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Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR)

Miller, Jay D., Thode, Andrea E.·2007·Remote Sensing of Environment
DOI 10.1016/j.rse.2006.12.006
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Research works printed but not linked: 24

  1. Brewer, 2005, Classifying and mapping wildfire severity: A comparison of methods, Photogrammetric Engineering and Remote Sensing, 71, 1311, 10.14358/PERS.71.11.1311 · DOI · Paper page
  2. Chander, 2003, Revised Landsat 5 TM radiometric calibration procedures, and postcalibration dynamic ranges, IEEE Transactions on Geoscience and Remote Sensing, 41, 2674, 10.1109/TGRS.2003.818464 · DOI · Paper page
  3. Cocke, 2005, Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data, International Journal of Wildland Fire, 14, 189, 10.1071/WF04010 · DOI · Paper page
  4. Collins, 1996, An assessment of several linear change detection techniques for mapping forest mortality using multitemporal Landsat TM data, Remote Sensing of Environment, 56, 66, 10.1016/0034-4257(95)00233-2 · DOI
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  6. Ekstrand, 1994, Assessment of forest damage with Landsat TM: Correction for varying forest stand characteristics, Remote Sensing of Environment, 47, 291, 10.1016/0034-4257(94)90097-3 · doi:10.1016/0034-4257(94)90097-3
  7. Elvidge, 1990, Visible and near infrared reflectance characteristics of dry plant materials, International Journal of Remote Sensing, 11, 1775, 10.1080/01431169008955129 · doi:10.1080/01431169008955129
  8. Epting, 2005, Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+, Remote Sensing of Environment, 96, 328, 10.1016/j.rse.2005.03.002 · DOI · Paper page
  9. Franklin, 2002, Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas, Progress in Physical Geography, 26, 173, 10.1191/0309133302pp332ra · DOI
  10. Jakubauskas, 1990, Assessment of vegetation change in a fire-altered forest landscape, Photogrammetric Engineering and Remote Sensing, 56, 371
  11. Jia, 2006, Assessing spatial patterns of forest fuel using AVIRIS data, Remote Sensing of Environment, 102, 318, 10.1016/j.rse.2006.02.025 · DOI
  12. Kokaly, R. F., Rockwell, B. W., Hiare, S. L., & King, T. V. V. (in press). 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.
  13. Lopez Garcia, 1991, Mapping burns and natural reforestation using Thematic Mapper data, Geocarto International, 1, 31, 10.1080/10106049109354290 · DOI · Paper page
  14. Lyon, 1998, A change detection experiment using vegetation indices, Photogrammetric Engineering and Remote Sensing, 64, 143
  15. Miller, 2002, Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data, Remote Sensing of Environment, 82, 481, 10.1016/S0034-4257(02)00071-8 · DOI · Paper page
  16. Nelson, 1983, Detecting forest canopy change due to insect activity using Landsat MSS, Photogrammetric Engineering and Remote Sensing, 49, 1303
  17. Singh, 1989, Digital change detection techniques using remotely-sensed data, International Journal of Remote Sensing, 10, 989, 10.1080/01431168908903939 · DOI · Paper page
  18. Strahler, 1981, Stratification of natural vegetation for forest and rangeland inventory using Landsat digital imagery and collateral data, International Journal of Remote Sensing, 2, 15, 10.1080/01431168108948338 · doi:10.1080/01431168108948338
  19. Thode, A.E. (2005). Quantifying the Fire Regime Attributes of Severity and Spatial Complexity Using Field and Imagery Data. PhD Dissertation, University of California, Davis, CA.
  20. Tucker, 1986, Satellite remote-sensing of primary production, International Journal of Remote Sensing, 7, 1395, 10.1080/01431168608948944 · DOI · Paper page
  21. Turner, 1998, Factors influencing succession: Lessons from large, infrequent natural disturbances, Ecosystems, 1, 511, 10.1007/s100219900047 · DOI · Paper page
  22. van Wagtendonk, 2004, Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity, Remote Sensing of Environment, 92, 397, 10.1016/j.rse.2003.12.015 · DOI · Paper page
  23. Vogelmann, 1988, Assessing forest damage in high-elevation coniferous forests in Vermont and New-Hampshire using Thematic Mapper data, Remote Sensing of Environment, 24, 227, 10.1016/0034-4257(88)90027-2 · doi:10.1016/0034-4257(88)90027-2
  24. White, 1996, Remote sensing of forest fire severity and vegetation recovery, International Journal of Wildland Fire, 6, 125, 10.1071/WF9960125 · DOI · Paper page

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Metadata

Authors
Miller, J. D., & Thode, A. E.
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2007-07
Volume
109
Issue
1
Pages
66-80
ISSN
0034-4257 (ISSN-L)
DOI
10.1016/j.rse.2006.12.006
OpenAlex
W2144230836
Cited by
1,431
References
0
FWCI
20.66
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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CoChat. (2026). Citation check: Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). https://app.cochat.ai/papers/10.1016/j.rse.2006.12.006
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Miller, J. D., & Thode, A. E. (2007). Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2006.12.006

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.