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Wildfire Risk Map Based on DBSCAN Clustering and Cluster Density Evaluation

Muchamad Taufiq, Anwar and Edy, Winarno and Wiwien, Hadikurniawati and Aji, Supriyanto Wildfire Risk Map Based on DBSCAN Clustering and Cluster Density Evaluation. Advance Sustainable Science, Engineering and Technology.

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Abstract

Wildfire risk analysis can be based on historical data of fire hotspot occurrence. Traditional wildfire risk analyses often rely on the use of administrative or grid polygons which has their own limitations. This research aims to develop a wildfire risk map by implementing DBSCAN clustering method to identify areas with wildfire risk based on historical data of wildfire hotspot occurrence points. The risk ranks for each area/cluster were then rankedlcalculated based on the cluster density. The result showed that this method is capable of detecting major clusters/areas with their respective wildfire risk and that the majority of consequent fire occurrences were repeated inside the identified clusters/areas.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty / Institution: Fakultas Teknologi Informasi
Depositing User: Fakultas Ekonomi
Date Deposited: 07 Oct 2022 03:34
Last Modified: 07 Oct 2022 03:34
URI: https://eprints.unisbank.ac.id/id/eprint/8811

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