Abstract
In this study, our aim was to model forest fire occurrences caused by lightning using the variable of vegetation water content over six fire-dominant forested natural subregions in Northern Alberta, Canada. We used eight-day composites of surface reflectance data at 500-m spatial resolution, along with historical lightning-caused fire occurrences during the 2005–2016 period, derived from a Moderate Resolution Imaging Spectroradiometer. First, we calculated the normalized difference water index (NDWI) as an indicator of vegetation/fuel water content over the six natural subregions of interest. Then, we generated the subregion-specific annual dynamic median NDWI during the 2005–2012 period, which was assembled into a distinct pattern every year. We plotted the historical lightning-caused fires onto the generated patterns, and used the concept of cumulative frequency to model lightning-caused fire occurrences. Then, we applied this concept to model the cumulative frequencies of lightning-caused fires using the median NDWI values in each natural subregion. By finding the best subregion-specific function (i.e., R2 values over 0.98 for each subregion), we evaluated their performance using an independent subregion-specific lightning-caused fire dataset acquired during the 2013–2016 period. Our analyses revealed strong relationships (i.e., R2 values in the range of 0.92 to 0.98) between the observed and modeled cumulative frequencies of lightning-caused fires at the natural subregion level throughout the validation years. Finally, our results demonstrate the applicability of the proposed method in modeling lightning-caused fire occurrences over forested regions.
Highlights
Human beings consider forest fires to be critical natural hazards, which damage the ecosystem and impact the economy throughout the world, including in Canada
We modeled the cumulative frequency of lightning-caused fire occurrences using cumulative median normalized difference water index (NDWI) values in every year during the validation phase, i.e., 2013–2016, by employing the obtained subregion-specific function as illustrated in the last paragraph
In the scope of this paper, we proposed a simple yet effective protocol for modeling lightning-caused fire occurrences using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived eight-day composites of NDWI, which is an indicator of vegetation/fuel moisture conditions
Summary
Human beings consider forest fires to be critical natural hazards, which damage the ecosystem and impact the economy throughout the world, including in Canada. During the last 25 years, Canada has experienced an average of 8300 fire occurrences that have burnt 2.3 million hectares of forested land every year [1]. The three most influential factors causing fires are (i) source of ignition (i.e., either lightning strikes or human activities); (ii) fuel condition; and (iii) weather regime [2]. Of the ignition sources, lightning-caused fires are relatively less frequent in Canada, but with higher impact compared to human-caused occurrences. In Canada, the boreal forest occupies a significant proportion of forested land, where lightning-caused fires play a vital role in the natural succession of ecosystem functions [5]. It is worthwhile to study lightning-caused forest fire occurrences in Canada to formulate fire management strategies that are better and more effective
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