An early warning system to forecast the close of the spring burning window from satellite-observed greenness

Paul D Pickell,Jinkai Zhang,Christopher W Bater,Colin J Ferster,Mike D Flannigan,Nicholas C Coops,Karen D Blouin

doi:10.1038/s41598-017-14730-0

Abstract

Spring represents the peak of human-caused wildfire events in populated boreal forests, resulting in catastrophic loss of property and human life. Human-caused wildfire risk is anticipated to increase in northern forests as fuels become drier, on average, under warming climate scenarios and as population density increases within formerly remote regions. We investigated springtime human-caused wildfire risk derived from satellite-observed vegetation greenness in the early part of the growing season, a period of increased ignition and wildfire spread potential from snow melt to vegetation green-up with the aim of developing an early warning wildfire risk system. The initial system was developed for 392,856 km2 of forested lands with satellite observations available prior to the start of the official wildfire season and predicted peak human-caused wildfire activity with 10-day accuracy for 76% of wildfire-protected lands by March 22. The early warning system could have significant utility as a cost-effective solution for wildfire managers to prioritize the deployment of wildfire protection resources in wildfire-prone landscapes across boreal-dominated ecosystems of North America, Europe, and Russia using open access Earth observations.

Highlights

The importance of changing wildfire regimes under a changing climate has become a major focus of research and management efforts globally[1]
Satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide a unique opportunity to observe and monitor fuel moisture from the flush of new vegetation, since healthy leaf area has long been shown to have a strong relationship with spectral greenness indices and leaf moisture[21]
Since leaf area is a proxy for foliar fine fuel moisture[8] and is readily measured directly from satellite-derived greenness indices, fewer assumptions are required about site-specific fuel types when assessing wildfire spread potential

Summary

Introduction

The importance of changing wildfire regimes under a changing climate has become a major focus of research and management efforts globally[1]. Alberta is a model jurisdiction for investigating human-caused wildfire risk during the springtime due to the confluence of human ignition sources and a seasonal change in fuel moisture modulated by climate and leaf phenology For these reasons, May is the most active wildfire month resulting in the highest monthly area burned in Alberta[7], and springtime burning is common to circumboreal ecosystems across North America, Europe, and Russia[9,10,11]. Knowledge of evapotranspiration rates for different forest fuel types to estimate daily fuel availability and potential wildfire behavior[14] These models are ledgers of fuel moisture that capture moisture content of fine fuels and large coarse fuels including deep soils and duff, accounting for daily wetting and drying as well as seasonal drying factors[15]. The developed relationships of the spring burning window can augment existing decision support systems by providing near real-time proxy information of fuel moisture to wildfire managers for allocating suppression resources and planning prescribed burns

Methods

Results

Conclusion