Determining the minimum sampling frequency for ground measurements of burn severity
Alexander W. Holmes A C , Christoph Rüdiger A , Sarah Harris B and Nigel Tapper BA Department of Civil Engineering, 23 College Walk, Monash University, Vic. 3800, Australia.
B School of Earth, Atmosphere and Environment, 9 Rainforest Walk, Monash University, Vic. 3800, Australia.
C Corresponding author. Email: alexander.holmes@monash.edu
International Journal of Wildland Fire 27(6) 387-395 https://doi.org/10.1071/WF17055
Submitted: 22 March 2017 Accepted: 17 April 2018 Published: 4 June 2018
Abstract
Understanding burn severity is essential to provide an overview of the precursory conditions leading to fires as well as understanding the constraints placed on fire management services when mitigating their effects. Determining the minimum sampling frequency for ground measurements is not only essential for accurately assessing burn severity, but also for fire managers to better allocate resources and reduce the time and costs associated with sampling. In this study, field sampling methods for assessing burn severity are analysed statistically for 10 burn sites across Victoria, Australia, with varying spatial extents, topography and vegetation. Random and transect sampling methods are compared against each other using a Monte Carlo simulation to determine the minimum sample size needed for a difference of 0.02 (2%) in the severity classes proportions relative to the population proportions. We show that, on average, transect sampling requires a sampling rate of 3.16% compared with 0.59% for random sampling. We also find that sites smaller than 400 ha require a sampling rate of between 1.4 and 2.8 times that of sites larger than 400 ha to achieve the same error. The information obtained from this study will assist fire managers to better allocate resources for assessing burn severity.
Additional keywords: fire, Monte Carlo, sample size, vegetation.
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