Geographic Information Systems Stack Exchange is a question and answer site for cartographers, geographers and GIS professionals. Join them; it only takes a minute:

Sign up
Here's how it works:
  1. Anybody can ask a question
  2. Anybody can answer
  3. The best answers are voted up and rise to the top

I am looking for the best band combination with Landsat 5 imagery to detect fire scars.

share|improve this question
up vote 6 down vote accepted

This varies greatly on the characteristics of the scene. Fire scar mapping studies using Landsat-5 TM have used the following three band combinations:

  • Spain: Bands 4, 5, 7

CHUVIECO, E., and CONGALTON, R., 1988, Mapping and inventory of forest fires from digital processing of TM data. Geocarto International, 4, 41–53.

  • Amazonia: Bands 3, 4, 5

PEREIRA, M. C., and SETZER, A. W., 1993, Spectral characteristics of fire scars in Landsat-5 TM images of Amazonia. International Journal of Remote Sensing, 14, 2061–2078.

  • Greece: Bands 4, 7, 1 or Bands 4, 7, 2

KOUTSIAS, N., and KARTERIS, M., 1998, Logistic regression modeling of multitemporal Thematic Mapper data for burned area mapping. International Journal of Remote Sensing, 19, 3499–3514.

KOUTSIAS, N., and KARTERIS, M., 2000, Burned area mapping using logistic regression modeling of a single post-fire Landsat-5 Thematic Mapper image. International Journal of Remote Sensing, 21, 673–687.

share|improve this answer
Just adding a few more words on the subject: According to Koutsias and Karteris (1998, 2000), the spectral channels TM 4 and TM 7 provide, in both multitemporal and unitemporal data sets, the highest and second best burned area detection ability respectively. – Nikos Alexandris Jul 28 '14 at 19:45
Based on single post-fire data sets, Pu and Gong (2004) also report that TM 4 and TM 7 are the best burned area discriminators. Among the visible channels, TM 1 and TM 2 were identified as the most useful in the multitemporal and the unitemporal studies respectively. | Pu, R. and Gong, P. (2004). Determination of burnt scars using logistic regression and neural network techniques from a single post-fire Landsat 7 ETM+ image. Photogrammetric Engineering and Remote Sensing, 70(7):841–850. – Nikos Alexandris Jul 28 '14 at 19:47

Another option if you have pre and post fire scenes is to use the differenced Normalised Burn Ratio (Key and Benson 1999), which really makes fire scars stand out.

dNBR is calculated as:

NBR = (R4-R7) / (R4+R7)

dNBR = NBRprefire - NBRpostfire

Where: RN = reflectance (not raw digital numbers) of Landsat 5 TM band 4 or 7.

share|improve this answer
+1 Indices are a very good method for visualizing features of interest and are useful in analysis. – Aaron Jul 28 '14 at 3:50

Your Answer


By posting your answer, you agree to the privacy policy and terms of service.

Not the answer you're looking for? Browse other questions tagged or ask your own question.