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Analyzing windstorm pattern in Malaysia based on extracted Twitter data.

Isa, N.A.; Salleh, S.A.; Chan, A.; Zakaria, N.H.; Suif, Z.; Abdul Halim, M.

Authors

N.A. Isa

S.A. Salleh

N.H. Zakaria

Z. Suif

M. Abdul Halim



Abstract

Wind-rain interactions often lead to severe windstorm events and consequently cause damages and fatal destructions. The increase in frequency of recent windstorm events overwhelmed the nation. Thus, efforts in obtaining and recording these events are intensified with the help of current technology. This study aims to analyze the pattern of recent windstorm events by utilizing big data and GIS. In this study, the reported windstorm events in Twitter application were extracted using R-programming. Prior to analyses, the extracted data were screened to remove any outliers found. The extracted data were selected based on the credibility of its sources to ensure the accuracy and quality. These selected data were extracted from trusted users such as Meteorological Department of Malaysia (MMD), Berita Harian, Bernama and others. This study has demonstrated the possibility of Twitter data as an alternative data source in windstorm studies based on its reasonable findings. It is exhibited that there is drastic increased of windstorm events frequency in years 2018-2020, especially in the northern and west-coast regions of Peninsular. The highest frequency was recorded in April (inter-monsoon season) while the lowest is in February and December (northeast monsoon). The increase of frequency in several locations in the Peninsular is very alarming especially in the Klang Valley since this region is highly populated and serves as Malaysia's important economic zones. Hence, risk control should be considered in this region to reduce the negative impacts as suggested in SDG11 and SDG13.

Citation

ISA, N.A., SALLEH, S.A., CHAN, A., ZAKARIA, N.H., SUIF, Z. and HALIM, M.A. 2022. Analyzing windstorm pattern in Malaysia based on extracted Twitter data. IOP conference series: earth and environmental science [online], 1019: Proceedings of the 1st International conference on biodiversity and sustainable development 2021 (iBioSDG 2021), 23 November 2021, [virtual event], article number 012011. Available from: https://doi.org/10.1088/1755-1315/1019/1/012011

Journal Article Type Conference Paper
Conference Name 1st International conference on biodiversity and sustainable development 2021 (iBioSDG 2021)
Conference Location [virtual event]
Acceptance Date Apr 5, 2022
Online Publication Date May 11, 2022
Publication Date May 11, 2022
Deposit Date Feb 20, 2024
Publicly Available Date Feb 20, 2024
Journal IOP conference series: earth and environmental science
Print ISSN 1755-1307
Electronic ISSN 1755-1315
Publisher IOP Publishing
Peer Reviewed Peer Reviewed
Volume 1019
Article Number 012011
DOI https://doi.org/10.1088/1755-1315/1019/1/012011
Keywords Windstorm; Big data; GIS; R-programming; SDG11; SDG13
Public URL https://rgu-repository.worktribe.com/output/2055069