- Author
- Autrey, B. S. | Zicherman, J.
- Title
- Development of a WUI Data Set and Its Uses.
- Coporate
- Fire Cause Analysis, Inc., Berkeley, CA
- Sponsor
- National Institute of Standards and Technology, Gaithersburg, MD
- Contract
- 60ANB7D6151
- Book or Conf
- Fire and Materials 2009. 11th International Conference. Conference Papers. Proceedings. Organised by Interscience Communications Limited. January 26-28, 2009, Interscience Communications Limited, London, England, San Francisco, CA, 181-190 p., 2009
- Keywords
- data sets | urban/wildland interface | fire simulation | fire research | fire risk | costs | meteorology | temperature | structures | elevation | wind velocity | wind direction | air temperature
- Identifiers
- RAWS is a network of ~1,900 data collection stations for collecting meteorological data; guiding principles and ideas; Old Fire (a wildfire that started on October 25, 2003 in the San Bernardino Mountains, California; Santa Ana winds; data types: Pixels or Grid, Points and Polygon; vegetation data set; meteorological data; aircraft-based technology; FireMapper; structure and parcel data; elevation data sets called the National Elevation Dataset; UWI data product; RAWS Network and the grids; embedding attributes in the grids
- Abstract
- Two interesting pursuits related to UWI fires are to give a spatial-temporal description of fire phenomenon (e.g. simulation, prediction, etc.) and to measure the risk posed by such fires. These two pursuits have a broad intersection because the data required in both cases are similar. There is a need for data with particular features: meteorological, topographical, vegetation, structure location, structure characteristics, ground temperatures, etc. Currently no such data exists. The construction of such a data product is explored in this paper. In this paper we illustrate the construction of a data product to support fire research and risk modeling efforts. The need for such a data product has been broadly cited. These citations are sometimes accompanied by descriptions of features the data product should have. For example, Rehm states that such a data product should have "detailed data on the topography, local meteorology, building layouts and elevations, three-dimensional distribution of fuels, and the material properties of both the natural fuels and the structures." Such descriptions serve well as guidance.