Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests
18 Pág.
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| Language: | English |
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Elsevier
2015-12-01
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| Subjects: | Change detection, Fire severity, L-band SAR, Radar Burn Ratio, |
| Online Access: | http://hdl.handle.net/10261/344258 http://dx.doi.org/10.13039/501100001782 https://api.elsevier.com/content/abstract/scopus_id/84941279987 |
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dig-inia-es-10261-3442582024-05-16T20:57:55Z Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests Tanase, Mihai A. Kennedy, Robert E. Aponte, Cristina University of Melbourne Japan Aerospace Exploration Agency Tanase, Mihai A. [0000-0002-0045-2299] Kennedy, Robert E. [0000-0002-5507-474X] Aponte, Cristina [0000-0002-8457-7573] Change detection Fire severity L-band SAR Radar Burn Ratio 18 Pág. Fires affect wide areas and their effects can be successfully estimated from a range of remote sensing sensors, with synthetic aperture radars (SAR) being of particular interest due to their sensitivity to forest vertical structure, global availability and independence of cloud cover or solar elevation. Previous studies have demonstrated the sensitivity to fire effects of L-band SAR sensors using post-fire datasets and empirical modeling. This study proposed an innovative method for estimating fire severity by combining pre- and post-fire SAR datasets within a change detection framework to compute a novel index, the Radar Burn Ratio (RBR). More importantly, a standardized RBR was developed and tested over seven temperate forest types located on three continents with above ground biomass values ranging from 30 to over 500tha-1. RBR standardization allowed for common thresholds to be defined and subsequently used for estimating the Composite Burn Index (CBI, a measure of fire impact) without the need for a priori information (i.e., in situ data) on local post-fire conditions. The estimation accuracy of the standardized RBR was compared to locally-calibrated empirical models based on field CBI data. The results showed similar estimation errors and a strong agreement with the reference in situ data (i.e., Cohen's weighted kappa >0.61). The RBR index most sensitive to fire severity was based on the cross-polarized channel applied under dry environmental conditions. Under wet conditions the estimation accuracy was considerably lower. The methods proposed in this study are particularly valuable for rapid fire severity assessments at regional to global scales, requiring only that RBR thresholds be calibrated for a range of environments and that CBI scores be related to fuel consumption for each forest type. This work was funded by an Early Career Research Grant (ECR 602155) from the University of Melbourne. ALOS PALSAR data were provided by the Japanese Space Agency (JAXA) within the 4th ALOS Research Announcement (PI 1091). The authors would like to acknowledge Dr. R. Benyon for helpful discussions on fire effects at Kinglake fire and Nicholas Bauer and Peter Baker for providing photographs for the Kinglake fire. The anonymous reviewer and the Associated Editor are also acknowledged for their valuable suggestions. Peer reviewed 2024-01-29T15:17:31Z 2024-01-29T15:17:31Z 2015-12-01 artículo http://purl.org/coar/resource_type/c_6501 Remote Sensing of Environment 170: 14-31 (2015) 0034-4257 http://hdl.handle.net/10261/344258 10.1016/j.rse.2015.08.025 http://dx.doi.org/10.13039/501100001782 2-s2.0-84941279987 https://api.elsevier.com/content/abstract/scopus_id/84941279987 en Departamento de Medio Ambiente y Agronomía Preprint https://doi.org/10.1016/j.rse.2015.08.025 Sí open application/pdf Elsevier |
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Change detection Fire severity L-band SAR Radar Burn Ratio Change detection Fire severity L-band SAR Radar Burn Ratio |
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Change detection Fire severity L-band SAR Radar Burn Ratio Change detection Fire severity L-band SAR Radar Burn Ratio Tanase, Mihai A. Kennedy, Robert E. Aponte, Cristina Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| description |
18 Pág. |
| author2 |
University of Melbourne |
| author_facet |
University of Melbourne Tanase, Mihai A. Kennedy, Robert E. Aponte, Cristina |
| format |
artículo |
| topic_facet |
Change detection Fire severity L-band SAR Radar Burn Ratio |
| author |
Tanase, Mihai A. Kennedy, Robert E. Aponte, Cristina |
| author_sort |
Tanase, Mihai A. |
| title |
Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| title_short |
Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| title_full |
Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| title_fullStr |
Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| title_full_unstemmed |
Radar Burn Ratio for fire severity estimation at canopy level: An example for temperate forests |
| title_sort |
radar burn ratio for fire severity estimation at canopy level: an example for temperate forests |
| publisher |
Elsevier |
| publishDate |
2015-12-01 |
| url |
http://hdl.handle.net/10261/344258 http://dx.doi.org/10.13039/501100001782 https://api.elsevier.com/content/abstract/scopus_id/84941279987 |
| work_keys_str_mv |
AT tanasemihaia radarburnratioforfireseverityestimationatcanopylevelanexamplefortemperateforests AT kennedyroberte radarburnratioforfireseverityestimationatcanopylevelanexamplefortemperateforests AT apontecristina radarburnratioforfireseverityestimationatcanopylevelanexamplefortemperateforests |
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