Blazing Models: Creating a Predictive Tool for Wildfires

EarthzineDEVELOP 2015 Summer VPS, DEVELOP Virtual Poster Session, Responding to Hydrologic Disasters

This is an article from the Summer 2015 VPS. For more VPS articles, click here.

1-6_JPL_USDisastersIICategory:åÊResponding to Hydrologic Disasters

Project Team: U.S. Disasters II

Team Location: NASA Jet Propulsion Laboratory – Pasadena, California


Brittany Zajic

Daniel Jensen

Nick RousseauåÊ


Dr. John T. Reager (NASA Jet Propulsion Laboratory)


Understanding the relationship between wildfire activity and soil moisture in the United States has been difficult to assess, with limited ability to determine areas that are at high risk. This limitation is largely due to complex environmental factors at play, especially as they relate to alternating periods of wet and dry conditions, and the lack of remotely-sensed products. Recent drought conditions and accompanying low Fuel Moisture Content (FMC) have led to wildfire outbreaks causing economic loss, property damage, and environmental degradation. Thus, developing a programmed toolset to assess the relationship between soil moisture, which contributes greatly to FMC and fire severity, can establish the framework for determining overall wildfire risk. To evaluate these parameters, we used data assimilated from the Gravity Recovery and Climate Experiment (GRACE) and data from the Fire Program Analysis fire-occurrence database (FPA FOD) to determine the extent soil moisture affects fire activity. Through these datasets, we produced correlation and regression maps at a coarse resolution of 0.25 degrees for the contiguous United States. These fire-risk products and toolsets proved the viability of this methodology, allowing for the future incorporation of more GRACE-derived water parameters, MODIS vegetation indices, and other environmental datasets to refine the algorithm for fire risk. Additionally, they will allow the Tactical Fire Remote Sensing Advisory Committee (TFRSAC) and the U.S. Forest Service Remote Sensing Applications Center (RSAC) to assess national-scale fire management and provide responders with a predictive tool to better employ early decision-support to high risk areas during regions’ respective fire season(s).

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