'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
In this study, we show how different spectral channels
of NOAA-AVHRR acquired data can be used to produce
a synthetized signal aimed at helping the characterization of
plumes associated to fire events. The synthetized signal is
computed using a reconstruction formula in the multifractal
microcanonical formalism (herein referred to as MMF). The
MMF is a recent development in the analysis of complex signals,
well adapted to the study of turbulent acquired data, for instance
geophysical fluids. It allows the computation, at each point of the
signal’s domain, of a singularity exponent, characteristic of the
scale behaviour of the signal around that point; singularity exponents
provide information about the strengths of the transitions
inside a signal, and they are related to the multifractal hierarchy
associated to structure functions in Fully Developped Turbulence
(FDT). In the MMF, it is possible to reconstruct a turbulent
signal from the manifold of most singular exponents. We make
use of this property by computing supergeometric structures from
a thermal infrared channel in NOAA-AVHRR acquired data,
and we use the signal’s gradient coming from other channels to
reconstruct a signal in which plume pixels are easier to detect.
This methodology is based on the turbulent properties of the
plume accessible from the thermal infrared band; the algorithm
is detailed and applied on a specific example, showing a new
spatially-based method for helping the determination of plume
pixels in NOAA-AVHRR data.JRC.H.6-Spatial data infrastructure