Academic Journal
Kernel Density Estimation for Seismic Hazard Mapping in Indonesia: Influence of Kernel Function, Bandwidth Size, and Grid Resolution.
| Τίτλος: | Kernel Density Estimation for Seismic Hazard Mapping in Indonesia: Influence of Kernel Function, Bandwidth Size, and Grid Resolution. |
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| Συγγραφείς: | Fadli, Ari, Priyambodo, Tri Kuntoro, Putra, Agfianto Eko, Suryanto, Wiwit |
| Πηγή: | Trends in Sciences; Aug2025, Vol. 22 Issue 8, p1-30, 30p |
| Θεματικοί όροι: | Probability density function, Kernel functions, Extreme value theory, Spatial resolution, Bandwidths, Hazard mitigation |
| Περίληψη: | Identifying earthquake-prone areas is critical for disaster mitigation to reduce casualties and economic losses. This study applies Kernel Density Estimation (KDE) to analyze and rank earthquake-prone regions in the context of seismic hazard mapping, focusing on variations in kernel functions, bandwidth sizes, and grid resolutions. The Indonesian Earthquake Catalog (1964 - 2023) is used as a case study. The results indicate that different kernel functions have unique strengths. The Epanechnikov kernel provides an even density distribution, particularly in low and medium categories, while the Gaussian kernel captures high concentrations effectively, especially in high and extreme categories. The Biweight kernel performs well in medium and high categories but less effectively identifies extreme density concentrations. Grid resolution also significantly impacts results; smaller grids 0.25o×0.25o reveal detailed density patterns but may overemphasize localized concentrations, whereas larger grids 5o×5o are suited for macro-scale analyses but can obscure finer variations. Bandwidth size selection significantly affects density estimates. Smaller bandwidths (0.1) spread density widely, resulting in many grids in the low category but fewer in the medium, high, and extreme categories. Medium bandwidths (0.3) increase the proportion of medium and high categories, while larger bandwidths (0.5) produce the highest proportion of grids in the medium category, though extreme values remain limited. These variations demonstrate how bandwidth choices influence the balance between localized detail and broader distribution patterns. KDE effectively identifies earthquake-prone areas with varying densities and cluster significance, providing essential insights for disaster mitigation and spatial planning. The Gaussian kernel, 0.5 bandwidth, and 1o×1o grid combination yields the most significant results in mapping earthquake risk. However, the study has some limitations, including sensitivity to dataset completeness, parameter selection, and the smoothing effect of KDE that may underrepresent low-frequency events, particularly in sparse-data regions, which may introduce uncertainties in density estimations. Future studies could explore adaptive bandwidth selection and refined spatial resolution to enhance the robustness of KDE-based earthquake hazard mapping. [ABSTRACT FROM AUTHOR] |
| Copyright of Trends in Sciences is the property of Walailak Journal of Science & Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 187010703 RelevancyScore: 1007 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 1007.33666992188 |
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| Items | – Name: Title Label: Title Group: Ti Data: Kernel Density Estimation for Seismic Hazard Mapping in Indonesia: Influence of Kernel Function, Bandwidth Size, and Grid Resolution. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Fadli%2C+Ari%22">Fadli, Ari</searchLink><br /><searchLink fieldCode="AR" term="%22Priyambodo%2C+Tri+Kuntoro%22">Priyambodo, Tri Kuntoro</searchLink><br /><searchLink fieldCode="AR" term="%22Putra%2C+Agfianto+Eko%22">Putra, Agfianto Eko</searchLink><br /><searchLink fieldCode="AR" term="%22Suryanto%2C+Wiwit%22">Suryanto, Wiwit</searchLink> – Name: TitleSource Label: Source Group: Src Data: Trends in Sciences; Aug2025, Vol. 22 Issue 8, p1-30, 30p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Probability+density+function%22">Probability density function</searchLink><br /><searchLink fieldCode="DE" term="%22Kernel+functions%22">Kernel functions</searchLink><br /><searchLink fieldCode="DE" term="%22Extreme+value+theory%22">Extreme value theory</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+resolution%22">Spatial resolution</searchLink><br /><searchLink fieldCode="DE" term="%22Bandwidths%22">Bandwidths</searchLink><br /><searchLink fieldCode="DE" term="%22Hazard+mitigation%22">Hazard mitigation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Identifying earthquake-prone areas is critical for disaster mitigation to reduce casualties and economic losses. This study applies Kernel Density Estimation (KDE) to analyze and rank earthquake-prone regions in the context of seismic hazard mapping, focusing on variations in kernel functions, bandwidth sizes, and grid resolutions. The Indonesian Earthquake Catalog (1964 - 2023) is used as a case study. The results indicate that different kernel functions have unique strengths. The Epanechnikov kernel provides an even density distribution, particularly in low and medium categories, while the Gaussian kernel captures high concentrations effectively, especially in high and extreme categories. The Biweight kernel performs well in medium and high categories but less effectively identifies extreme density concentrations. Grid resolution also significantly impacts results; smaller grids 0.25o×0.25o reveal detailed density patterns but may overemphasize localized concentrations, whereas larger grids 5<superscript>o</superscript>×5<superscript>o</superscript> are suited for macro-scale analyses but can obscure finer variations. Bandwidth size selection significantly affects density estimates. Smaller bandwidths (0.1) spread density widely, resulting in many grids in the low category but fewer in the medium, high, and extreme categories. Medium bandwidths (0.3) increase the proportion of medium and high categories, while larger bandwidths (0.5) produce the highest proportion of grids in the medium category, though extreme values remain limited. These variations demonstrate how bandwidth choices influence the balance between localized detail and broader distribution patterns. KDE effectively identifies earthquake-prone areas with varying densities and cluster significance, providing essential insights for disaster mitigation and spatial planning. The Gaussian kernel, 0.5 bandwidth, and 1<superscript>o</superscript>×1<superscript>o</superscript> grid combination yields the most significant results in mapping earthquake risk. However, the study has some limitations, including sensitivity to dataset completeness, parameter selection, and the smoothing effect of KDE that may underrepresent low-frequency events, particularly in sparse-data regions, which may introduce uncertainties in density estimations. Future studies could explore adaptive bandwidth selection and refined spatial resolution to enhance the robustness of KDE-based earthquake hazard mapping. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Trends in Sciences is the property of Walailak Journal of Science & Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.48048/tis.2025.10064 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 1 Subjects: – SubjectFull: Probability density function Type: general – SubjectFull: Kernel functions Type: general – SubjectFull: Extreme value theory Type: general – SubjectFull: Spatial resolution Type: general – SubjectFull: Bandwidths Type: general – SubjectFull: Hazard mitigation Type: general Titles: – TitleFull: Kernel Density Estimation for Seismic Hazard Mapping in Indonesia: Influence of Kernel Function, Bandwidth Size, and Grid Resolution. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Fadli, Ari – PersonEntity: Name: NameFull: Priyambodo, Tri Kuntoro – PersonEntity: Name: NameFull: Putra, Agfianto Eko – PersonEntity: Name: NameFull: Suryanto, Wiwit IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 27740226 Numbering: – Type: volume Value: 22 – Type: issue Value: 8 Titles: – TitleFull: Trends in Sciences Type: main |
| ResultId | 1 |