Field estimation of ash and char colour-lightness using a standard grey scale
David P. Roy A E , Luigi Boschetti B , Stefan W. Maier C and Alistair M. S. Smith D
A Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, USA.
B Department of Geography, University of Maryland, College Park, MD 20740, USA.
C School of Environmental and Life Sciences, Charles Darwin University, Darwin, NT 0909, Australia.
D Department of Forest Resources, University of Idaho, ID 83844, USA.
E Corresponding author. Email: firstname.lastname@example.org
International Journal of Wildland Fire 19(6) 698-704 http://dx.doi.org/10.1071/WF09133
Submitted: 18 November 2009 Accepted: 17 April 2010 Published: 17 September 2010
Vegetation fires produce biomass combustion residues, with colour varying from dark black char to white mineral ash. The colour-lightness of char and ash combustion residues is a qualitative parameter describing the post-fire condition of burned areas, and has been correlated with the completeness of combustion, fire intensity, and fire duration. Researchers have suggested that visual comparison of combustion residue samples with a standard grey scale would enable reliable combustion residue colour-lightness estimation. This paper describes an experiment aimed at assessing if colour-lightness can be estimated using a standard grey scale. Fifteen combustion residue samples with colour-lightness ranging from black char to white mineral ash were collected in the Northern Territory, Australia, and visually evaluated by three individuals using a grey scale. The grey-scale scores (0–19) were compared with the mean visible (390 to 830 nm) wavelength combustion residue reflectance (0–1) measured with a portable spectroradiometer. A significant linear relationship between the grey-scale scores and the mean visible combustion residue reflectance was found (R2 = 0.816 with a linear fit, R2 = 0.936 with a logarithmic-transformed fit). This finding suggests that combustion residue colour-lightness can be assessed in the field using inexpensive grey scales, and that this technique is a suitable avenue for future research on the field assessment of fire characteristics and effects.
Analytical Spectral Devices (2002) ‘FieldSpec Pro – User’s Guide.’ (Analytical Spectral Devices: Boulder, CO)
Byram GM (1959) Combustion of forest fuels. In ‘Forest Fire: Control and Use’. (Ed. KP Davis) pp. 61–89. (McGraw Hill: New York)
Edwards ARussell-Smith J2009Ecological thresholds and the status of fire-sensitive vegetation in western Arnhem Land, northern Australia: implications for management.International Journal of Wildland Fire182127146doi:10.1071/WF08008
Eismann K, Duggan S (2008) ‘The Creative Digital Darkroom.’ (O’Reilly Media: Sebastopol, CA)
Key CH2006Ecological and sampling constraints on defining landscape fire severity.Fire Ecology223459doi:10.4996/FIREECOLOGY.0202034
Landmann T2003Characterizing sub-pixel Landsat ETM+ fire severity on experimental fires in the Kruger National Park, South Africa.South African Journal of Science99357360
Lentile LBHolden ZSmith AMSFalkowski MJHudak ATMorgan PLewis SAGessler PEBenson NC2006Remote sensing techniques to assess active fire and post-fire effects.International Journal of Wildland Fire153319345doi:10.1071/WF05097
Lentile LBSmith AMSHudak ATMorgan PBobbitt M2009Remote sensing for prediction of 1-year post-fire ecosystem condition.International Journal of Wildland Fire18594608doi:10.1071/WF07091
Lobell DBAsner GP2002Moisture effects on soil reflectance.Soil Science Society of America Journal66722727
McNaughton SJStronach NRHGeorgiadis NJ1998Combustion in natural fires and global emissions budgets.Ecological Applications82464468doi:10.1890/1051-0761(1998)008[0464:CINFAG]2.0.CO;2
Pereira JMC2003Remote sensing of burned areas in tropical savannas.International Journal of Wildland Fire12259270doi:10.1071/WF03028
Pereira JMCBernardo MPrivette JLCaylor KKSilva JMNSá ACLNi-Meister W2004A simulation analysis of the detectability of understory burns in Miombo woodlands.Remote Sensing of Environment93296310doi:10.1016/J.RSE.2004.01.009
Roy DPLandmann T2005Characterizing the surface heterogeneity of fire effects using multitemporal reflective wavelength data.International Journal of Remote Sensing2641974218doi:10.1080/01431160500112783
Roy DPBoschetti LJustice COJu J2008The Collection 5 MODIS Burned Area Product – global evaluation by comparison with the MODIS Active Fire Product.Remote Sensing of Environment11236903707doi:10.1016/J.RSE.2008.05.013
Russell-Smith JMurphy BPMeyer MCook GDMaier SEdwards ACSchatz JBrocklehurst P2009Improving estimates of savanna burning emissions for greenhouse accounting in northern Australia: limitations, challenges, applications.International Journal of Wildland Fire18118doi:10.1071/WF08009
Sanches IDTuohy MPHedley MJBretherton MR2009Large, durable and low-cost reflectance standard for field remote sensing applications.International Journal of Remote Sensing3023092319doi:10.1080/01431160802549377
Scholes RJKendall JJustice CO1996The quantity of biomass burned in southern Africa.Journal of Geophysical Research10123 66723 676doi:10.1029/96JD01623
Sharpe LTStockman AJagla WJägle H2005A luminous efficiency function, V*(λ), for daylight adaptation.Journal of Vision53948968
Shea RWShea BWKauffman JBWard DEHaskins CIScholes M1996Fuel biomass and combustion factors associated with fires in savanna ecosystems of South Africa and Zambia.Journal of Geophysical Research10123 55123 568doi:10.1029/95JD02047
Smith AMSHudak AT2005Estimating combustion of large downed woody debris from residual white ash.International Journal of Wildland Fire14245248doi:10.1071/WF05011
Smith AMSWooster MJDrake NADipotso FMFalkowski MJHudak AT2005Testing the potential of multispectral remote sensing for retrospectively estimating fire severity in African savannahs.Remote Sensing of Environment97192115doi:10.1016/J.RSE.2005.04.014
Smith AMSLentile LBHudak ATMorgan P2007Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a North American ponderosa pine forest.International Journal of Remote Sensing282251595166doi:10.1080/01431160701395161
Souza CMRoberts DACochrane MA2005Combining spectral and spatial information to map canopy damage from selective logging and forest fires.Remote Sensing of Environment98329343doi:10.1016/J.RSE.2005.07.013
Stronach NRHMcNaughton SJ1989Grassland fire dynamics in the Serengeti ecosystem, and a potential method of retrospective estimating fire energy.Journal of Applied Ecology2610251033doi:10.2307/2403709
Trigg SNFlasse SP2000Characterizing the spectral–temporal response of burned savannah using in situ spectroradiometry and infrared thermometry.International Journal of Remote Sensing2131613168doi:10.1080/01431160050145045
Trollope WSWTainton NM1986Effect of fire intensity on the grass and bush components of the Eastern Cape Thornveld.African Journal of Range and Forage Science323742
Williams RJGill AMMoore PHR1998Seasonal changes in fire behaviour in a tropical savanna in northern Australia.International Journal of Wildland Fire84227239doi:10.1071/WF9980227
Wooster MJRoberts GPerry GLWKaufman YJ2005Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release.Journal of Geophysical Research110D24311doi:10.1029/2005JD006318
Yates CPEdwards ACRussell-Smith J2008Big fires and their ecological impacts in Australian savannas: size and frequency matters.International Journal of Wildland Fire17768781doi:10.1071/WF07150