An alternative spectral index for rapid fire severity assessments

2012 ◽  
Vol 123 ◽  
pp. 72-80 ◽  
Author(s):  
S. Veraverbeke ◽  
S. Hook ◽  
G. Hulley
Keyword(s):  
Spectral Index ◽  
Fire Severity

scholarly journals Evaluating the Near and Mid Infrared Bi-Spectral Space for Assessing Fire Severity and Comparison with the Differenced Normalized Burn Ratio

2021 ◽  
Vol 13 (4) ◽  
pp. 695
Author(s):  
Max J. van Gerrevink ◽  
Sander Veraverbeke
Keyword(s):  
Spectral Index ◽  
Field Data ◽  
Vegetation Index ◽  
Fire Regime ◽  
Fire Severity ◽  
Spectral Space ◽  
Mid Infrared ◽  
Fire Emissions ◽  
Differenced Normalized Burn Ratio ◽  
Normalized Burn Ratio

Fire severity, defined as the degree of environmental change caused by a fire, is a critical fire regime attribute of interest to fire emissions modelling and post-fire rehabilitation planning. Remotely sensed fire severity is traditionally assessed by the differenced normalized burn ratio (dNBR). This spectral index captures fire-induced reflectance changes in the near infrared (NIR) and short-wave infrared (SWIR) spectral regions. This study evaluates a spectral index based on a band combination including the NIR and mid infrared (MIR) spectral regions, the differenced normalized difference vegetation index with mid infrared (dNDVIMID), to assess fire severity. This evaluation capitalized upon the unique opportunity stemming from the pre- and post-fire airborne acquisitions over the Rim (2013) and King (2014) fires in California with the MODIS/ASTER Airborne Simulator (MASTER) instrument. The field data consist of 85 Geometrically structured Composite Burn Index (GeoCBI) plots. In addition, six different index combinations, respectively three with a NIR–SWIR combination and three with a NIR–MIR combination, were evaluated based on the optimality of fire-induced spectral displacements. The optimality statistic ranges between zero and one, with values of one representing pixel displacements that are unaffected by noise. The results show that the dNBR demonstrated a stronger relationship with GeoCBI field data when field measurements over the two fire scars were combined than the dNDVIMID approaches. The results yielded an R2 of 0.68 based on a saturated growth model for the best performing dNBR index, whereas the performance of the dNDVIMID indices was lower with an R2 = 0.61 for the best performing dNDVIMID index. The dNBR also outperformed the dNDVIMID in terms of spectral optimality across both fires. The best performing dNBR index yielded median optimality statistics of 0.56 over the Rim and 0.60 over the King fire. The best performing dNDVIMID index recorded optimality values of 0.49 over the Rim and 0.46 over the King fire. We also found that the dNBR approach led to considerable differences in the form of the relationship with the GeoCBI between the two fires, whereas the dNDVIMID approach yielded comparable relationships with the GeoCBI over the two fires. This suggests that the dNDVIMID approach, despite its slightly lower performance than the dNBR, may be a more robust method for estimating and comparing fire severity over large regions. This premise needs additional verification when more air- or spaceborne imagery with NIR and MIR bands will become available with a spatial resolution that allows ground truthing of fire severity.

scholarly journals Evaluating the Hyperspectral Sensitivity of the Differenced Normalized Burn Ratio for Assessing Fire Severity

2021 ◽  
Vol 13 (22) ◽  
pp. 4611
Author(s):  
Max J. van Gerrevink ◽  
Sander Veraverbeke
Keyword(s):  
Spectral Index ◽  
Field Data ◽  
Near Infrared ◽  
Environmental Changes ◽  
Fire Severity ◽  
Hyperspectral Data ◽  
Landsat 8 ◽  
Fire Emissions ◽  
Differenced Normalized Burn Ratio ◽  
Normalized Burn Ratio

Fire severity represents fire-induced environmental changes and is an important variable for modeling fire emissions and planning post-fire rehabilitation. Remotely sensed fire severity is traditionally evaluated using the differenced normalized burn ratio (dNBR) derived from multispectral imagery. This spectral index is based on bi-temporal differenced reflectance changes caused by fires in the near-infrared (NIR) and short-wave infrared (SWIR) spectral regions. Our study aims to evaluate the spectral sensitivity of the dNBR using hyperspectral imagery by identifying the optimal bi-spectral NIR SWIR combination. This assessment made use of a rare opportunity arising from the pre- and post-fire airborne image acquisitions over the 2013 Rim and 2014 King fires in California with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. The 224 contiguous bands of this sensor allow for 5760 unique combinations of the dNBR at a high spatial resolution of approximately 15 m. The performance of the hyperspectral dNBR was assessed by comparison against field data and the spectral optimality statistic. The field data is composed of 83 in situ measurements of fire severity using the Geometrically structured Composite Burn Index (GeoCBI) protocol. The optimality statistic ranges between zero and one, with one denoting an optimal measurement of the fire-induced spectral change. We also combined the field and optimality assessments into a combined score. The hyperspectral dNBR combinations demonstrated strong relationships with GeoCBI field data. The best performance of the dNBR combination was derived from bands 63, centered at 0.962 µm, and 218, centered at 2.382 µm. This bi-spectral combination yielded a strong relationship with GeoCBI field data of R2 = 0.70 based on a saturated growth model and a median spectral index optimality statistic of 0.31. Our hyperspectral sensitivity analysis revealed optimal NIR and SWIR bands for the composition of the dNBR that are outside the ranges of the NIR and SWIR bands of the Landsat 8 and Sentinel-2 sensors. With the launch of the Precursore Iperspettrale Della Missione Applicativa (PRISMA) in 2019 and several planned spaceborne hyperspectral missions, such as the Environmental Mapping and Analysis Program (EnMAP) and Surface Biology and Geology (SBG), our study provides a timely assessment of the potential and sensitivity of hyperspectral data for assessing fire severity.

Evaluating the near and mid infrared bi-spectral space for assessing fire severity and comparison with the differenced normalized burn ratio

2021 ◽  
Author(s):  
Max van Gerrevink ◽  
Sander Veraverbeke
Keyword(s):  
Spectral Index ◽  
Field Data ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Fire Regime ◽  
Fire Severity ◽  
Spectral Space ◽  
Mid Infrared ◽  
Fire Emissions

<p>Fire severity, defined as the degree of environmental change caused by a fire, is a critical fire regime attribute of interest to fire emissions modelling and post-fire rehabilitation planning. Remotely sensed fire severity is traditionally assessed by the differenced normalized burned ratio (dNBR). This spectral index captures fire-induced reflectance changes in the near infrared (NIR) and short-wave infrared (SWIR) spectral regions. This study evaluates a spectral index based on a band combination including the NIR and mid infrared (MIR) spectral regions, the differenced normalized difference vegetation index (dNDVI<sub>MID</sub>), to assess fire severity. This evaluation capitalized upon the unique opportunity stemming from the pre- and post-fire airborne acquisitions over the Rim (2013) and King (2014) fires in California with the MODIS/ASTER (MASTER) instrument. The field data consists of 85 Geometrically structured Composite Burn Index (GeoCBI) plots. In addition, six different index combinations, respectively three with a NIR-SWIR combination and three with a NIR-MIR combination, were evaluated based on the optimality of fire-induced spectral displacements. The optimality statistic ranges between zero and one, with values of one representing pixel displacements that are unaffected by noise. Results show that the dNBR demonstrated a stronger relationship with GeoCBI field data when field measurements over the two fire scars were combined than the dNDVI<sub>MID</sub> approaches. The results yielded an R<sup>2</sup> of 0.68 based on a saturated growth model for the best performing dNBR index, whereas the performance of the dNDVI<sub>MID </sub>indices was clearly lower with an R<sup>2</sup> = 0.61 for the best performing dNDVI<sub>MID </sub>index. The dNBR also outperformed the dNDVI<sub>MID</sub> in terms of spectral optimality across both fires. The best performing dNBR index yielded the optimality statistics of 0.56 over the Rim and 0.60 over the King fire. The best performing dNDVI<sub>MID, </sub>index recorded optimality values of 0.49 over the Rim and 0.46 over the King fire. We also found that the dNBR approach led to considerable differences in the form of the relationship with the GeoCBI between the two fires, whereas the dNDVI<sub>MID</sub> approach yielded comparable relationships with the GeoCBI over the two fires. This suggests that the dNDVI<sub>MID</sub> approach, despite its slightly lower performance than the dNBR, may be a more robust method for estimating and comparing fire severity over large regions. This premise needs additional verification when more air- or spaceborne imagery with NIR and MIR bands will become available with a spatial resolution that allows ground truthing of fire severity. </p>

Analysis of the spectral index method for vector modes of rib waveguides

1990 ◽  
Vol 137 (1) ◽  
pp. 21 ◽  
Author(s):  
M.S. Stern ◽  
P.C. Kendall ◽  
P.W.A. McLlroy
Keyword(s):  
Spectral Index ◽  
Index Method ◽  
Rib Waveguides

Spectral index method for rib waveguide analysis

1989 ◽  
Vol 25 (2) ◽  
pp. 107 ◽  
Author(s):  
P.C. Kendall ◽  
P.W.A. Mcllroy ◽  
M.S. Stern
Keyword(s):  
Spectral Index ◽  
Index Method ◽  
Rib Waveguide

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Spectral index-flux relation for investigating the origins of steep decay in γ-ray bursts

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Samuele Ronchini ◽  
Gor Oganesyan ◽  
Marica Branchesi ◽  
Stefano Ascenzi ◽  
Maria Grazia Bernardini ◽  
...  
Keyword(s):  
Spectral Index ◽  
Proton Synchrotron ◽  
Relativistic Jets ◽  
Time Resolved ◽  
X Ray ◽  
Compact Binary ◽  
Internal Dissipation ◽  
Adiabatic Cooling ◽  
Alternative Scenarios ◽  
Steep Decay

Abstractγ-ray bursts (GRBs) are short-lived transients releasing a large amount of energy (1051 − 1053 erg) in the keV-MeV energy range. GRBs are thought to originate from internal dissipation of the energy carried by ultra-relativistic jets launched by the remnant of a massive star’s death or a compact binary coalescence. While thousands of GRBs have been observed over the last thirty years, we still have an incomplete understanding of where and how the radiation is generated in the jet. Here we show a relation between the spectral index and the flux found by investigating the X-ray tails of bright GRB pulses via time-resolved spectral analysis. This relation is incompatible with the long standing scenario which invokes the delayed arrival of photons from high-latitude parts of the jet. While the alternative scenarios cannot be firmly excluded, the adiabatic cooling of the emitting particles is the most plausible explanation for the discovered relation, suggesting a proton-synchrotron origin of the GRB emission.

scholarly journals Effects of Soil Abiotic and Biotic Factors on Tree Seedling Regeneration Following a Boreal Forest Wildfire

Ecosystems ◽  
2021 ◽  
Author(s):  
Theresa S. Ibáñez ◽  
David A. Wardle ◽  
Michael J. Gundale ◽  
Marie-Charlotte Nilsson
Keyword(s):  
Boreal Forest ◽  
Betula Pendula ◽  
Fire Severity ◽  
Tree Regeneration ◽  
Soil Biota ◽  
Fire Disturbance ◽  
Burn Severity ◽  
Soil Conditions ◽  
Tree Seedling ◽  
Seedling Regeneration

AbstractWildfire disturbance is important for tree regeneration in boreal ecosystems. A considerable amount of literature has been published on how wildfires affect boreal forest regeneration. However, we lack understanding about how soil-mediated effects of fire disturbance on seedlings occur via soil abiotic properties versus soil biota. We collected soil from stands with three different severities of burning (high, low and unburned) and conducted two greenhouse experiments to explore how seedlings of tree species (Betula pendula, Pinus sylvestris and Picea abies) performed in live soils and in sterilized soil inoculated by live soil from each of the three burning severities. Seedlings grown in live soil grew best in unburned soil. When sterilized soils were reinoculated with live soil, seedlings of P. abies and P. sylvestris grew better in soil from low burn severity stands than soil from either high severity or unburned stands, demonstrating that fire disturbance may favor post-fire regeneration of conifers in part due to the presence of soil biota that persists when fire severity is low or recovers quickly post-fire. Betula pendula did not respond to soil biota and was instead driven by changes in abiotic soil properties following fire. Our study provides strong evidence that high fire severity creates soil conditions that are adverse for seedling regeneration, but that low burn severity promotes soil biota that stimulates growth and potential regeneration of conifers. It also shows that species-specific responses to abiotic and biotic soil characteristics are altered by variation in fire severity. This has important implications for tree regeneration because it points to the role of plant–soil–microbial feedbacks in promoting successful establishment, and potentially successional trajectories and species dominance in boreal forests in the future as fire regimes become increasingly severe through climate change.

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