Assessment of Fire Fuel Load Dynamics in Shrubland Ecosystems in the Western United States Using MODIS Products

Zhengpeng Li,Hua Shi,Todd J Hawbaker,James E Vogelmann,Birgit Peterson

doi:10.3390/rs12121911

Abstract

Assessing fire behavior in shrubland/grassland ecosystems of the western United States has proven especially problematic, in part due to the complex nature of the vegetation and its relationships with prior fire history events. Our goals in this study were (1) to determine if we can effectively leverage the high temporal resolution capabilities of current remote sensing systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve upon shrub and grassland mapping and (2) to determine if these improvements alter and improve fire behavior model results in these grass- and shrub-dominated systems. The study focused on the shrublands and grasslands of the Owyhee Basin, which is located primarily in southern Idaho. Shrubland and grassland fuel load dynamics were characterized using Normalized Difference Vegetation Index (NDVI) and Net Primary Production (NPP) datasets (both derived from MODIS). NDVI shrub and grassland values were converted to biomass, and custom fire behavior fuel models were then developed to evaluate the impacts of surface fuel changes on fire behaviors. Results from the study include the following: (1) high intra- and interannual spectral variability characterized these shrubland/grassland ecosystems, and this spectral variability was highly correlated with climate variables, most notably precipitation; (2) fire activity had a higher likelihood of occurring in areas where the NDVI (and biomass) differential between spring and summer values was especially high; (3) the annual fuel loads estimated from MODIS NPP showed that live herbaceous fuel loads were closely correlated with annual precipitation; (4) estimated fuel load accumulation was higher on shrublands than grasslands with the same vegetation productivity; (5) the total fuel load on shrublands was impacted by shrubland age, and live woody fuel load was over 66% of the total fuel load; and (6) comparisons of simulated fire behavior and spread between dynamic and static fuel loads, the latter estimates being obtained from the operational and nationwide LANDFIRE program, showed clear differences in fire indices and fire burn areas between the dynamic fuel loads and the static fuel loads. Current standard fuel models appear to have bias in underestimating the fire spread and total burnable area.

Highlights

Over the past several decades, increases in wildland fire frequency, size, and severity have had major influences on ecological, economic, and social systems [1,2]
Fuel Dynamics Estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) Products
We used the NDVI and Net Primary Production (NPP) products from the MODIS sensors to estimate the fuel loads on a typical shrubland/grassland ecosystem in the western USA

Summary

Introduction

Over the past several decades, increases in wildland fire frequency, size, and severity have had major influences on ecological, economic, and social systems [1,2]. The Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) [5,6] was established in association with the National Fire Plan by the U.S Department of Agriculture Forest Service and the Department of Interior This landscape-scale fire, ecosystem, and fuel assessment project generates and distributes nationwide 30-meter-resolution data products for fire hazard reduction, incident planning and support, and resource management. Shrublands and grasslands tend to have less readily available field information than forests, which tend to be relatively data rich Another aspect of shrublands and grasslands that has been problematic for LANDFIRE relates to the intra- and interannual spectral, phenological, and ecological variability inherent to these systems. The combination of (1) the lack of field information and (2) the complexity of fire fuel characteristics in these regions has made applications of LANDFIRE data in shrubland/grassland ecosystems challenging

Methods

Results

Discussion

Conclusion