SBIR/STTR Research Award

SBIR Phase I: Fire Information from REmote-sensing and Weather-models Integrated and Supplied to End-users (FIREWISE)

Award identifier 954aef8d42f2ff85259239f05e794a15d07dcdfdadb5051d6d2daf62de8908b6Awarding agency National Science Foundation

Award amount

$96,272

Program and phase

SBIR · Phase I

Award year

2006

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
HyPerspectives Inc.
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
NSF 05-605
Topic code
EO

Research abstract

This Small Business Innovation Research (SBIR) Phase I research project will demonstrate feasibility for an innovative, interactive software product that will improve the Nation's fire fighting, prevention, and restoration capabilities. The product uniquely combines remotely sensed NASA data with a leading-edge weather model, delivers the resulting data to decision makers visually via the Internet, and creates previously unavailable data sets for use by existing fire simulation software. The FIREWISE project will develop a system that combines two components critically needed by the public and private fire fighting sector: (1) NASA Moderate Resolution Imaging Spectroradiometer (MODIS) active fire data products, and (2) Mesoscale Model 5 (MM5) weather predictions. Additionally the model which will include digital elevation models (DEMs), and near-realtime satellite imagery, will accommodate additional inputs such as vegetation and fuel type maps, existing geographic information system (GIS) data layers (e.g., roads, waterways, ownership. FIREWISE, marketed as a subscription web service, will allow users to select spatially and temporally appropriate data from archival and/or daily-refreshed data sources and visualize them graphically in 3-D with animation capability, allowing end-users to follow dynamic factors such as weather and fire spread through time. Additionally, FIREWISE will output data for ready ingest into existing predictive fire models such as FARSITE, a fire behavior and growth simulator mandated for use across the US Forest Service and US Department of Interior agencies. Three factors have combined to make fire risk a national priority: (1) global warming; (2) past management of fires; and (3) increasing development of the urban/wildland interface. Improved predictions of wildfire behavior have concomitantly become increasingly important to protect life and property. This proposed project will combine MODIS and MM5 data, and demonstrate feasibility for both visualizing and manipulating those data via the Internet and serving them to existing fire models and other end-users. The innovations include: (1) Visualization - by draping geospatial and weather data over DEMs, FIREWISE will provide 3-D visualization of fire hazards or in-progress fires, far superior to single layer, static GIS representations. (2) Data integration - FIREWISE will uniquely combine MODIS remotely sensed optical data with MM5 atmospheric model output to create new data products to predict fire hazards. (3) Data access and delivery - FIREWISE will provide fire decision makers unprecedented Internet-based access to the critical dynamic fire information. FIREWISE will improve the Nation's fire fighting abilities by enabling the rapid, data-driven decision making necessary to saving lives, property, and natural resources. FIREWISE will also enable educational and distance learning programs by making visualizations available on-line. Additionally, Native American student interns will be included in the FIREWISE development team.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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