A Dynamic Data Driven Wildland Fire Model

Modeling Wildland Fire Radiance in Synthetic Remote Sensing Scenes

This thesis develops a framework for implementing radiometric modeling and visualization of wildland fire. The ability to accurately model physical and optical properties of wildfire and burn area in an infrared remote sensing system will assist efforts in phenomenology studies, algorithm development, and sensor evaluation. Synthetic scenes are also needed for a Wildland Fire Dynamic Data Drive...

University of Colorado at Denver and Health Sciences Center Wildland Fire Dynamic Data-Driven Application System

Automated Extraction of Fire Line Parameters from Multispectral Infrared Images

Remotely sensed infrared images are often used to assess wildland fire conditions. Separately, fire propagation models are in use to forecast future conditions. In the Dynamic Data Driven Application System (DDDAS) concept, the fire propagation model will react to the image data, which should produce more accurate predictions of fire propagation. In this study we describe a series of image proc...

Applying a Dynamic Data Driven Genetic Algorithm to Improve Forest Fire Spread Prediction

This work represents the first step toward a DDDAS for Wildland Fire Prediction where our main efforts are oriented to take advantage of the computing power provided by High Performance Computing systems to, on the one hand, propose computational data driven steering strategies to overcome input data uncertainty and, on the other hand, to reduce the execution time of the whole prediction proces...

Real-Time Data Driven Wildland Fire Modeling

We are developing a wildland fire model based on semiempirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use th...