August 2025).
Harvard Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. (2023) 'Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning', International Journal Of Advance Research And Innovative Ideas In Education, 9(1), pp. 1695-1699IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Cyclone_Intensity_Estimation_Using_INSAT_3D_IR_Imagery_and_deep_learning_ijariie19285.pdf (Accessed : 22 August 2025)
IEEE Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B, "Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 1, pp. 1695-1699, Jan-Feb 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Cyclone_Intensity_Estimation_Using_INSAT_3D_IR_Imagery_and_deep_learning_ijariie19285.pdf [Accessed : 22 August 2025].
Turabian Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. "Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 1 (22 August 2025).
Vancouver Abhijna K C, B G Shreyas, Bhargavi, Dhanush Gowda S, and Dr. Madhumala R B. Cyclone Intensity Estimation Using INSAT-3D IR Imagery and deep learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : 22 August 2025]; 9(1) : 1695-1699. Available from: https://ijariie.com/AdminUploadPdf/Cyclone_Intensity_Estimation_Using_INSAT_3D_IR_Imagery_and_deep_learning_ijariie19285.pdf
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