The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
A Project for Monitoring Trends in Burn Severity
Open accessAbstract
Elected officials and leaders of environmental agencies need information about the effects of large wildfires in order to set policy and make management decisions. Recently, the Wildland Fire Leadership Council (WFLC), which implements and coordinates the National Fire Plan (NFP) and Federal Wildland Fire Management Policies (National Fire Plan 2004 ), adopted a strategy to monitor the effectiveness of the National Fire Plan and the Healthy Forests Restoration Act (HFRA). One component of this strategy is to assess the environmental impacts of large wildland fires and identify the trends of burn severity on all lands across the United States. To that end, WFLC has sponsored a six-year project, Monitoring Trends in Burn Severity (MTBS), which requires the U.S. Department of Agriculture Forest Service (USDA-FS) and the U.S. Geological Survey (USGS) to map and assess the burn severity for all large current and historical fires. Using Landsat data and the differenced Normalized Burn Ratio (dNBR) algorithm, the USGS Center for Earth Resources Observation and Science (EROS) and USDA-FS Remote Sensing Applications Center will map burn severity of all fires since 1984 greater than 202 ha (500 ac) in the east, and 404 ha (1,000 ac) in the west. The number of historical fires from this period combined with current fires occurring during the course of the project will exceed 9,000. The MTBS project will generate burn severity data, maps, and reports, which will be available for use at local, state, and national levels to evaluate trends in burn severity and help develop and assess the effectiveness of land management decisions. Additionally, the information developed will provide a baseline from which to monitor the recovery and health of fire-affected landscapes over time. Spatial and tabular data quantifying burn severity will augment existing information used to estimate risk associated with a range of current and future resource threats. The annual report of 2004 fires has been completed. All data and results will be distributed to the public on a Web site.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“MTBS is currently the best dataset available for the purpose of this analysis, because it contains the largest historical record of CONUS wildland fires larger than 405 ha (1000 acres) in the West, and larger than 202 ha (500 acres) in the East, respectively, between 1984 and 2016.”
From Burned forests impact water supplies (2018) · cites this paper as [27]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Photogrammetric Engineering and Remote Sensing
Nicol, J., King, B., Quattrochi, D., Dowman, I. J., Ehlers, M., & Xiaoli, D. (2007) · UCL Discovery (University College London) · Cited by 9,325
Development of a 2001 National Land-Cover Database for the United States
Homer, C. G., Huang, C., Yang, L., Wylie, B. K., & Coan, M. J. (2004) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.70.7.829 · Cited by 1,567
Miller, J. D., & Thode, A. E. (2007) · Remote Sensing of Environment · doi:10.1016/j.rse.2006.12.006 · Cited by 1,444
Remote sensing techniques to assess active fire characteristics and post-fire effects
Lentile, L. B., Holden, Z. A., Smith, A. M. S., Falkowski, M. J., Hudak, A. T., Morgan, P., Lewis, S. A., Gessler, P. E., & Benson, N. (2006) · International Journal of Wildland Fire · doi:10.1071/wf05097 · Cited by 1,002
International Journal of Remote Sensing
(2011) · International Journal of Remote Sensing · doi:10.1080/01431161.2012.638042 · Cited by 1,000
Mapping burns and natural reforestation using thematic Mapper data
García, M. J. L., & Caselles, V. (1991) · Geocarto International · doi:10.1080/10106049109354290 · Cited by 743
FEDERAL FOREST‐FIRE POLICY IN THE UNITED STATES
Stephens, S. L., & Ruth, L. W. (2005) · Ecological Applications · doi:10.1890/04-0545 · Cited by 584
Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data
Cocke, A. E., Fulé, P. Z., & Crouse, J. E. (2005) · International Journal of Wildland Fire · doi:10.1071/wf04010 · Cited by 498
Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity
van Wagtendonk, J. W., Root, R. R., & Key, C. H. (2004) · Remote Sensing of Environment · doi:10.1016/j.rse.2003.12.015 · Cited by 467
A change detection experiment using vegetation indices.
Lyon, J. G., Yuan, D., Lunetta, R. S., & Elvidge, C. D. (1998) · Cited by 462
Flagged first, then by citations
Research works printed but not linked: 3
- Gmelin, M., and K. Brewer. 2002. Operational change detection-based fire severity mapping using Landsat TM data. P. 1–8 in Rapid delivery of remote sensing products [electronic resource]: proceedings of the Ninth Forest Service Remote Sensing Applications Conference, Greer, J. (ed.). ASPRS, San Diego, California.
- Key, C.H., and N.C. Benson. 2002. Measuring and remote sensing of burn severity, U.S. Geological Survey wildland fire workshop.
- Thode, A. 2005. Quantifying the fire regime attributes of severity and spatial complexity using field and imagery data, PhD diss, University of California, Davis, California.
Cited by
Sorted by citations
Items 101–200 of 1,000
Kane, V. R., North, M. P., Lutz, J. A., Churchill, D. J., Roberts, S. L., Smith, D. F., McGaughey, R. J., Kane, J. T., & Brooks, M. L. (2013) · Remote Sensing of Environment · doi:10.1016/j.rse.2013.07.041 · Cited by 158
Cattau, M. E., Wessman, C. A., Mahood, A. L., & Balch, J. K. (2020) · Global Ecology and Biogeography · doi:10.1111/geb.13058 · Cited by 154
Anthropogenic climate change impacts exacerbate summer forest fires in California
Turco, M., Abatzoglou, J. T., Herrera, S., Zhuang, Y., Jerez, S., Lucas, D. D., AghaKouchak, A., & Cvijanović, I. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2213815120 · Cited by 151
Human and biophysical influences on fire occurrence in the United States
Hawbaker, T. J., Radeloff, V. C., Stewart, S. I., Hammer, R. B., Keuler, N. S., & Clayton, M. K. (2013) · Ecological Applications · doi:10.1890/12-1816.1 · Cited by 143
Giving Ecological Meaning to Satellite-Derived Fire Severity Metrics across North American Forests
Parks, S. A., Holsinger, L. M., Koontz, M. J., Collins, L., Whitman, E., Parisien, M., Loehman, R. A., Barnes, J. L., Bourdon, J.-F., Boucher, J., et al. (2019) · Remote Sensing · doi:10.3390/rs11141735 · Cited by 152
Weather, fuels, and topography impede wildland fire spread in western US landscapes
Holsinger, L. M., Parks, S. A., & Miller, C. (2016) · Forest Ecology and Management · doi:10.1016/j.foreco.2016.08.035 · Cited by 167
Crockett, J. L., & Westerling, A. L. (2017) · Journal of Climate · doi:10.1175/jcli-d-17-0254.1 · Cited by 145
Human-Related Ignitions Increase the Number of Large Wildfires across U.S. Ecoregions
Nagy, R. C., Fusco, E. J., Bradley, B. A., Abatzoglou, J. T., & Balch, J. K. (2018) · Fire · doi:10.3390/fire1010004 · Cited by 153
The role of remote sensing in process-scaling studies of managed forest ecosystems
Masek, J. G., Hayes, D. J., Hughes, M. J., Healey, S. P., & Turner, D. P. (2015) · Forest Ecology and Management · doi:10.1016/j.foreco.2015.05.032 · Cited by 147
Picotte, J. J., Bhattarai, K., Howard, D., Lecker, J., Epting, J., Quayle, B., Benson, N., & Nelson, K. J. (2020) · Fire Ecology · doi:10.1186/s42408-020-00076-y · Cited by 142
Self-citationKane, V. R., Lutz, J. A., Roberts, S. L., Smith, D. F., McGaughey, R. J., Povak, N. A., & Brooks, M. L. (2012) · Forest Ecology and Management · doi:10.1016/j.foreco.2012.08.044 · Cited by 142
Fairfax, E., & Whittle, A. (2020) · Ecological Applications · doi:10.1002/eap.2225 · Cited by 144
Zhang, F., Chen, J. M., Pan, Y., Birdsey, R. A., Shen, S., Ju, W., & He, L. (2012) · Journal of Geophysical Research Atmospheres · doi:10.1029/2011jg001930 · Cited by 139
Fuel treatments and landform modify landscape patterns of burn severity in an extreme fire event
Prichard, S. J., & Kennedy, M. C. (2013) · Ecological Applications · doi:10.1890/13-0343.1 · Cited by 139
van Leeuwen, W. (2008) · Sensors · doi:10.3390/s8032017 · Cited by 140
Increasing Synchronous Fire Danger in Forests of the Western United States
Abatzoglou, J. T., Juang, C. S., Williams, P., Kolden, C. A., & Westerling, A. L. (2020) · Geophysical Research Letters · doi:10.1029/2020gl091377 · Cited by 145
Remote Sensing of Forest Burnt Area, Burn Severity, and Post-Fire Recovery: A Review
Kurbanov, E. A., Николаевич, В. О., Анатольевич, Л. С., Sha, J., Wang, J., Li, X., Cole, J., Дергунов, Д. М., & Wang, Y. (2022) · Remote Sensing · doi:10.3390/rs14194714 · Cited by 139
Training data requirements for fire severity mapping using Landsat imagery and random forest
Collins, L., McCarthy, G., Mellor, A., Newell, G. R., & Smith, L. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2020.111839 · Cited by 142
Estimation of wildfire size and risk changes due to fuels treatments
Cochrane, M. A., Moran, C. J., Wimberly, M. C., Baer, A. D., Finney, M. A., Beckendorf, K. L., Eidenshink, J., & Zhu, Z. (2012) · International Journal of Wildland Fire · doi:10.1071/wf11079 · Cited by 136
Self-citationKoontz, M. J., North, M. P., Werner, C. M., Fick, S. E., & Latimer, A. M. (2020) · Ecology Letters · doi:10.1111/ele.13447 · Cited by 142
Fang, L., Yang, J., Zu, J., Gui-Cai, L., & Zhang, J. (2015) · Forest Ecology and Management · doi:10.1016/j.foreco.2015.01.011 · Cited by 135
Goodwin, N., & Collett, L. J. (2014) · Remote Sensing of Environment · doi:10.1016/j.rse.2014.03.021 · Cited by 136
Meng, R., Wu, J., Schwager, K., Zhao, F., Dennison, P. E., Cook, B. D., Brewster, K., Green, T. M., & Serbin, S. P. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.01.016 · Cited by 135
O’Connor, C. D., Falk, D. A., Lynch, A. M., & Swetnam, T. W. (2014) · Forest Ecology and Management · doi:10.1016/j.foreco.2014.06.032 · Cited by 137
McRoberts, R. E., Cohen, W. B., Næsset, E., Stehman, S. V., & Tomppo, E. (2010) · Scandinavian Journal of Forest Research · doi:10.1080/02827581.2010.497496 · Cited by 133
Area burned in the western United States is unaffected by recent mountain pine beetle outbreaks
Hart, S. J., Schoennagel, T., Veblen, T. T., & Chapman, T. B. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1424037112 · Cited by 128
Pinto, M. M., Libonati, R., Trigo, R. M., Trigo, I. F., & DaCamara, C. C. (2020) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2019.12.014 · Cited by 137
State‐and‐transition simulation models: a framework for forecasting landscape change
Daniel, C. J., Frid, L., Sleeter, B. M., & Fortin, M. (2016) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12597 · Cited by 128
Previous burns and topography limit and reinforce fire severity in a large wildfire
Harris, L. B., & Taylor, A. H. (2017) · Ecosphere · doi:10.1002/ecs2.2019 · Cited by 135
Spatiotemporal remote sensing of ecosystem change and causation across Alaska
Pastick, N. J., Jorgenson, M. T., Goetz, S. J., Jones, B. M., Wylie, B. K., Minsley, B. J., Genet, H., Knight, J., Swanson, D. K., & Jorgenson, J. C. (2018) · Global Change Biology · doi:10.1111/gcb.14279 · Cited by 132
van Wagtendonk, J. W., van Wagtendonk, K. A., & Thode, A. E. (2012) · Fire Ecology · doi:10.4996/fireecology.0801011 · Cited by 127
Mapping day-of-burning with coarse-resolution satellite fire-detection data
Parks, S. A. (2014) · International Journal of Wildland Fire · doi:10.1071/wf13138 · Cited by 120
Ryan, K. C., & Opperman, T. S. (2013) · Forest Ecology and Management · doi:10.1016/j.foreco.2012.11.003 · Cited by 124
Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem
Assal, T. J., Anderson, P. J., & Sibold, J. S. (2016) · Forest Ecology and Management · doi:10.1016/j.foreco.2016.01.017 · Cited by 120
Kemp, K. B., Higuera, P. E., Morgan, P., & Abatzoglou, J. T. (2019) · Ecosphere · doi:10.1002/ecs2.2568 · Cited by 119
Fire history of the Appalachian region: a review and synthesis
Lafon, C. W., Naito, A. T., Grissino‐Mayer, H. D., Horn, S. P., & Waldrop, T. A. (2017) · doi:10.2737/srs-gtr-219 · Cited by 118
Temporal variability of forest fires in eastern Amazonia
Alencar, A. A. C., Asner, G. P., Knapp, D., & Zarin, D. J. (2011) · Ecological Applications · doi:10.1890/10-1168.1 · Cited by 116
Parks, S. A., Parisien, M., Miller, C., & Dobrowski, S. Z. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099699 · Cited by 118
Boschetti, L., Stehman, S. V., & Roy, D. P. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.09.016 · Cited by 118
Meddens, A. J. H., Kolden, C. A., & Lutz, J. A. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.08.023 · Cited by 124
Arkle, R. S., Pilliod, D. S., Hanser, S. E., Brooks, M. L., Chambers, J. C., Grace, J. B., Knutson, K. C., Pyke, D. A., Welty, J. L., & Wirth, T. A. (2014) · Ecosphere · doi:10.1890/es13-00278.1 · Cited by 116
Harvey, B. J., Donato, D. C., & Turner, M. G. (2016) · Landscape Ecology · doi:10.1007/s10980-016-0408-4 · Cited by 115
Li, F., Zhang, X., Roy, D. P., & Kondragunta, S. (2019) · Atmospheric Environment · doi:10.1016/j.atmosenv.2019.05.017 · Cited by 119
A changing climate is snuffing out post‐fire recovery in montane forests
Rodman, K. C., Veblen, T. T., Battaglia, M. A., Chambers, M. E., Fornwalt, P. J., Holden, Z. A., Kolb, T. E., Ouzts, J., & Rother, M. T. (2020) · Global Ecology and Biogeography · doi:10.1111/geb.13174 · Cited by 122
Zhao, F., Sun, R., Zhong, L., Meng, R., Huang, C., Zeng, X., Wang, M., Li, Y., & Wang, Z. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112822 · Cited by 115
Berner, L. T., Law, B. E., Meddens, A. J. H., & Hicke, J. A. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa6f94 · Cited by 113
Hunter, M. E., & Robles, M. D. (2020) · Forest Ecology and Management · doi:10.1016/j.foreco.2020.118435 · Cited by 119
Lister, A. J., Andersen, H., Frescino, T. S., Gatziolis, D., Healey, S. P., Heath, L. S., Liknes, G. C., McRoberts, R. E., Moisen, G. G., Nelson, M. D., et al. (2020) · Forests · doi:10.3390/f11121364 · Cited by 117
Multi-temporal LiDAR and Landsat quantification of fire-induced changes to forest structure
McCarley, T. R., Kolden, C. A., Vaillant, N. M., Hudak, A. T., Smith, A. M. S., Wing, B. M., Kellogg, B. S., & Kreitler, J. R. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.12.022 · Cited by 112
Four-fold increase in solar forcing on snow in western U.S. burned forests since 1999
Gleason, K. E., McConnell, J. R., Arienzo, M. M., Chellman, N. J., & Calvin, W. M. (2019) · Nature Communications · doi:10.1038/s41467-019-09935-y · Cited by 113
Harvey, B. J., Donato, D., & Turner, M. (2016) · Ecology · doi:10.1002/ecy.1439 · Cited by 107
Carbon stocks of trees killed by bark beetles and wildfire in the western United States
Hicke, J. A., Meddens, A. J. H., Allen, C. D., & Kolden, C. A. (2013) · Environmental Research Letters · doi:10.1088/1748-9326/8/3/035032 · Cited by 111
Climatic influences on interannual variability in regional burn severity across western US forests
Abatzoglou, J. T., Kolden, C. A., Williams, P., Lutz, J. A., & Smith, A. M. S. (2017) · International Journal of Wildland Fire · doi:10.1071/wf16165 · Cited by 116
García-Llamas, P., Suárez‐Seoane, S., Fernández‐Guisuraga, J. M., Fernández‐García, V., Fernández–Manso, A., Quintano, C., Taboada, Á., Marcos, E., & Calvo, L. (2019) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2019.04.006 · Cited by 109
Wildfire disturbance and productivity as drivers of plant species diversity across spatial scales
Burkle, L. A., Myers, J. A., & Belote, R. T. (2015) · Ecosphere · doi:10.1890/es15-00438.1 · Cited by 106
Near‐future forest vulnerability to drought and fire varies across the western United States
Buotte, P. C., Levis, S., Law, B. E., Hudiburg, T. W., Rupp, D. E., & Kent, J. (2018) · Global Change Biology · doi:10.1111/gcb.14490 · Cited by 109
The fastest-growing and most destructive fires in the US (2001 to 2020)
Balch, J. K., Iglesias, V., Mahood, A. L., Cook, M., do Amaral, C. H., DeCastro, A. L., Leyk, S., McIntosh, T. L., Nagy, R. C., Denis, L. A. S., et al. (2024) · Science · doi:10.1126/science.adk5737 · Cited by 124
Loehman, R. A., Reinhardt, E. D., & Riley, K. L. (2013) · Forest Ecology and Management · doi:10.1016/j.foreco.2013.04.014 · Cited by 119
Haffey, C., Sisk, T. D., Allen, C. D., Thode, A. E., & Margolis, E. Q. (2018) · Fire Ecology · doi:10.4996/fireecology.140114316 · Cited by 108
The missing fire: quantifying human exclusion of wildfire in Pacific Northwest forests, USA
Haugo, R. D., Kellogg, B. S., Cansler, C., Kolden, C., Kemp, K., Robertson, J., Metlen, K., Vaillant, N., & Restaino, C. M. (2019) · Ecosphere · doi:10.1002/ecs2.2702 · Cited by 99
Serra-Diaz, J. M., Maxwell, C. J., Lucash, M. S., Scheller, R. M., Laflower, D. M., Miller, A. D., Tepley, A. J., Epstein, H. E., Anderson‐Teixeira, K. J., & Thompson, J. R. (2018) · Scientific Reports · doi:10.1038/s41598-018-24642-2 · Cited by 109
Sleeter, B. M., Liu, J., Daniel, C. J., Rayfield, B., Sherba, J. T., Hawbaker, T. J., Zhu, Z., Selmants, P. C., & Loveland, T. R. (2018) · Environmental Research Letters · doi:10.1088/1748-9326/aab540 · Cited by 105
Self-citationUnfamiliar Territory: Emerging Themes for Ecological Drought Research and Management
Crausbay, S. D., Betancourt, J. L., Bradford, J. B., Cartwright, J., Dennison, W. C., Dunham, J. B., Enquist, C. A. F., Frazier, A. G., Hall, K. R., Littell, J. S., et al. (2020) · One Earth · doi:10.1016/j.oneear.2020.08.019 · Cited by 106
Repeated fires reduce plant diversity in low‐elevation Wyoming big sagebrush ecosystems (1984–2014)
Mahood, A. L., & Balch, J. K. (2019) · Ecosphere · doi:10.1002/ecs2.2591 · Cited by 99
Siberian taiga and tundra fire regimes from 2001–2020
Talucci, A. C., Loranty, M. M., & Alexander, H. D. (2022) · Environmental Research Letters · doi:10.1088/1748-9326/ac3f07 · Cited by 102
Liu, Z., & Wimberly, M. C. (2015) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2015.10.093 · Cited by 96
Chen, Y., Hantson, S., Andela, N., Coffield, S., Graff, C. A., Morton, D. C., Ott, L. E., Foufoula‐Georgiou, E., Smyth, P., Goulden, M. L., et al. (2022) · Scientific Data · doi:10.1038/s41597-022-01343-0 · Cited by 98
Wine, M. L., & Cadol, D. (2016) · Environmental Research Letters · doi:10.1088/1748-9326/11/8/085006 · Cited by 96
Wildland fire emissions, carbon, and climate: U.S. emissions inventories
Larkin, N. K., Raffuse, S. M., & Strand, T. (2013) · Forest Ecology and Management · doi:10.1016/j.foreco.2013.09.012 · Cited by 96
Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR
Reddy, A. D., Hawbaker, T. J., Wurster, F. C., Zhu, Z., Ward, S., Newcomb, D., & Murray, R. (2015) · Remote Sensing of Environment · doi:10.1016/j.rse.2015.09.017 · Cited by 101
Self-citationSaxe, S., Hogue, T. S., & Hay, L. E. (2018) · Hydrology and earth system sciences · doi:10.5194/hess-22-1221-2018 · Cited by 104
Vegetation type conversion in the US Southwest: frontline observations and management responses
Guiterman, C. H., Gregg, R. M., Marshall, L. A. E., Beckmann, J. J., van Mantgem, P. J., Falk, D. A., Keeley, J. E., Caprio, A. C., Coop, J. D., Fornwalt, P. J., et al. (2022) · Fire Ecology · doi:10.1186/s42408-022-00131-w · Cited by 98
Veraverbeke, S., Verstraeten, W. W., Lhermitte, S., & Goossens, R. (2010) · International Journal of Wildland Fire · doi:10.1071/wf09069 · Cited by 95
Calibration and Validation of Immediate Post-Fire Satellite-Derived Data to Three Severity Metrics
Miller, J. D., & Quayle, B. (2015) · Fire Ecology · doi:10.4996/fireecology.1102012 · Cited by 96
Self-citationAssessing fuel treatment effectiveness using satellite imagery and spatial statistics
Wimberly, M. C., Cochrane, M. A., Baer, A. D., & Pabst, K. (2009) · Ecological Applications · doi:10.1890/08-1685.1 · Cited by 95
Repeated wildfires alter forest recovery of mixed-conifer ecosystems.
Stevens-Rumann, C., & Morgan, P. (2016) · Ecological Applications · doi:10.1890/15-1521.1 · Cited by 96
US wildfire potential: a historical view and future projection using high-resolution climate data
Brown, E. K., Wang, J., & Feng, Y. W. (2020) · Environmental Research Letters · doi:10.1088/1748-9326/aba868 · Cited by 99
Forecasting the Frequency and Magnitude of Postfire Debris Flows Across Southern California
Kean, J. W., & Staley, D. M. (2021) · Earth s Future · doi:10.1029/2020ef001735 · Cited by 96
Human and infrastructure exposure to large wildfires in the United States
Rad, A. M., Abatzoglou, J. T., Kreitler, J. R., Alizadeh, M. R., AghaKouchak, A., Hudyma, N., Nauslar, N. J., & Sadegh, M. (2023) · Nature Sustainability · doi:10.1038/s41893-023-01163-z · Cited by 97
Boreal Shield forest disturbance and recovery trends using Landsat time series
Frazier, R. J., Coops, N. C., & Wulder, M. A. (2015) · Remote Sensing of Environment · doi:10.1016/j.rse.2015.09.015 · Cited by 91
Keyser, A. R., & Westerling, A. L. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa6b10 · Cited by 98
Meigs, G. W., Kennedy, R. E., Gray, A. N., & Gregory, M. J. (2014) · Forest Ecology and Management · doi:10.1016/j.foreco.2014.11.030 · Cited by 94
Harris, S. L., Veraverbeke, S., & Hook, S. J. (2011) · Remote Sensing · doi:10.3390/rs3112403 · Cited by 98
Wildland fire limits subsequent fire occurrence
Parks, S. A., Miller, C., Holsinger, L. M., Baggett, L. S., & Bird, B. J. (2015) · International Journal of Wildland Fire · doi:10.1071/wf15107 · Cited by 92
Global Forest Monitoring from Earth Observation
Achard, F., & Hansen, M. C. (2016) · CRC Press eBooks · doi:10.1201/b13040 · Cited by 93
Romme, W. H., Whitby, T. G., Tinker, D. B., & Turner, M. G. (2016) · Ecological Monographs · doi:10.1002/ecm.1220 · Cited by 89
Contributions of fire refugia to resilient ponderosa pine and dry mixed‐conifer forest landscapes
Coop, J. D., DeLory, T. J., Downing, W. M., Haire, S. L., Krawchuk, M. A., Miller, C., Parisien, M., & Walker, R. B. (2019) · Ecosphere · doi:10.1002/ecs2.2809 · Cited by 91
Miesel, J., Reiner, A. L., Ewell, C. M., Maestrini, B., & Dickinson, M. B. (2018) · Frontiers in Earth Science · doi:10.3389/feart.2018.00041 · Cited by 92
Switching on the Big Burn of 2017
Balch, J. K., Schoennagel, T., Williams, A. P., Abatzoglou, J. T., Cattau, M. E., Mietkiewicz, N. P., & St. Denis, L. A. (2018) · Fire · doi:10.3390/fire1010017 · Cited by 88
Drought triggers and sustains overnight fires in North America
Luo, K., Wang, X., Jong, M. C. D., & Flannigan, M. (2024) · Nature · doi:10.1038/s41586-024-07028-5 · Cited by 92
Assessing intra-annual vegetation regrowth after fire using the pixel based regeneration index
Lhermitte, S., Verbesselt, J., Verstraeten, W. W., Veraverbeke, S., & Coppin, P. R. (2010) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2010.08.004 · Cited by 88
Shuai, Y., Masek, J. G., Feng Gao, A., Schaaf, C., & He, T. (2014) · Remote Sensing of Environment · doi:10.1016/j.rse.2014.07.009 · Cited by 91
Varner, J. M., Hood, S. M., Aubrey, D. P., Yedinak, K. M., Hiers, J. K., Jolly, W. M., Shearman, T. M., McDaniel, J. K., O’Brien, J. J., & Rowell, E. M. (2021) · New Phytologist · doi:10.1111/nph.17539 · Cited by 87
Previous wildfires and management treatments moderate subsequent fire severity
Cansler, C. A., Kane, V. R., Hessburg, P. F., Kane, J. T., Jeronimo, S. M. A., Lutz, J. A., Povak, N. A., Churchill, D. J., & Larson, A. J. (2021) · Forest Ecology and Management · doi:10.1016/j.foreco.2021.119764 · Cited by 88
Fire Frequency, Area Burned, and Severity: A Quantitative Approach to Defining a Normal Fire Year
Lutz, J. A., Key, C. H., Kolden, C. A., Kane, J. T., & van Wagtendonk, J. W. (2011) · Fire Ecology · doi:10.4996/fireecology.0702051 · Cited by 88
Turner, M. G., Whitby, T. G., Tinker, D. B., & Romme, W. H. (2016) · Ecology · doi:10.1890/15-1585.1 · Cited by 87
Fulé, P. Z., Swetnam, T. W., Brown, P. M., Falk, D. A., Peterson, D. L., Allen, C. D., Aplet, G. H., Battaglia, M. A., Binkley, D., Farris, C. A., et al. (2013) · Global Ecology and Biogeography · doi:10.1111/geb.12136 · Cited by 86
Murphy, B. P., Czuba, J. A., & Belmont, P. (2019) · Earth Surface Processes and Landforms · doi:10.1002/esp.4635 · Cited by 86
Rodman, K. C., Veblen, T. T., Chapman, T. B., Rother, M. T., Wion, A. P., & Redmond, M. D. (2019) · Ecological Applications · doi:10.1002/eap.2001 · Cited by 86
Towards a new paradigm in fire severity research using dose–response experiments
Smith, A. M. S., Sparks, A. M., Kolden, C. A., Abatzoglou, J. T., Talhelm, A. F., Johnson, D. M., Boschetti, L., Lutz, J. A., Apostol, K. G., Yedinak, K. M., et al. (2016) · International Journal of Wildland Fire · doi:10.1071/wf15130 · Cited by 85
Metadata
- Authors
- Eidenshink, J., Schwind, B., Brewer, K., Zhu, Z.-L., Quayle, B., & Howard, S.
- Affiliations
- United States Geological Survey (US)
- US Forest Service (US)
- Corresponding author
- Eidenshink, Jeff
- ORCID
- Howard, Stephen
- Venue
- Fire Ecology
- Published
- 2007-06
- Volume
- 3
- Issue
- 1
- Pages
- 3-21
- ISSN
- 1933-9747 (ISSN-L)
- OpenAlex
- W2138800506
- Cited by
- 1,423
- References
- 31
- Citations by year
- 2026: 110 · 2025: 118 · 2024: 138 · 2023: 101 · 2022: 123 · 2021: 96 · 2020: 111 · 2019: 112 · 2018: 100 · 2017: 73 · 2016: 65 · 2015: 77 · 2014: 64 · 2013: 42 · 2012: 42
- FWCI
- 6.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Fire Ecology (publishedVersion, cc-by)
- Funders
- U.S. Department of Agriculture
- U.S. Forest Service
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
- Health Sciences › Medicine › Surgery › Burn Injury Management and Outcomes
- Keywords
- burn severity, Monitoring Trends in Burn Severity, National Fire Plan, forest fires, dNBR, Landsat, fire policy, fire risk assessment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review