Keywords
Prescribed fire, Aerial images, FARSITE Model, Fireline estimation
Start Date
16-9-2020 1:20 PM
End Date
16-9-2020 1:40 PM
Abstract
The study of fire progression requires a detailed characterization of several components, such as, the location of the ignition, the slope of the terrain, fuel properties and weather conditions. Usually, the fire progression is estimated using numerical models, but as the input variables in wildfires and even in experimental ones are highly uncertain, the estimation of the fireline progression is also uncertain. The main objective of this work was to study the fireline progression using two different approaches. The first approach is based on a modelling tool – FARSITE – which estimates fireline progression using topography, fuel characteristics and weather information. In the second approach, we use image processing techniques to extract data about the fireline progression from aerial images captured by an Unmanned Aerial Vehicle (UAV) equipped with an RGB camera. Both approaches were tested during a prescribed fire in the north of Portugal and the results were processed and evaluated using a geographical information system. The results show that FARSITE overestimates the burnt area in comparison with the data extracted from the aerial images. On the other hand, the segmentation of the fire in the aerial images was challenging, since the fireline was not visible in several framed due to heavy smoke together with the camera angles and flight limitations. This first attempt to compare both approaches also allowed to identify issues and improvements to be considered in the design of future experimental campaigns. These include guidelines to improve the spatiotemporal representation of the fireline propagation in both approaches, as well as to establish the first steps towards a new methodology to measure the fireline propagation during prescribed burns.
Fireline Propagation: How well does the FARSITE model compare with observations from aerial images?
The study of fire progression requires a detailed characterization of several components, such as, the location of the ignition, the slope of the terrain, fuel properties and weather conditions. Usually, the fire progression is estimated using numerical models, but as the input variables in wildfires and even in experimental ones are highly uncertain, the estimation of the fireline progression is also uncertain. The main objective of this work was to study the fireline progression using two different approaches. The first approach is based on a modelling tool – FARSITE – which estimates fireline progression using topography, fuel characteristics and weather information. In the second approach, we use image processing techniques to extract data about the fireline progression from aerial images captured by an Unmanned Aerial Vehicle (UAV) equipped with an RGB camera. Both approaches were tested during a prescribed fire in the north of Portugal and the results were processed and evaluated using a geographical information system. The results show that FARSITE overestimates the burnt area in comparison with the data extracted from the aerial images. On the other hand, the segmentation of the fire in the aerial images was challenging, since the fireline was not visible in several framed due to heavy smoke together with the camera angles and flight limitations. This first attempt to compare both approaches also allowed to identify issues and improvements to be considered in the design of future experimental campaigns. These include guidelines to improve the spatiotemporal representation of the fireline propagation in both approaches, as well as to establish the first steps towards a new methodology to measure the fireline propagation during prescribed burns.
Stream and Session
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