2021
DOI: 10.52939/ijg.v17i6.2061
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The Comparison of Spatial Models in Peak Ground Acceleration (PGA) Study

Abstract: This study was conducted to compare the performance of three different spatial analysis models: Inverse Distance Weighted (IDW), Ordinary Kriging,­­ and Regularized Spline interpolation technique to determine the best fit model representing Peak Ground Acceleration (PGA) in West Java Province, Indonesia. The three models are commonly used in spatial visualization, but have different calculation methods. The calculations were performed using available formulas while the spatial modeling was conducted using the … Show more

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Cited by 3 publications
(2 citation statements)
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“…The earthquake hazard zoning map variable uses the following indicators: administrative boundaries, Lembang fault, land use, rock types, soil types, earthquake intensity, earthquake acceleration, slope and population density. Earthquake hazard mapping using the AHP method is largely determined by the weighting classification of each indicator (Ihsan et al 2021 ; Serlia, Cahyono & Handayani 2021 ). The weighting classification consists of Peak Ground Acceleration (PGA) data which are the cause of damage to the surface in the area identified as earthquake-affected based on the Center for Volcanology and Geological Hazard Mitigation, Indonesia.…”
Section: Methodsmentioning
confidence: 99%
“…The earthquake hazard zoning map variable uses the following indicators: administrative boundaries, Lembang fault, land use, rock types, soil types, earthquake intensity, earthquake acceleration, slope and population density. Earthquake hazard mapping using the AHP method is largely determined by the weighting classification of each indicator (Ihsan et al 2021 ; Serlia, Cahyono & Handayani 2021 ). The weighting classification consists of Peak Ground Acceleration (PGA) data which are the cause of damage to the surface in the area identified as earthquake-affected based on the Center for Volcanology and Geological Hazard Mitigation, Indonesia.…”
Section: Methodsmentioning
confidence: 99%
“…IDW is one of the spatial approaches to describe the rainfall distribution that usually possesses a good accuracy, yet, the results depend on the quality of the rain data and posts (Chen & Liu, 2012). IDW is a spatial approach with a high correlation compared to other spatial algorithms (Ihsan et al, 2021). The rainfall used had four rain posts ranging from 2004 to 2021.…”
Section: Rainfallmentioning
confidence: 99%