Development of a New Daily-Scale Forest Fire Danger Forecasting System Using Remote Sensing Data

Ehsan Chowdhury,Quazi Hassan

doi:10.3390/rs70302431

Ehsan Chowdhury, Quazi Hassan

Open Access

https://doi.org/10.3390/rs70302431

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Journal: Remote sensing	Publication Date: Mar 2, 2015
Citations: 36	License type: CC BY 4.0

Affiliation: University of Calgary

Abstract

Forest fires are a critical natural disturbance in most of the forested ecosystems around the globe, including the Canadian boreal forest where fires are recurrent. Here, our goal was to develop a new daily-scale forest fire danger forecasting system (FFDFS) using remote sensing data and implement it over the northern part of Canadian province of Alberta during 2009–2011 fire seasons. The daily-scale FFDFS was comprised of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived four-input variables, i.e., 8-day composite of surface temperature (TS), normalized difference vegetation index (NDVI), and normalized multiband drought index (NMDI); and daily precipitable water (PW). The TS, NMDI, and NDVI variables were calculated during i period and PW during j day and then integrated to forecast fire danger conditions in five categories (i.e., extremely high, very high, high, moderate, and low) during j + 1 day. Our findings revealed that overall 95.51% of the fires fell under “extremely high” to “moderate” danger classes. Therefore, FFDFS has potential to supplement operational meteorological-based forecasting systems in between the observed meteorological stations and remote parts of the landscape.

Highlights

Forest fires are a critical natural disturbance in most of the forested ecosystems around the globe including the Canadian boreal forest
Upon employing the Moderate Resolution Imaging Spectroradiometer (MODIS) quality assurance information for each variable of interest, we found that the data gaps in the 8-day composite of TS, normalized multiband drought index (NMDI), and normalized difference vegetation index (NDVI) variables were in the range
As we were incorporating the daily precipitable water (PW) variable in the forest fire danger forecasting system (FFDFS) framework for the first time, we opted to evaluate its individual impact on the fire danger conditions prior to integrating with other variables

Summary

Introduction

Forest fires are a critical natural disturbance in most of the forested ecosystems around the globe including the Canadian boreal forest (that represents about 10% of the global forest [1]). Canadian forests have experienced about 8300 fires that burned an average of 2.3 million ha every year for the last 25 years [1]. The forest fires are usually perceived as a threat (e.g., creating health hazards, burning vegetation increasing the carbon dioxide released into the atmosphere, economic loss, etc.) [2]. It has many positive impacts, such as helping forest regeneration, enriching soil nutrient regimes, killing insects and diseases, etc. In order to suppress fires, Canada has spent in the range of CAD $500 million to $1 billion every year on average during the last decade [1]. Factors like deforestation, land use change, and climate change have caused increases in both the frequency and severity of forest fires across the world [5,6] which means that understanding of fire danger conditions is very important to aid sustainable fire management strategies [7]

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