We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time- space with a highly parallel implementation. In this paper, we discuss how we will demonstrate that our system works using a DDDAS testbed approach and data collected from an earlier fire.

Publication Date



"Demonstrating the validity of a wildfire DDDAS," Proceedings of the International Conference on Computational Science 2006 (ICCS 2006). Held at the University of Reading, UK: 28-31 May 2006.ISBN:978-3540-3438-37Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Technical Report

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


RIT – Main Campus