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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

Sarah A. Lewis A D , Andrew T. Hudak A , Peter R. Robichaud A , Penelope Morgan B , Kevin L. Satterberg B , Eva K. Strand B , Alistair M. S. Smith B , Joseph A. Zamudio C and Leigh B. Lentile B
+ Author Affiliations
- Author Affiliations

A USDA, Forest Service, Rocky Mountain Research Station, 1221 South Main Street, Moscow, ID 83843, USA.

B Department of Forest, Rangeland, and Fire Sciences, University of Idaho, 975 West 6th Street, Moscow, ID 83844, USA.

C Unmanned Aircraft Systems USA (UASUSA), 229 Airport Road, East Hangar, Longmont, CO 80503, USA.

D Corresponding author. Email: sarahlewis@fs.fed.us

International Journal of Wildland Fire 26(9) 755-771 https://doi.org/10.1071/WF17019
Submitted: 17 February 2016  Accepted: 12 June 2017   Published: 6 September 2017

Journal Compilation © IAWF 2017 Open Access CC BY-NC-ND

Abstract

We collected field and remotely sensed data spanning 10 years after three 2003 Montana wildfires to monitor ecological change across multiple temporal and spatial scales. Multiple endmember spectral mixture analysis was used to create post-fire maps of: char, soil, green (GV) and non-photosynthetic (NPV) vegetation from high-resolution 2003 hyperspectral (HS) and 2007 QuickBird (QB) imagery, and from Landsat 5 and 8 imagery collected on anniversary dates in 2002, 2003 (post fire), 2004, 2007 and 2013. Initial estimates of char and NPV from the HS images were significantly correlated with their ground-measured counterparts (ρ = 0.60 (P = 0.03) and 0.68 (P = 0.01) respectively), whereas HS GV and Landsat GV were correlated with canopy GV (ρ = 0.75 and 0.70 (P = 0.003) respectively). HS imagery had stronger direct correlations with all classes of fine-scale ground data than Landsat and also had stronger predictive correlations with 10-year canopy data (ρ = 0.65 (P = 0.02) to 0.84 (P = 0.0003)). There was less than 5% understorey GV cover on the sites initially, but by 2013, it had increased to nearly 60% regardless of initial condition. The data suggest it took twice as long for understorey GV and NPV to replace char and soil as primary ground cover components on the high-burn-severity sites compared with other sites.

Additional keywords: char, hyperspectral remote sensing, multiple endmember spectral mixture analysis, QuickBird.


References

Abella SR, Fornwalt PJ (2015) Ten years of vegetation assembly after a North American mega fire. Global Change Biology 21, 789–802.
Ten years of vegetation assembly after a North American mega fire.Crossref | GoogleScholarGoogle Scholar |

Agee JK (1998) The landscape ecology of western fire regimes. Northwest Science 72, 24–34.

AIG (Analytical Imaging and Geophysics, LLC) (2002) ‘ACORN 5.0 User’s Guide.’ (AIG: Boulder, CO, USA)

Arno SF, Parsons DJ, Keane RE (2000) Mixed-severity fire regimes in the Northern Rocky Mountains: consequences of fire exclusion and options for the future. In ‘Proceedings of the wilderness science in a time of change conference, Vol. 5: Wilderness ecosystems, threats and management’. (Eds DN Cole, SF McCool, WT Borrie, J O’Laughlin) USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-15-VOL-5, pp. 225–232. (Fort Collins, CO, USA)

ASD (Analytical Spectral Devices, Inc.) (2002) ‘FieldSpec Pro User’s Guide.’(ASD: Boulder, CO, USA)

Bartels SF, Chen HYH, Wulder MA, White JC (2016) Trends in post-disturbance recovery rates of Canada’s forests following wildfire and harvest. Forest Ecology and Management 361, 194–207.
Trends in post-disturbance recovery rates of Canada’s forests following wildfire and harvest.Crossref | GoogleScholarGoogle Scholar |

Bataineh AL, Oswald BP, Bataineh MM, Williams HM, Coble DW (2006) Changes in understory vegetation of a ponderosa pine forest in northern Arizona 30 years after a wildfire. Forest Ecology and Management 235, 283–294.
Changes in understory vegetation of a ponderosa pine forest in northern Arizona 30 years after a wildfire.Crossref | GoogleScholarGoogle Scholar |

Berryman EM, Morgan P, Robichaud PR, Page-Dumroese D (2014) Post-fire erosion control mulches alter belowground processes and nitrate reductase activity of a perennial forb, heartleaf arnica (Arnica cordifolia). USDA Forest Service, Rocky Mountain Research Station, Research Note RMRS-RN-69. (Fort Collins, CO, USA)

Bowman DMJ, Balch JK, Artaxo P, Bond WJ, Carlson JM, Cochrane MA, D’Antonio CM, DeFries RS, Doyle JC, Harrison SP, Johnston FH, Keeley JE, Krawchuk MA, Kull CA, Marston JB, Moritz MA, Prentice IC, Roos CI, Scott AC, Swetnam TW, van der Werf GR, Pyne SJ (2009) Fire in the Earth system. Science 324, 481–484.
Fire in the Earth system.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXkvVGmtb8%3D&md5=96f7dafa4667da9a81da3ac8af295e1bCAS |

Clark RN, Swayze GA, Livo KE, Kokaly RF, King TV, Dalton JB, Vance JS, Rockwell BW, Hoefen T, McDougal RR (2002) Surface reflectance calibration of terrestrial imaging spectroscopy data: a tutorial using AVIRIS. In ‘Proceedings of the 10th JPL airborne sciences workshop (Pasadena, CA, 27 February–2 March 2001’. (Ed. RO Green) (Jet Propulsion Laboratory: Pasadena, CA) Available at http://speclab.cr.usgs.gov/PAPERS.calibration.tutorial [Accessed 23 November 2016]

Cochrane MA, Souza CM (1998) Linear mixture model classification of burned forests in the eastern Amazon. International Journal of Remote Sensing 19, 3433–3440.
Linear mixture model classification of burned forests in the eastern Amazon.Crossref | GoogleScholarGoogle Scholar |

Cocke AE, Fule PZ, Crouse JE (2005) Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data. International Journal of Wildland Fire 14, 189–198.
Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data.Crossref | GoogleScholarGoogle Scholar |

Cooper SV, Neiman KE, Roberts DW (1991) Forest habitat types of northern Idaho: a second approximation. USDA Forest Service, Intermountain Research Station, General Technical Report INT-236. (Ogden, UT, USA)

Dale VH, Joyce LA, McNulty S, Neilson RP, Ayres MP, Flannigan MD, Hanson PJ, Irland LC, Lugo AE, Peterson CJ, Simberloff D, Swanson FJ, Stocks BJ, Wotton BM (2001) Climate change and forest disturbances: climate change can affect forests by altering the frequency, intensity, duration, and timing of fire, drought, introduced species, insect and pathogen outbreaks, hurricanes, windstorms, ice storms, or landslides. Bioscience 51, 723–734.
Climate change and forest disturbances: climate change can affect forests by altering the frequency, intensity, duration, and timing of fire, drought, introduced species, insect and pathogen outbreaks, hurricanes, windstorms, ice storms, or landslides.Crossref | GoogleScholarGoogle Scholar |

Dennison PE, Roberts DA (2003) Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE. Remote Sensing of Environment 87, 123–135.
Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE.Crossref | GoogleScholarGoogle Scholar |

Dennison PE, Halligan KQ, Roberts DA (2004) A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper. Remote Sensing of Environment 93, 359–367.
A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper.Crossref | GoogleScholarGoogle Scholar |

Diaz-Delgado R, Lloret F, Pons X (2003) Influence of fire severity on plant regeneration by means of remote sensing imagery. International Journal of Remote Sensing 24, 1751–1763.
Influence of fire severity on plant regeneration by means of remote sensing imagery.Crossref | GoogleScholarGoogle Scholar |

Eckmann TC, Roberts DA, Still CJ (2008) Using multiple endmember spectral mixture analysis to retrieve subpixel fire properties from MODIS. Remote Sensing of Environment 112, 3773–3783.
Using multiple endmember spectral mixture analysis to retrieve subpixel fire properties from MODIS.Crossref | GoogleScholarGoogle Scholar |

Eidenshink J, Schwind B, Brewer K, Zhu ZL, 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 |

Fernandez-Manso A, Quintano C, Roberts DA (2016) Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems. Remote Sensing of Environment 184, 112–123.
Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems.Crossref | GoogleScholarGoogle Scholar |

Fischer WC, Bradley AF (1987) Fire ecology of western Montana forest habitat types. USDA Forest Service, Intermountain Research Station, General Technical Report INT-223. (Ogden, UT, USA)

French NHF, Goovaerts P, Kasischke ES (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 |

Hayes JJ, Robeson SM (2011) Relationships between fire severity and post-fire landscape pattern following a large mixed-severity fire in the Valle Vidal, New Mexico, USA. Forest Ecology and Management 261, 1392–1400.
Relationships between fire severity and post-fire landscape pattern following a large mixed-severity fire in the Valle Vidal, New Mexico, USA.Crossref | GoogleScholarGoogle Scholar |

Hicke JA, Asner GP, Kasischke ES, French NHF, Randerson JT, Collatz GJ, Stocks BJ, Tucker CJ, Los SO, Field CB (2003) Post-fire response of North American boreal forest net primary productivity analyzed with satellite observations. Global Change Biology 9, 1145–1157.
Post-fire response of North American boreal forest net primary productivity analyzed with satellite observations.Crossref | GoogleScholarGoogle Scholar |

Holden ZA, Morgan P, Smith AMS, Vierling L (2010) Beyond Landsat: a comparison of four satellite sensors for detecting burn severity in ponderosa pine forests of the Gila Wilderness, NM, USA. International Journal of Wildland Fire 19, 449–458.
Beyond Landsat: a comparison of four satellite sensors for detecting burn severity in ponderosa pine forests of the Gila Wilderness, NM, USA.Crossref | GoogleScholarGoogle Scholar |

Hudak AT, Morgan P, Bobbitt M, Smith AMS, Lewis SA, Lentile LB (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 |

Hudak AT, Ottmar RD, Vihnanek RE, Brewer NW, Smith AMS, Morgan P (2013) The relationship of post-fire white ash cover to surface fuel consumption. International Journal of Wildland Fire 22, 780–785.
The relationship of post-fire white ash cover to surface fuel consumption.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtlyqurfN&md5=dc3a49228a6db415d24b63831e3617aaCAS |

Idris MH, Kurajo K, Suzuki M (2005) Evaluating vegetation recovery following large-scale forest fires in Borneo and north-eastern China using multitemporal NOAA-AVHRR images. Journal of Forest Research 10, 101–111.
Evaluating vegetation recovery following large-scale forest fires in Borneo and north-eastern China using multitemporal NOAA-AVHRR images.Crossref | GoogleScholarGoogle Scholar |

Kashian DM, Romme WH, Tinker DB, Turner MG, Ryan MG (2006) Carbon storage on landscapes with stand-replacing fires. Bioscience 56, 598–606.
Carbon storage on landscapes with stand-replacing fires.Crossref | GoogleScholarGoogle Scholar |

Kokaly RF, Rockwell BW, Haire SL, King TVV (2007) Characterization of post-fire surface cover, soils, and burn severity and 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 and the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing.Crossref | GoogleScholarGoogle Scholar |

Kolden CA, Lutz LA, Key CH, Kane JT, van Wagtendonk JW (2012) Mapped versus actual burned area within wildfire perimeters: characterizing the unburned. Forest Ecology and Management 286, 38–47.
Mapped versus actual burned area within wildfire perimeters: characterizing the unburned.Crossref | GoogleScholarGoogle Scholar |

Kolden CA, Smith AMS, Abatzoglou JT (2015) Limitations and utilisation of Monitoring Trends in Burn Severity products for assessing wildfire severity in the USA. International Journal of Wildland Fire 24, 1023–1028.

Lentile LB, Holden ZA, Smith AMS, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE, Benson NC (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 LB, Morgan P, Hudak AT, Bobbitt MJ, Lewis SA, Smith AMS, Robichaud PR (2007a) Burn severity and vegetation response following eight large wildfires across the western US. Fire Ecology 3, 91–108.
Burn severity and vegetation response following eight large wildfires across the western US.Crossref | GoogleScholarGoogle Scholar |

Lentile L, Morgan P, Hardy C, Hudak A, Means R, Ottmar R, Robichaud P, Sutherland E, Way F, Lewis S (2007b) Lessons learned from rapid response research on wildland fires. Fire Management Today 67, 24–31.

Lentile LB, Smith AMS, Hudak AT, Morgan P, Bobbitt MJ, Lewis SA, Robichaud PR (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 SA, Lentile LB, Hudak AT, Robichaud PR, Morgan P, Bobbitt MJ (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 |

Lewis SA, Hudak AT, Ottmar RD, Robichaud PR, Lentile LB, Hood SM, Cronan JB, Morgan P (2011) Using hyperspectral imagery to estimate forest floor consumption from wildfire in boreal forests of Alaska, USA. International Journal of Wildland Fire 20, 255–271.
Using hyperspectral imagery to estimate forest floor consumption from wildfire in boreal forests of Alaska, USA.Crossref | GoogleScholarGoogle Scholar |

Li L, Ustin SL, Lay M (2005) Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA. International Journal of Remote Sensing 26, 5193–5207.
Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA.Crossref | GoogleScholarGoogle Scholar |

Loehman RA, Reinhardt E, Riley KL (2014) Wildland fire emissions, carbon, and climate: seeing the forest and the trees – a cross-scale assessment of wildfire and carbon dynamics in fire-prone, forested ecosystems. Forest Ecology and Management 317, 9–19.
Wildland fire emissions, carbon, and climate: seeing the forest and the trees – a cross-scale assessment of wildfire and carbon dynamics in fire-prone, forested ecosystems.Crossref | GoogleScholarGoogle Scholar |

Morgan P, Keane RE, Dillon GK, Jain TB, Hudak AT, Karau EC, Sikkink PG, Holden ZA, Strand EK (2014) Challenge of assessing fire and burn severity using field measures, remote sensing and modelling. International Journal of Wildland Fire 23, 1045–1060.
Challenge of assessing fire and burn severity using field measures, remote sensing and modelling.Crossref | GoogleScholarGoogle Scholar |

Neary DG, Klopatek CC, DeBano LF, Ffolliott PF (1999) Fire effects on belowground sustainability: a review and synthesis. Forest Ecology and Management 122, 51–71.
Fire effects on belowground sustainability: a review and synthesis.Crossref | GoogleScholarGoogle Scholar |

Okin GS, Roberts DA, Murray B, Okin WJ (2001) Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments. Remote Sensing of Environment 77, 212–225.
Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments.Crossref | GoogleScholarGoogle Scholar |

Page-Dumroese DS, Abbott AM, Rice TM (2009) Forest soil disturbance mapping protocol. Volume II: Supplementary methods, statistics, and data collection. USDA Forest Service, General Technical Report WO-82b. (Washington, DC, USA)

Parsons A, Robichaud PR, Lewis SA, Napper C, Clark JT (2010) Field guide for mapping post-fire soil burn severity. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-243. (Fort Collins, CO, USA)

Perry DA, Hessburg PF, Skinner CN, Spies TA, Stephens SL, Taylor AH, Franklin JF, McComb B, Riegel G (2011) The ecology of mixed severity fire regimes in Washington, Oregon, and northern California. Forest Ecology and Management 262, 703–717.
The ecology of mixed severity fire regimes in Washington, Oregon, and northern California.Crossref | GoogleScholarGoogle Scholar |

Peters DP, Pielke RA, Bestelmeyer BT, Allen CD, Munson-McGee S, Havstad KM (2004) Cross-scale interactions, non-linearities, and forecasting catastrophic events. Proceedings of the National Academy of Sciences of the United States of America 101, 15130–15135.
Cross-scale interactions, non-linearities, and forecasting catastrophic events.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXpsVSgs7c%3D&md5=9bebd92236eaefd7592d47a7bdc0047cCAS |

Pfister RD, Kovalchik BL, Arno SF, Presby RC (1977) Forest habitat types of Montana. USDA Forest Service, Intermountain Research Station, General Technical Report INT-34. (Ogden, UT, USA)

Powell RL, Roberts DA (2008) Characterizing variability of the urban physical environment for a suite of cities in Rondonia, Brazil. Earth Interactions 12, 1–32.
Characterizing variability of the urban physical environment for a suite of cities in Rondonia, Brazil.Crossref | GoogleScholarGoogle Scholar |

Quintano C, Fernandez-Manso A, Roberts DA (2013) Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sensing of Environment 136, 76–88.
Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries.Crossref | GoogleScholarGoogle Scholar |

Quintano C, Fernandez-Manso A, Roberts DA (2017) Burn severity mapping from Landsat MESMA fraction images and land surface temperature. Remote Sensing of Environment 190, 83–95.
Burn severity mapping from Landsat MESMA fraction images and land surface temperature.Crossref | GoogleScholarGoogle Scholar |

Richards JA, Jia X (1999) ‘Remote sensing digital image analysis: an introduction’, 3rd edn. (Springer Verlag: Berlin, Germany)

Roberts DA, Smith MO, Adams JB (1993) Green vegetation, non-photosynthetic vegetation, and soils in AVIRIS data. Remote Sensing of Environment 44, 255–269.
Green vegetation, non-photosynthetic vegetation, and soils in AVIRIS data.Crossref | GoogleScholarGoogle Scholar |

Roberts DA, Gardner M, Church R, Ustin S, Scheer G, Green RO (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 PR, Lewis SA, Laes DYM, Hudak AT, Kokaly RF, Zamudio JA (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 |

Rocca ME, Miniat CF, Mitchell RJ (2014) Introduction to the regional assessments: climate change, wildfire, and forest ecosystem services in the USA. Forest Ecology and Management 327, 265–268.
Introduction to the regional assessments: climate change, wildfire, and forest ecosystem services in the USA.Crossref | GoogleScholarGoogle Scholar |

Rogan J, Yool SR (2001) Mapping fire-induced vegetation depletion in the Peloncillo Mountains, Arizona and New Mexico. International Journal of Remote Sensing 22, 3101–3121.
Mapping fire-induced vegetation depletion in the Peloncillo Mountains, Arizona and New Mexico.Crossref | GoogleScholarGoogle Scholar |

Romme WH, Boyce MS, Gresswell R, Merrill EH, Minshall GW, Whitlock C, Turner MG (2011) Twenty years after the 1988 Yellowstone fires: lessons about disturbance and ecosystems. Ecosystems 14, 1196–1215.
Twenty years after the 1988 Yellowstone fires: lessons about disturbance and ecosystems.Crossref | GoogleScholarGoogle Scholar |

Roth KL, Dennison PE, Roberts DA (2012) Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data. Remote Sensing of Environment 127, 139–152.
Comparing endmember selection techniques for accurate mapping of plant species and land cover using imaging spectrometer data.Crossref | GoogleScholarGoogle Scholar |

Roy DP, Boschetti L, Trigg SN (2006) Remote sensing of fire severity: assessing the performance of the Normalized Burn Ratio. IEEE Geoscience and Remote Sensing Letters 3, 112–116.
Remote sensing of fire severity: assessing the performance of the Normalized Burn Ratio.Crossref | GoogleScholarGoogle Scholar |

RSAC (Remote Sensing Applications Center) (2005) Remote Sensing Applications Center Burned Area Emergency Response (BAER) imagery support. USDA Forest Service, Remote Sensing Applications Center. (Salt Lake City, UT, USA) Available at http://www.fs.fed.us/eng/rsac/baer/ [Accessed 10 June 2016]

Ryan KC (2002) Dynamic interactions between forest structure and fire behavior in boreal ecosystems. Silva Fennica 36, 13–39.
Dynamic interactions between forest structure and fire behavior in boreal ecosystems.Crossref | GoogleScholarGoogle Scholar |

Sá ACL, Pereira JMC, Vasconcelos MJP, Silva JMN, Ribeiro N, Awasse A (2003) Assessing the feasibility of subpixel burned area mapping in miombo woodlands of northern Mozambique using MODIS imagery. International Journal of Remote Sensing 24, 1783–1796.
Assessing the feasibility of subpixel burned area mapping in miombo woodlands of northern Mozambique using MODIS imagery.Crossref | GoogleScholarGoogle Scholar |

Sankey JB, Wallace CSA, Ravi S (2013) Phenology-based, remote sensing of post-burn disturbance windows in rangelands. Ecological Indicators 30, 35–44.
Phenology-based, remote sensing of post-burn disturbance windows in rangelands.Crossref | GoogleScholarGoogle Scholar |

SAS Institute Inc. (2003) ‘SAS System software.’ (SAS Institute Inc.: Cary, NC, USA)

Schoennagel T, Smithwick EAH, Turner MG (2008) Landscape heterogeneity following large fires: insights from Yellowstone National Park, USA. International Journal of Wildland Fire 17, 742–753.
Landscape heterogeneity following large fires: insights from Yellowstone National Park, USA.Crossref | GoogleScholarGoogle Scholar |

Settle JJ, Drake NA (1993) Linear mixing and the estimation of ground cover proportions. International Journal of Remote Sensing 14, 1159–1177.
Linear mixing and the estimation of ground cover proportions.Crossref | GoogleScholarGoogle Scholar |

Shive KL, Sieg CH, Fulé PZ (2013) Pre-wildfire management treatments interact with fire severity to have lasting effects on post-wildfire vegetation response. Forest Ecology and Management 297, 75–83.
Pre-wildfire management treatments interact with fire severity to have lasting effects on post-wildfire vegetation response.Crossref | GoogleScholarGoogle Scholar |

Smith AMS, Hudak AT (2005) Estimating combustion of large downed woody debris from residual white ash. International Journal of Wildland Fire 14, 245–248.
Estimating combustion of large downed woody debris from residual white ash.Crossref | GoogleScholarGoogle Scholar |

Smith AMS, Wooster MJ, Drake NA, Dipotso FM, Falkowski MJ, Hudak AT (2005) Testing the potential of multispectral remote sensing for retrospectively estimating fire severity in African savannahs environments. Remote Sensing of Environment 97, 92–115.
Testing the potential of multispectral remote sensing for retrospectively estimating fire severity in African savannahs environments.Crossref | GoogleScholarGoogle Scholar |

Smith AMS, Lentile LB, Hudak AT, Morgan P (2007a) 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 AMS, Drake NA, Wooster MJ, Hudak AT, Holden ZA, Gibbons CJ (2007b) Production of Landsat ETM+ reference imagery of burned areas within southern African savannas: comparison of methods and application to MODIS. International Journal of Remote Sensing 28, 2753–2775.
Production of Landsat ETM+ reference imagery of burned areas within southern African savannas: comparison of methods and application to MODIS.Crossref | GoogleScholarGoogle Scholar |

Smith AMS, Eitel JUH, Hudak AT (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=50e57dbb280ef5831dd751ea03a03f3bCAS |

Smith AMS, Kolden CA, Tinkham WT, Talhelm A, Marshall JD, Hudak AT, Boschetti L, Falkowski MJ, Greenberg JA, Anderson JW, Kliskey A, Alessa L, Keefe RF, Gosz J (2014) Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems. Remote Sensing of Environment 154, 322–337.
Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems.Crossref | GoogleScholarGoogle Scholar |

Smith AMS, Sparks AM, Kolden CA, Abatzoglou JT, Talhelm AF, Johnson DM, Boschetti L, Lutz JA, Apostol KG, Yedinak KM, Tinkham WT, Kremens RJ (2016) Towards a new paradigm in fire severity research using dose–response experiments. International Journal of Wildland Fire 25, 158–166.
Towards a new paradigm in fire severity research using dose–response experiments.Crossref | GoogleScholarGoogle Scholar |

Stephan K, Kavanagh KL, Koyama A (2012) Effects of spring prescribed burning and wildfires on watershed nitrogen dynamics of central Idaho headwater areas. Forest Ecology and Management 263, 240–252.
Effects of spring prescribed burning and wildfires on watershed nitrogen dynamics of central Idaho headwater areas.Crossref | GoogleScholarGoogle Scholar |

Tompkins S, Mustard JF, Pieters CM, Forsyth DW (1997) Optimization of endmembers for spectral mixture analysis. Remote Sensing of Environment 59, 472–489.
Optimization of endmembers for spectral mixture analysis.Crossref | GoogleScholarGoogle Scholar |

van Wagtendonk JW, Root RR, Key CH (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, Hook SJ (2013) Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness, and carbon emissions. International Journal of Wildland Fire 22, 707–720.
Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness, and carbon emissions.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhtFyntrjE&md5=da0bb7e24542e8973d5ef767ec7393a7CAS |

Veraverbeke S, Hook SJ, Harris S (2012) Synergy of VSWIR (0.4–2.5 μm) and MTIR (3.5–12.5 μm) data for post-fire assessments. Remote Sensing of Environment 124, 771–779.
Synergy of VSWIR (0.4–2.5 μm) and MTIR (3.5–12.5 μm) data for post-fire assessments.Crossref | GoogleScholarGoogle Scholar |

Viedma O, Meliá J, Segarra D, Garcia-Haro J (1997) Modeling rates of ecosystem recovery after fires by using Landsat TM data. Remote Sensing of Environment 61, 383–398.
Modeling rates of ecosystem recovery after fires by using Landsat TM data.Crossref | GoogleScholarGoogle Scholar |

Viedma O, Torres I, Perez B, Moreno JM (2012) Modeling plant species richness using reflectance and texture data derived from QuickBird in a recently burned area of central Spain. Remote Sensing of Environment 119, 208–221.
Modeling plant species richness using reflectance and texture data derived from QuickBird in a recently burned area of central Spain.Crossref | GoogleScholarGoogle Scholar |

Wang JJ, Zhang Y, Bussink C (2012) Unsupervised multiple endmember spectral mixture analysis-based detection of opium poppy fields from an EO-1 Hyperion image in Helmand, Afghanistan. The Science of the Total Environment 476–477, 1–6.

Willis KS (2015) Remote sensing change detection for ecological monitoring in United States protected areas. Biological Conservation 182, 233–242.
Remote sensing change detection for ecological monitoring in United States protected areas.Crossref | GoogleScholarGoogle Scholar |

Wittenberg L, Malkinson D, Beeri O, Halutzy A, Tesler N (2007) Spatial and temporal patterns of vegetation recovery following sequences of forest fires in a Mediterranean landscape, Mt Carmel, Israel. Catena 71, 76–83.
Spatial and temporal patterns of vegetation recovery following sequences of forest fires in a Mediterranean landscape, Mt Carmel, Israel.Crossref | GoogleScholarGoogle Scholar |

Yang J, He Y, Caspersen J (2015) Fully constrained linear spectral unmixing-based global shadow compensation for high-resolution satellite imagery of urban areas. International Journal of Applied Earth Observation and Geoinformation 38, 88–98.
Fully constrained linear spectral unmixing-based global shadow compensation for high-resolution satellite imagery of urban areas.Crossref | GoogleScholarGoogle Scholar |

Youngentob KN, Roberts DA, Held AA, Dennison PE, Jia X, Lindenmayer DB (2011) Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data. Remote Sensing of Environment 115, 1115–1128.
Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data.Crossref | GoogleScholarGoogle Scholar |