Towards policies for data insertion in dynamic data driven application systems: a case study sudden changes in wildland fire

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

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...

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...

Dynamic Data-Driven Application Systems for Empty Houses, Contaminat Tracking, and Wildland Fireline Prediction

We describe three different dynamic data-driven applications systems (DDDAS): an empty house, a contaminant identification and tracking, and a wildland fire. Each has something in common with all of the rest and can use some common tools. Each DDDAS is quite complicated in comparison to a traditional static input simulation that is run with large numbers of inputs instead of one longer run that...

An automatic statistical segmentation algorithm for extraction of fire and smoke regions

Estimation of the extent and spread of wildland fires is an important application of high spatial resolution multispectral images. This work addresses a fuzzy segmentation algorithm to map fire extent, active fire front, hot burn scar, and smoke regions based on a statistical model. The fuzzy results are useful data sources for integrated fire behavior and propagation models built using Dynamic...