Data Fusion for Decision Support
Abstract
This thesis demonstrates the utility of fusing data from multiple sources, including remote sensing data, in a Geographic Information System (GIS) for decision support by designing a new method of assessing wildfire risk in the wilderness urban interface (WUI) to facilitate better informed land management decisions and reduce mission impacts of wildfires on the military. Information from remote sensing systems has been used for decades to support decisions. Today, data are time and location tagged, making it possible to correlate and fuse disparate sources in a GIS, from which data can be stored, analyzed, and the resulting information shared. The GIS, relating data based on spatial attributes, has become an ideal fusion platform and decision support tool. In demonstration, decades of work in fire science were put to work, applying the Fire Susceptibility Index (FSI) on a new, 30 m scale with Landsat 8 data. Eight data sources were fused in a GIS to identify high-risk patches of wildland by calculating the FSI and preparing it for meaningful analysis and sharing. The initial results, qualitatively validated with wildfire behavior basics, appear promising, providing a view of fire danger in the landscape not seen in the current state of practice.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 27, 2014
- Accession Number
- ADA609128
Entities
People
- Rebecca A. Unruh
Organizations
- Air Force Institute of Technology