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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 1298 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 1285 | - |
dc.citation.title | Korean Journal of Remote Sensing | - |
dc.citation.volume | 35 | - |
dc.contributor.author | Park, Sumin | - |
dc.contributor.author | Son, Bokyung | - |
dc.contributor.author | Im, Jungho | - |
dc.contributor.author | Lee, Jaese | - |
dc.contributor.author | Lee, Byungdoo | - |
dc.contributor.author | Kwon, ChunGeun | - |
dc.date.accessioned | 2023-12-21T18:13:50Z | - |
dc.date.available | 2023-12-21T18:13:50Z | - |
dc.date.created | 2020-01-03 | - |
dc.date.issued | 2019-12 | - |
dc.description.abstract | Drought is one of the factors that can cause wildfires. Drought is related to not only the occurrence of wildfires but also their frequency, extent and severity. In South Korea, most wildfires occur in dry seasons (i.e. spring and autumn), which are highly correlated to drought events. In this study, we examined the relationship between wildfire occurrence and drought factors, and developed satellite-based new drought indices for assessing wildfire risk over South Korea. Drought factors used in this study were high-resolution downscaled soil moisture, Normalized Different Water Index (NDWI), Normalized Multi-band Drought Index (NMDI), Normalized Different Drought Index (NDDI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI) and Vegetation Condition Index (VCI). Drought indices were then proposed through weighted linear combination and one-class support vector machine (One-class SVM) using the drought factors. We found that most drought factors, in particular, soil moisture, NDWI, and PCI were linked well to wildfire occurrence. The validation results using wildfire cases in 2018 showed that all five linear combinations produced consistently good performance (> 88% in occurrence match). In particular, the combination of soil moisture and NDWI, and the combination of soil moisture, NDWI, and precipitation were found to be appropriate for representing wildfire risk. | - |
dc.identifier.bibliographicCitation | Korean Journal of Remote Sensing, v.35, no.6, pp.1285 - 1298 | - |
dc.identifier.doi | 10.7780/kjrs.2019.35.6.3.11 | - |
dc.identifier.issn | 1225-6161 | - |
dc.identifier.scopusid | 2-s2.0-85119159903 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/30773 | - |
dc.language | 한국어 | - |
dc.publisher | 대한원격탐사학회 | - |
dc.title.alternative | Development of Satellite-based Drought Indices for Assessing Wildfire Risk | - |
dc.title | Development of Satellite-based Drought Indices for Assessing Wildfire Risk | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.identifier.kciid | ART002538074 | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.subject.keywordAuthor | Wildfire | - |
dc.subject.keywordAuthor | drought index | - |
dc.subject.keywordAuthor | soil moisture downscaling | - |
dc.subject.keywordAuthor | Random forest | - |
dc.subject.keywordAuthor | one-class SVM | - |
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