clustering historical wildfires from interpolated rates of spread

Clustering Historical Rates of Spread

Stephen Guerin, SimTable

James Gattiker, LANL Statistical Sciences

May 20, 2014

What an Empirical Cluster @#$%!

Stephen Guerin, SimTable

James Gattiker, LANL Statistical Sciences

May 20, 2014

Silver Fire ROS vs Time for 11 Fuel Types

prog

ress

ion

rate

time

Dendrogram Clustering of 47 Fires

Example: Progression Rate, Fuel and Fire

Clustering from last slide

Orders the fire rate empirical pdf:

ROS Clustering Historical Fires

stephen@simtable.com

gatt@lanl.gov

May 20, 2014

End

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Cluster Ordering

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Cluster Ordering

Using Knowledge from Observed Wildfires

Historical analysis / fire-ography (pyronography :-)• Training and Education

– Use past fire data to explore fire characteristics and response– Demonstrate the variability of fire qualities and fire conditions

• Expectations of fire behavior• Community decisions on defensible spaces

• Fire situation awareness– Query historical database of fire observations for likely analogs during

an unfolding wildfire event– Create empirical models; aggregate characteristics of fire types

• Model Calibration– Resource for tuning model parameters, and analyzing the possible

failures (and quantified uncertainty) of model predictions