Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness and carbon emissions
Sander Veraverbeke A B and Simon J. Hook A
+ Author Affiliations
- Author Affiliations
A Jet Propulsion Laboratory (NASA), California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA.
B Corresponding author. Email: sander.s.veraverbeke@jpl.nasa.gov
International Journal of Wildland Fire 22(5) 707-720 https://doi.org/10.1071/WF12168
Submitted: 6 October 2012 Accepted: 16 December 2012 Published: 18 March 2013
Abstract
We used a Landsat Thematic Mapper (TM) image from the 2011 Wallow fire in Arizona, USA, in combination with field data to assess different methods for determining fire severity. These include the normalised burn ratio (NBR), the differenced NBR (dNBR), the relative dNBR (RdNBR) and the burned fraction (BF) estimated by spectral mixture analysis (SMA). The Geo Composite Burn Index (GeoCBI) and vegetation mortality data were used as ground truth. Of all the remotely sensed measures evaluated the dNBR had the best performance (GeoCBI–dNBR R2 = 0.84), which supports the operational use of the dNBR for post-fire management. Of the other remotely sensed measures, the SMA-derived BF also had moderately high correlations with the GeoCBI (R2 = 0.66). Both approaches demonstrated their usefulness for refining modelled CC values, however, the SMA approach has the advantage of providing transferable quantitative estimates without the need for calibration with field data. The carbon emission estimates that included fire severity were more than 50% lower than the estimate derived from modelling alone. These results suggest that for certain fire types, especially mixed-severity fires, current emission estimates are significantly overestimated, which will affect global carbon emission estimates from wildfires.
Additional keywords: burn severity, burning efficiency, carbon cycle, normalised burn ratio (NBR), wildfire emission.
References
Adams J, Smith M, Johnson P (1986) Spectral mixture modelling: a new analysis of rock and soil types at Viking Lander. Journal of Geophysical Research 91, 8113–8125.Ahern F, Erdle T, Maclean D, Kneppeck I (1991) A quantitative relationship between forest growth rates and Thematic Mapper reflectance measurements. International Journal of Remote Sensing 12, 387–400.
| A quantitative relationship between forest growth rates and Thematic Mapper reflectance measurements.Crossref | GoogleScholarGoogle Scholar |
Andreae M, Merlet P (2001) Emission of trace gases and aerosols from biomass burning. Global Biogeochemical Cycles 15, 955–966.
| Emission of trace gases and aerosols from biomass burning.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XjtV2iuw%3D%3D&md5=97bbef209e6448c582d57158ccda567eCAS |
Asner G, Lobell D (2000) A biogeophysical approach for automated SWIR unmixing of soils and vegetation. Remote Sensing of Environment 74, 99–112.
| A biogeophysical approach for automated SWIR unmixing of soils and vegetation.Crossref | GoogleScholarGoogle Scholar |
Baldridge A, Hook S, Grove C, Rivera G (2009) The ASTER spectral library version 2.0. Remote Sensing of Environment 113, 711–715.
| The ASTER spectral library version 2.0.Crossref | GoogleScholarGoogle Scholar |
Barducci A, Mecocci A (2005) Theoretical and experimental assessment of noise effects on least-squares spectral unmixing of hyperspectral images. Optical Engineering 44, 087008
| Theoretical and experimental assessment of noise effects on least-squares spectral unmixing of hyperspectral images.Crossref | GoogleScholarGoogle Scholar |
Bateson C, Asner G, Wessman C (2000) Endmember bundles: a new approach to incorporating endmember variability in spectral mixture analysis. IEEE Transactions on Geoscience and Remote Sensing 38, 1083–1094.
| Endmember bundles: a new approach to incorporating endmember variability in spectral mixture analysis.Crossref | GoogleScholarGoogle Scholar |
Boschetti L, Brivio P, Gregoire J (2003) The use of Meteosat and GMS imagery to detect burned areas in tropical environments. Remote Sensing of Environment 85, 78–91.
| The use of Meteosat and GMS imagery to detect burned areas in tropical environments.Crossref | GoogleScholarGoogle Scholar |
Boschetti L, Eva H, Brivio P, Grregoire J (2004) Lessons to be learned from the comparison of three satellite-derived biomass burning products. Geophysical Research Letters 31, L21501
| Lessons to be learned from the comparison of three satellite-derived biomass burning products.Crossref | GoogleScholarGoogle Scholar |
Brown T, Hall B, Westerling A (2004) The impact of twenty-first century climate change on wildland fire in the western United States. Climatic Change 62, 365–388.
| The impact of twenty-first century climate change on wildland fire in the western United States.Crossref | GoogleScholarGoogle Scholar |
Campbell J, Donato D, Azuma D, Law B (2007) Pyrogenic carbon emission from a large wildfire in oregon, United States. Journal of Geophysical Research 112, G04014
| Pyrogenic carbon emission from a large wildfire in oregon, United States.Crossref | GoogleScholarGoogle Scholar |
Chander G, Markham L, Barsi J (2007) Revised Landsat-5 Thematic Mapper radiometric calibration. IEEE Geoscience and Remote Sensing Letters 4, 490–494.
| Revised Landsat-5 Thematic Mapper radiometric calibration.Crossref | GoogleScholarGoogle Scholar |
Chavez P (1996) Image-based atmospheric corrections – revisited and improved. Photogrammetric Engineering and Remote Sensing 62, 1025–1036.
Conard S, Ivanova G (1997) Wildfire in Russian boreal forest – potential impacts of fire regime characteristics on emissions and global carbon balance estimates. Environmental Pollution 98, 305–313.
| Wildfire in Russian boreal forest – potential impacts of fire regime characteristics on emissions and global carbon balance estimates.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXitlequrc%3D&md5=30e7db4188a83d7f487e1ef9ad9faed4CAS |
Conard S, Sukhinin A, Stocks B, Cahoon D, Davidenko E, Ivanova G (2002) Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia. Climatic Change 55, 197–211.
| Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XntVKqt7o%3D&md5=1bff48c006825ab887336aadd29696d2CAS |
de Groot W, Pritchard J, Lynham T (2009) Forest floor consumption and carbon emissions in Canadian boreal forest fires. Canadian Journal of Forest Research 39, 367–382.
| Forest floor consumption and carbon emissions in Canadian boreal forest fires.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXjtlyntbs%3D&md5=9db1561804054aa8e58ecb6765052a7cCAS |
De Santis A, Chuvieco E (2007) Burn severity estimation from remotely sensed data: performance of simulation versus empirical models. Remote Sensing of Environment 108, 422–435.
| Burn severity estimation from remotely sensed data: performance of simulation versus empirical models.Crossref | GoogleScholarGoogle Scholar |
De Santis A, Chuvieco E (2009) GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data. Remote Sensing of Environment 113, 554–562.
| GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data.Crossref | GoogleScholarGoogle Scholar |
De Santis A, Asner G, Vaughan P, Knapp D (2010) Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery. Remote Sensing of Environment 114, 1535–1545.
| Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery.Crossref | GoogleScholarGoogle Scholar |
Dwyer E, Perreira J, Grégoire J, DaCamara C (2000) Characterization of the spatio-temporal patterns of global fire activity using satellite imagery for the period April 1992 to March 1993. Journal of Biogeography 27, 57–69.
| Characterization of the spatio-temporal patterns of global fire activity using satellite imagery for the period April 1992 to March 1993.Crossref | GoogleScholarGoogle Scholar |
Eidenshink J, Schwind B, Brewer K, Zhu Z, Quayle B, Howard S (2007) A project for monitoring trends in burn severity. Fire Ecology 3, 3–21.
| A project for monitoring trends in burn severity.Crossref | GoogleScholarGoogle Scholar |
Ellicott E, Vermote E, Giglio L, Roberts G (2009) Estimating biomass consumed from fire using MODIS FRE. Geophysical Research Letters 36, L13401
| Estimating biomass consumed from fire using MODIS FRE.Crossref | GoogleScholarGoogle Scholar |
Elmore A, Mustard J, Manning S, Lobell D (2000) Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index. Remote Sensing of Environment 73, 87–102.
| Quantifying vegetation change in semiarid environments: precision and accuracy of spectral mixture analysis and the normalized difference vegetation index.Crossref | GoogleScholarGoogle Scholar |
Epting J, Verbyla D (2005) Landscape-level interactions of prefire vegetation, burn severity, and post-fire vegetation over a 16-year period in interior Alaska. Canadian Journal of Forest Research 35, 1367–1377.
| Landscape-level interactions of prefire vegetation, burn severity, and post-fire vegetation over a 16-year period in interior Alaska.Crossref | GoogleScholarGoogle Scholar |
Epting J, Verbyla D, Sorbel B (2005) Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+. Remote Sensing of Environment 96, 328–339.
| Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+.Crossref | GoogleScholarGoogle Scholar |
Escuin S, Navarro R, Fernandez P (2008) Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images. International Journal of Remote Sensing 29, 1053–1073.
| Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM images.Crossref | GoogleScholarGoogle Scholar |
French N, Kasischke E, Williams D (2003) Variability in the emission of carbon-based trace gases from wildfire in the Alaskan boreal forest. Journal of Geophysical Research 108, 8151
| Variability in the emission of carbon-based trace gases from wildfire in the Alaskan boreal forest.Crossref | GoogleScholarGoogle Scholar |
French N, Goovaerts P, Kasischke E (2004) Uncertainty in estimating carbon emissions from boreal forest fires. Journal of Geophysical Research 109, D14S08
| Uncertainty in estimating carbon emissions from boreal forest fires.Crossref | GoogleScholarGoogle Scholar |
French N, Kasischke E, Hall R, Murphy K, Verbyla D, Hoy E, Allen J (2008) Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results. International Journal of Wildland Fire 17, 443–462.
| Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results.Crossref | GoogleScholarGoogle Scholar |
French N, de Groot W, Jenkins L, Rogers B, Alvarado E, Amiro B, de Jong B, Goetz S, Hoy E, Hyer E, Keane R, Law B, McKenzie D, McNulty S, Ottmar R, Perez-Salicrup D, Randerson J, Robertson K, Turetsky M (2011) Model comparisons for estimating carbon emissions from North American wildland fire. Journal of Geophysical Research 116, G00K05
| Model comparisons for estimating carbon emissions from North American wildland fire.Crossref | GoogleScholarGoogle Scholar |
Giglio L, Loboda T, Roy D, Quayle B, Justice C (2009) An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sensing of Environment 113, 408–420.
| An active-fire based burned area mapping algorithm for the MODIS sensor.Crossref | GoogleScholarGoogle Scholar |
Goodwin N, Coops N, Stone C (2005) Assessing plantation canopy condition from airborne imagery using spectral mixture analysis and fractional abundances. International Journal of Applied Earth Observation and Geoinformation 7, 11–28.
| Assessing plantation canopy condition from airborne imagery using spectral mixture analysis and fractional abundances.Crossref | GoogleScholarGoogle Scholar |
Henry M, Hope A (1998) Monitoring post-burn recovery of chaparral vegetation in southern California using multi-temporal satellite data. International Journal of Remote Sensing 19, 3097–3107.
| Monitoring post-burn recovery of chaparral vegetation in southern California using multi-temporal satellite data.Crossref | GoogleScholarGoogle Scholar |
Hoy E, French N, Turetsky M, Trigg S, Kasischke E (2008) Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forest. International Journal of Wildland Fire 17, 500–514.
| Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forest.Crossref | GoogleScholarGoogle Scholar |
Hudak A, Morgan P, Bobbitt M, Smith A, Lewis S, Lentile L, Robichaud P, Clark J, McKinley R (2007) The relationship of multispectral satellite imagery to immediate fire effects. Fire Ecology 3, 64–90.
| The relationship of multispectral satellite imagery to immediate fire effects.Crossref | GoogleScholarGoogle Scholar |
Irons J, Masek J (2006) Requirements for a Landsat data continuity mission. Photogrammetric Engineering and Remote Sensing 72, 1102–1108.
Jain A (2007) Global estimation of CO emissions using three sets of satellite data for burned area. Atmospheric Environment 41, 6931–6940.
| Global estimation of CO emissions using three sets of satellite data for burned area.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtV2qurvM&md5=d6e5aee1851fbcec808f3e17cdce0353CAS |
Ju J, Roy D (2008) The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally. Remote Sensing of Environment 112, 1196–1211.
| The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally.Crossref | GoogleScholarGoogle Scholar |
Justice C, Giglio L, Korontzi S, Owens J, Morisette J, Roy D, Descloitres J, Alleaume S, Petitcolin F, Kaufman Y (2002) The MODIS fire products. Remote Sensing of Environment 83, 244–262.
| The MODIS fire products.Crossref | GoogleScholarGoogle Scholar |
Kasischke E, Turetsky M, Ottmar R, French N, Hoy E, Kane E (2008) Evaluation of the composite burn index for assessing fire severity in Alaskan black spruce forests. International Journal of Wildland Fire 17, 515–526.
| Evaluation of the composite burn index for assessing fire severity in Alaskan black spruce forests.Crossref | GoogleScholarGoogle Scholar |
Kasischke E, Loboda T, Giglio L, French N, Hoy E, de Jong B, Riaño D (2011) Quantifying burned area for North American forests: implications for direct reduction of carbon stocks. Journal of Geophysical Research 116, G04003
| Quantifying burned area for North American forests: implications for direct reduction of carbon stocks.Crossref | GoogleScholarGoogle Scholar |
Key C (2006) Ecological and sampling constraints on defining landscape fire severity. Fire Ecology 2, 34–59.
| Ecological and sampling constraints on defining landscape fire severity.Crossref | GoogleScholarGoogle Scholar |
Key C, Benson N (2005) Landscape assessment: ground measure of severity; the Composite Burn Index, and remote sensing of severity, the Normalized Burn Index. In ‘FIREMON: Fire effects monitoring and inventory system’. (Eds D Lutes, R Keane, J Caratti, C Key, N Benson, S Sutherland, L Grangi) USDA Forest Service, Rocky Mountains Research Station, General Technical Report RMRS-GTR-164-CD LA, pp. 1–51 (Fort Collins, CO).
Kokaly R, Rockwell B, Haire S, King T (2007) Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing. Remote Sensing of Environment 106, 305–325.
| Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing.Crossref | GoogleScholarGoogle Scholar |
Lelong C, Pinet P, Poilvé H (1998) Hyperspectral imaging and stress mapping in agriculture: a case study on wheat in Beauce (France). Remote Sensing of Environment 66, 179–191.
| Hyperspectral imaging and stress mapping in agriculture: a case study on wheat in Beauce (France).Crossref | GoogleScholarGoogle Scholar |
Lentile L, Holden Z, Smith A, Falkowski M, Hudak A, Morgan P, Lewis S, Gessler P, Benson N (2006) Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
| Remote sensing techniques to assess active fire characteristics and post-fire effects.Crossref | GoogleScholarGoogle Scholar |
Lentile L, Smith A, Hudak A, Morgan P, Bobbitt M, Lewis S, Robichaud P (2009) Remote sensing for prediction of 1-year post-fire ecosystem condition. International Journal of Wildland Fire 18, 594–608.
| Remote sensing for prediction of 1-year post-fire ecosystem condition.Crossref | GoogleScholarGoogle Scholar |
Lewis S, Lentile L, Hudak A, Robichaud P, Morgan P, Bobbitt M (2007) Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in Southern California. Fire Ecology 3, 109–128.
| Mapping ground cover using hyperspectral remote sensing after the 2003 Simi and Old wildfires in Southern California.Crossref | GoogleScholarGoogle Scholar |
Lopez-García M, Caselles V (1991) Mapping burns and natural reforestation using Thematic Mapper data. Geocarto International 6, 31–37.
| Mapping burns and natural reforestation using Thematic Mapper data.Crossref | GoogleScholarGoogle Scholar |
Miller J, Thode A (2007) Quantifying burn severity in a heterogenous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment 109, 66–80.
| Quantifying burn severity in a heterogenous landscape with a relative version of the delta Normalized Burn Ratio (dNBR).Crossref | GoogleScholarGoogle Scholar |
Morgan P, Hardy C, Swetnam T, Rollins M, Long D (2001) Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns. International Journal of Wildland Fire 10, 329–343.
| Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns.Crossref | GoogleScholarGoogle Scholar |
Murphy K, Reynolds J, Koltun J (2008) Evaluating the ability of the differenced Normalized Burn Ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests. International Journal of Wildland Fire 17, 490–499.
| Evaluating the ability of the differenced Normalized Burn Ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests.Crossref | GoogleScholarGoogle Scholar |
Ottmar R, Pritchard S, Vihnanek R, Sandberg D (2006) Modification and validation of fuel consumption models for shrub and forested lands in the Southwest, Pacific Northwest, Rockies, Midwest, Southeast and Alaska. Joint Fire Science Program, Pacific Northwest Research Station, Final Report JFSP 98–1-9–06. (Seattle, WA)
Ottmar R, Sandberg D, Riccardi C, Prichard S (2007) An overview of the Fuel Characteristic Classification System. Canadian Journal of Forest Research 37, 2383–2393.
| An overview of the Fuel Characteristic Classification System.Crossref | GoogleScholarGoogle Scholar |
Pausas J (2004) Changes in fire and climate in the eastern Iberian peninsula (Mediterranean Basin). Climatic Change 63, 337–350.
| Changes in fire and climate in the eastern Iberian peninsula (Mediterranean Basin).Crossref | GoogleScholarGoogle Scholar |
Ray T, Murray B (1996) Nonlinear spectral mixing in desert vegetation. Remote Sensing of Environment 55, 59–64.
| Nonlinear spectral mixing in desert vegetation.Crossref | GoogleScholarGoogle Scholar |
Riaño D, Moreno-Ruiz J, Isidoros D, Ustin S (2007) Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder. Global Change Biology 13, 40–50.
| Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder.Crossref | GoogleScholarGoogle Scholar |
Roberts D, Smith M, Adams J (1993) Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data. Remote Sensing of Environment 44, 255–269.
| Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data.Crossref | GoogleScholarGoogle Scholar |
Roberts D, Gardner M, Church R, Ustin S, Scheer G, Green R (1998) Mapping chaparral in the Santa Monica mountains using multiple endmember spectral mixture models. Remote Sensing of Environment 65, 267–279.
| Mapping chaparral in the Santa Monica mountains using multiple endmember spectral mixture models.Crossref | GoogleScholarGoogle Scholar |
Robichaud P, Lewis S, Laes D, Hudak A, Kokaly R, Zamudio J (2007) Post-fire soil burn severity mapping with hyperspectral image unmixing. Remote Sensing of Environment 108, 467–480.
| Post-fire soil burn severity mapping with hyperspectral image unmixing.Crossref | GoogleScholarGoogle Scholar |
Roder A, Hill J, Duguy B, Alloza J, Vallejo R (2008) Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain). Remote Sensing of Environment 112, 259–273.
| Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain).Crossref | GoogleScholarGoogle Scholar |
Rogan J, Franklin J (2001) Mapping wildfire burn severity in southern California forest and shrublands using enhanced Thematic Mapper imagery. Geocarto International 16, 91–106.
| Mapping wildfire burn severity in southern California forest and shrublands using enhanced Thematic Mapper imagery.Crossref | GoogleScholarGoogle Scholar |
Roy D, Jin Y, Lewis P, Justice C (2005) Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data. Remote Sensing of Environment 97, 137–162.
| Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data.Crossref | GoogleScholarGoogle Scholar |
Roy D, Boschetti L, Trigg S (2006) Remote sensing of fire severity: assessing the performance of the Normalized Burn Ratio. IEEE Transactions on Geoscience and Remote Sensing 3, 112–116.
| Remote sensing of fire severity: assessing the performance of the Normalized Burn Ratio.Crossref | GoogleScholarGoogle Scholar |
Roy D, Boschetti L, Justice C, Ju J (2008) The collection 5 MODIS burned area product – global evaluation by comparison with the MODIS active fire product. Remote Sensing of Environment 112, 3690–3707.
| The collection 5 MODIS burned area product – global evaluation by comparison with the MODIS active fire product.Crossref | GoogleScholarGoogle Scholar |
Sá A, Pereira J, Silva J (2005) Estimation of combustion completeness based on fire-induced spectral reflectance changes in a dambo grassland (Western Province, Zambia). International Journal of Remote Sensing 26, 4185–4195.
| Estimation of combustion completeness based on fire-induced spectral reflectance changes in a dambo grassland (Western Province, Zambia).Crossref | GoogleScholarGoogle Scholar |
Seiler W, Crutzen P (1980) Estimates of gross and net fluxes of carbon between the biosphere and atmosphere from biomass burning. Climatic Change 2, 207–247.
| Estimates of gross and net fluxes of carbon between the biosphere and atmosphere from biomass burning.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL3cXlsFelt7c%3D&md5=18792b7c1e8a4368319a9ef89f3d95c6CAS |
Smith A, Wooster M, Drake N, Dipotso F, Falkowski M, Hudak A (2005) Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African savannahs. Remote Sensing of Environment 97, 92–115.
| Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African savannahs.Crossref | GoogleScholarGoogle Scholar |
Smith A, Lentile L, Hudak A, Morgan P (2007) Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a North American ponderosa pine forest. International Journal of Remote Sensing 28, 5159–5166.
| Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a North American ponderosa pine forest.Crossref | GoogleScholarGoogle Scholar |
Smith A, Eitel J, Hudak A (2010) Spectral analysis of charcoal on soils: implications for wildland fire severity mapping methods. International Journal of Wildland Fire 19, 976–983.
| Spectral analysis of charcoal on soils: implications for wildland fire severity mapping methods.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXhtlyjsL3M&md5=177dc54d286e786b840bb8115a3b5d3fCAS |
Solans Vila G, Barbosa P (2010) Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data. Ecological Modelling 221, 75–84.
| Post-fire vegetation regrowth detection in the Deiva Marina region (Liguria-Italy) using Landsat TM and ETM+ data.Crossref | GoogleScholarGoogle Scholar |
Somers B, Cools K, Delalieux S, Stuckens J, Van der Zande D, Verstraeten WW, Coppin P (2009) Nonlinear hyperspectral mixture analysis for tree cover estimates in orchards. Remote Sensing of Environment 113, 1183–1193.
| Nonlinear hyperspectral mixture analysis for tree cover estimates in orchards.Crossref | GoogleScholarGoogle Scholar |
Somers B, Verbesselt J, Ampe E, Sims N, Verstraeten WW, Coppin P (2010) Spectral mixture analysis to monitor defoliation in mixed-age Eucalyptus globulus Labill. plantations in southern Australia using Landsat 5-TM and EO-A Hyperion data. International Journal of Applied Earth Observation and Geoinformation 12, 270–277.
| Spectral mixture analysis to monitor defoliation in mixed-age Eucalyptus globulus Labill. plantations in southern Australia using Landsat 5-TM and EO-A Hyperion data.Crossref | GoogleScholarGoogle Scholar |
Somers B, Asner G, Tits L, Coppin P (2011) Endmember variability in Spectral Mixture Analysis: a review. Remote Sensing of Environment 115, 1603–1616.
| Endmember variability in Spectral Mixture Analysis: a review.Crossref | GoogleScholarGoogle Scholar |
van der Werf G, Randerson J, Giglio L, Collatz G, Kasibhatla P, Arellano A (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural and peat fires (1997–2009). Atmospheric Chemistry and Physics 10, 11707–11735.
| Global fire emissions and the contribution of deforestation, savanna, forest, agricultural and peat fires (1997–2009).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXmvFemsb0%3D&md5=8b27651f8ad8ae5ddbb23beb6dc53fadCAS |
van Wagtendonk J, Root R, Key C (2004) Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment 92, 397–408.
| Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Lhermitte S, Verstraeten WW, Goossens R (2010a) The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece. Remote Sensing of Environment 114, 2548–2563.
| The temporal dimension of differenced Normalized Burn Ratio (dNBR) fire/burn severity studies: the case of the large 2007 Peloponnese wildfires in Greece.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Verstraeten WW, Lhermitte S, Goossens R (2010b) Evaluation Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece. International Journal of Wildland Fire 19, 558–569.
| Evaluation Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Lhermitte S, Verstraeten WW, Goossens R (2010c) Illumination effects on the differenced Normalized Burn Ratio’s optimality for assessing fire severity. International Journal of Applied Earth Observation and Geoinformation 12, 60–70.
| Illumination effects on the differenced Normalized Burn Ratio’s optimality for assessing fire severity.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Lhermitte S, Verstraeten WW, Goossens R (2011) Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper. International Journal of Remote Sensing 32, 3521–3537.
| Evaluation of pre/post-fire differenced spectral indices for assessing burn severity in a Mediterranean environment with Landsat Thematic Mapper.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Somers B, Gitas I, Katagis T, Polychronaki A, Goossens R (2012a) Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: accounting for soil brightness variation. International Journal of Applied Earth Observation and Geoinformation 14, 1–11.
| Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: accounting for soil brightness variation.Crossref | GoogleScholarGoogle Scholar |
Veraverbeke S, Hook S, Hulley G (2012b) An alternative spectral index for rapid fire severity assessments. Remote Sensing of Environment 123, 72–80.
| An alternative spectral index for rapid fire severity assessments.Crossref | GoogleScholarGoogle Scholar |
Verbyla D, Kasischke E, Hoy E (2008) Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data. International Journal of Wildland Fire 17, 527–534.
| Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data.Crossref | GoogleScholarGoogle Scholar |
Zhu Z, Key C, Ohlen D, Benson N (2006) Evaluate sensitivities of burn-severity mapping algorithms for different ecosystems and fire histories in the United States. US Department of Interior, Final Report to the Joint Fire Science Program: Project JFSP 01–1-4–12, pp. 1–36. (Sioux Falls, SD)
