Abstract

To pursue the development and validation of coupled fire-atmosphere models, the wildland fire modeling community needs validation data sets with scenarios where fire-induced winds influence fire front behavior, and with high temporal and spatial resolution. Helicopter-borne infrared thermal cameras have the potential to monitor landscape-scale wildland fires at a high resolution during experimental burns. To extract valuable information from those observations, three-step image processing is required: (a) Orthorectification to warp raw images on a fixed coordinate system grid, (b) segmentation to delineate the fire front location out of the orthorectified images, and (c) computation of fire behavior metrics such as the rate of spread from the time-evolving fire front location. This work is dedicated to the first orthorectification step, and presents a series of algorithms that are designed to process handheld helicopter-borne thermal images collected during savannah experimental burns. The novelty in the approach lies on its recursive design, which does not require the presence of fixed ground control points, hence relaxing the constraint on field of view coverage and helping the acquisition of high-frequency observations. For four burns ranging from four to eight hectares, long-wave and mid infra red images were collected at 1 and 3 Hz, respectively, and orthorectified at a high spatial resolution (<1 m) with an absolute accuracy estimated to be lower than 4 m. Subsequent computation of fire radiative power is discussed with comparison to concurrent space-borne measurements.

Highlights

  • High-resolution active fire monitoring and an associated fire behavior metric are growing needs in the fire science community, in particular in the development of coupled fire-atmosphere systems [1]

  • Estimating orthorectification accuracy is necessary for the computation of several fire behavior metrics that depend on multiple images

  • Due to the lack of ground features that can be identified along the image time series, we propose here to estimate the performance of both Long Wave Infra Red (LWIR) and Middle Infra Red (MIR) image orthorectification using GCPs formed by the corner fires that are present in Skukuza4 and Skukuza6 burns

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Summary

Introduction

High-resolution active fire monitoring and an associated fire behavior metric are growing needs in the fire science community, in particular in the development of coupled fire-atmosphere systems [1]. To support these efforts, we present here a new approach to process Infra Red (IR) observation from landscape-scale (>100 m) experimental fires, helicopter-borne images collected by handheld Long Wave Infra Red (LWIR). To improve mitigation of wildfire effects in fire-prone regions, fire-atmosphere coupled systems have been developed and are intended to become operational [7] These coupled systems include CAWFE [8], WRF-SFIRE [9,10], and MesoNH-ForeFire [11,12].

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