Detection and growth of an Alaskan forest fire using GOES-9 3.9 um imagery
Document Type: Journal Article
Author(s): Gary L. Hufford; Herbert L. Kelley; Raymond K. Moore; Jeffrey S. Cotterman
Publication Year: 1999

Cataloging Information

  • automated technique
  • Betula spp.
  • blowup
  • climatology
  • coniferous forests
  • crown fires
  • drought
  • fire case histories
  • fire danger rating
  • fire detection
  • fire growth
  • fire intensity
  • fire suppression
  • forest fires
  • forest management
  • GIS - geographic information system
  • hot spots
  • management tool
  • Miller's Reach Fire
  • mop up
  • Picea glauca
  • Picea mariana
  • rate of spread
  • remote sensing
  • statistical analysis
  • temperature
  • wilderness fire management
  • wildfires
Record Maintained By:
Record Last Modified: June 1, 2018
FRAMES Record Number: 4353
Tall Timbers Record Number: 17312
TTRS Location Status: In-file
TTRS Call Number: Journals-I
TTRS Abstract Status: Okay, Fair use, Reproduced by permission

This bibliographic record was either created or modified by the Tall Timbers Research Station and Land Conservancy and is provided without charge to promote research and education in Fire Ecology. The E.V. Komarek Fire Ecology Database is the intellectual property of the Tall Timbers Research Station and Land Conservancy.


The utility of the new GOES-9 satellite 3.9 um channel to monitor wildfires and their subsequent changes in growth and intensity in Alaska is examined. The June, 1996 Miller's Reach forest fire is presented as a case study. Eighteen hours of sequential imagery coincident to the initiation and early stages of the fire are analyzed for hot spots. The dramatic response of the 3.9 um channel to sub-pixel hot spots and the ability to access the data every 15 minutes makes the channel an effective tool to support forest fire management on wild-fires in high latitudes to at least 61 degrees N. In the case of Miller's Reach, the fire was detected when it was less than 200 hectares in size. Changes in fire growth and intensity were also observed. An automated technique for decision makers which classifies hot spots without requiring image interpretation is proposed.

Online Link(s):
Hufford, Gary L.; Kelley, Herbert L.; Moore, Raymond K.; Cotterman, Jeffrey S. 1999. Detection and growth of an Alaskan forest fire using GOES-9 3.9 um imagery. International Journal of Wildland Fire 9(2):129-136.