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| Titel |
Assessing the temporal sensitivity of the differenced Normalized Burn Ratio (dNBR) to estimate burn severity using MODIS time series |
| VerfasserIn |
Sander Veraverbeke, Stefaan Lhermitte, Willem Verstraeten, Rudi Goossens |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250031816
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| Zusammenfassung |
| The temporal sensitivity of the differenced Normalized Burn Ratio (dNBR) to assess burn
severity was evaluated for the case of the 2007 Peloponnese (Greece) wildfires. Prior to the
analysis, a pixel-based control plot selection procedure was initiated for each burned pixel
based on time series similarity of the pre-fire year 2006. Post-fire near infrared (NIR)
dramatically dropped immediately post-fire, while the highest MIR reflectance values were
reached three weeks after the fire. Both NIR and MIR reflectance showed an increased
variability during the wet Mediterranean winter. Due to the process of early vegetation
recovery, the burned pixels’ NIR reflectance approached the control pixels’ values during the
productive spring-time. Because of the three weeks post-fire delay in MIR reflectance
increase, the NBR drop and dNBR peak were obtained synchronously. Both the standard
deviation of the NBR and dNBR were high during winter, as a consequence of the
simultaneous increase in NIR and MIR reflectance variability. In spite of the high variation in
dNBR during winter, this moment is suboptimal to estimate burn severity due to
low rates of image availability and low optimality values. Index performance was
clearly lower during winter and spring because vegetation regeneration clearly
diminishes the distance in the bi-spectral feature space to which the dNBR is sensitive
at the favor of displacements to which the index is insensitive. In contrast, NIR
reflectance, MIR reflectance, NBR, dNBR and dNBR optimality changes achieved a
maximum three weeks post. Consequently this was the optimal time to estimate burn
severity in our case study retaining a maximal degree of information with a high
reliability. Conclusions should be verified for other fires and in other ecoregions. |
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