Analyzing Lightning Strike Susceptibility Using the Elliptical Fitting Method with a Principal Component Analysis Approach
Abstract
Lightning is a high-current discharge that occurs in Cumulonimbus clouds, with CG (Cloud to Ground)
lightning strikes posing significant dangers, especially to human life. Pasuruan, located in the highlands
between mountains and the ocean in Indonesia, is particularly vulnerable to such strikes. This study
aims to mitigate the impact of lightning strikes, particularly in industrial areas like Pasuruan, by delineating lightning-prone areas using a sophisticated methodological approach. Our research employs a
robust Ellipse Fitting Method, parameterized with Principal Component Analysis (PCA), to accurately
define the boundaries of these high-risk zones. The Ellipse Fitting Method, which involves forming
an ellipse from the intersection of a plane and a cone, uses five key parameters: a center point, two
vertex points, and two focus points. PCA is then applied to these parameters to determine the ellipse’s
configuration, with the center point derived from the mean of all data points. The major and minor
axes are defined by the first and second eigenvalues of the principal components, respectively. The size
of the ellipse correlates with the confidence level, with higher confidence resulting in a larger ellipse.
The result of integrating these advanced techniques is the generation of two PCA models from data
collected across 28 sub-districts in Pasuruan, with findings indicating a high level of vulnerability in
Lumbang District and a moderate level of risk in Gempol District. This methodological framework not
only enhances the precision in identifying lightning-prone areas but also provides a scalable approach
for similar studies in other regions. Suggestion for the further research are to overcome extreme points
or extreme points in the PCA confidence ellipse such as MVEE.
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