Assessment of factors driving high fire severity potential and classification in a Mediterranean pine ecosystem.
Abstract Fire severity is an increasingly critical issue for forest managers for estimating fire impacts. Estimating high fire severity potential and accurate classification between fire severity levels are essential for integrated fire management planning in fire prone Mediterranean pine ecosystems...
| Publicado en: | Journal of Environmental Management Vol. 235; pp. 266 - 276 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Academic Press Inc.
Apr2019
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=134531659&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 134531659 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Apr2019 vid: 235 pid: 735 pub: Academic Press Inc. artinfo: ui: 134531659 10.1016/j.jenvman.2019.01.056 ppf: 266 ppct: 10 formats: tig: atl: Assessment of factors driving high fire severity potential and classification in a Mediterranean pine ecosystem. aug: au: Mitsopoulos, Ioannis Chrysafi, Irene Bountis, Diamantis Mallinis, Giorgos affil: Directorate of Biodiversity and Natural Environment Management, Ministry of Environment and Energy, Patision 147, 11251, Athens, Greece Department of Forestry and Natural Resources Management, Democritus University of Thrace, Pantazidou 193, 68 200, Orestiada, Greece su: Mediterranean Region Fire risk assessment Topography Fire management Classification algorithms sug: subj: Mediterranean Region Fire risk assessment Topography Fire management Classification algorithms keyword: Fire severity Mediterranean Pine forests Random forest algorithm Remote sensing Fire severity Mediterranean Pine forests Random forest algorithm Remote sensing ab: Abstract Fire severity is an increasingly critical issue for forest managers for estimating fire impacts. Estimating high fire severity potential and accurate classification between fire severity levels are essential for integrated fire management planning in fire prone Mediterranean pine ecosystems. This study attempts to determine the role of topography, pre-fire forest stand structure, fuel complex characteristics and fire behavior parameters on high fire severity potential and classification based on a large fire event occurred in Thasos, Greece. Within this framework, the Random Forest (RF) classification algorithm was used to model the relationship between a large set of predictors and fire severity as expressed by the differenced Normalized Burn Ratio (dNBR) spectral index, inferred from differenced pre- and post-fire Landsat 8 Operational Land Imager (OLI) at 30-m resolution. Results from the RF classifier algorithm showed that high fire severity potential and classification between fire severity levels mainly depended on topography variables and fuel complex characteristics. Assessing of factors which drive a fire to turn into high severe fire and classification into fire severity levels will substantially help land and forest managers to increase fire prevention and develop of concrete actions for successful post fire management at landscape level. Highlights • Fire severity is mainly depended on topography variables and fuel characteristics. • The models from the study will be valuable for understanding fire severity. • The spatial assessment of fire severity potential can help in fire management. • The models developed should be interpreted with care in other forest ecosystems. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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