Forest fire detection based on Gaussian field analysis

Florent Lafarge (1) , Xavier Descombes (1) , Josiane Zerubia (1)

1 ARIANA - Inverse problems in earth monitoring

The Thermical InfraRed (TIR) channel contains wave lengths sensitive to the emission of heat. The forest fires can be characterized by intensity peaks on TIR images. We present a fully automatic method of forest fi re detection from TIR satellite images based on the random fi eld theory. First, preprocessing is used to model the image as a realization of a Gaussian fi eld which presents interesting properties. The fire areas which are supposed to be a minority are considered as anomalies of that fi eld. We present a statistical analysis of Gaussian field to determine a degree of belonging of a cluster to the image background (i.e. a realization of a Gaussian fi eld). We then extend this application to the estimation of the fi re propagation direction.

Mots clés: forest fire; rare event; Random field; fire detection; high resolution image

Domaines: Mathématique discrète [cs.DM]

Florent Lafarge, Xavier Descombes, Josiane Zerubia. Forest fire detection based on Gaussian field analysis. European Signal Processing Conference (EUSIPCO), Sep 2007, Poznan, Poland. ⟨hal-00781765⟩