231
Views
1
CrossRef citations to date
0
Altmetric
Original Articles

Remote optical observation of biomass burning: A feasibility and experimental case study with the SIM.GA hyperspectral system

, , &
Pages 6241-6259 | Received 24 Nov 2009, Accepted 08 Jul 2010, Published online: 22 Jul 2011
 

Abstract

In this article, the feasibility of detecting fire fronts from biomass burning, using the HYPER/SIM.GA system (Galileo Avionica Multisensor Hyperspectral System), has been tested. This system includes two hyperspectral optical heads, in the Visible and near-infrared (VNIR) and Short-wave infrared (SWIR) bands, providing complete spectral coverage from the visible (0.4 μm) to the thermal infrared (24 μm) bands.

We revised the strategies to detect the fire front from hyperspectral data. We found that the radiance emitted by potassium atoms (K) at 766.5 and 769.9 nm, electronically excited during biomass burning, can be usefully exploited to detect the fire front. A study has been made, in order to verify the sensitivity of this feature to biomass composition, fire temperature and visibility. A typical scenario, in which a wildland fire takes place, has been simulated. Simulated data have been compared with real data, confirming the feasibility of this approach to detect the fire front.

This approach is advantageous, both from the economic and operative viewpoints, with respect to classical remote sensing for fire detection, usually based on the Planck emission at thermal bands.

Acknowledgements

Authors wish to acknowledge the support of Fabrizio Aversa, Antonio Bartoloni and Paolo Colandrea at Kell (Rome), and Michele Dami and Demetrio Labate at Galileo Avionica (Florence). This article is dedicated to Fabrizio Aversa, who recently passed away.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 689.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.