Satellite detection limitations of sub-canopy smouldering wildfires in the north american boreal forest

Joshua M. Johnston*, Lynn M. Johnston, Martin J. Wooster, Alison Brookes, Colin McFayden, Alan S. Cantin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

We develop a simulation model for prediction of forest canopy interception of upwelling fire radiated energy from sub-canopy smouldering vegetation fires. We apply this model spatially across the North American boreal forest in order to map minimum detectable sub-canopy smouldering fire size for three satellite fire detection systems (sensor and algorithm), broadly representative of the Moderate Resolution Imaging Spectroradiometer (MODIS), Sea and Land Surface Temperature Radiometer (SLSTR) and Visible Infrared Imaging Radiometer Suite (VIIRS). We evaluate our results according to fire management requirements for “early detection” of wildland fires. In comparison to the historic fire archive (Canadian National Fire Database, 1980–2017), satellite data with a 1000 m pixel size used with an algorithm having a minimum MWIR channel BT elevation threshold of 5 and 3 K above background (e.g., MODIS or SLSTR) proves incapable of providing a sub-0.2 ha smouldering fire detection 70% and 45% of the time respectively, even assuming that the sensor overpassed the relevant location within the correct time window. By contrast, reducing the pixel area by an order of magnitude (e.g., 375 m pixels of VIIRS) and using a 3.5 K active fire detection threshold offers the potential for successfully detecting all fires when they are still below 0.2 ha. Our results represent a ‘theoretical best performance’ of remote sensing systems to detect sub-canopy smoldering fires early in their lifetime.

Original languageEnglish
Article number28
Pages (from-to)1-16
Number of pages16
JournalFire
Volume1
Issue number2
DOIs
Publication statusPublished - Sept 2018

Keywords

  • Forest canopy
  • Infrared
  • Leaf area index (LAI)
  • Remote sensing
  • Wildfire detection

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