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Geospatial Analysis Application to Forecast Wildfire Occurrences in South Carolina

1
School of Agricultural, Forest and Environmental Sciences, Box 340310, Clemson University, Clemson, SC 29634, USA
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School of Planning, Development, Preservation and Landscape Architecture, Box 340511, Clemson University, Clemson, SC 29634, USA
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Author to whom correspondence should be addressed.
Forests 2012, 3(2), 265-282; https://doi.org/10.3390/f3020265
Received: 6 February 2012 / Revised: 16 April 2012 / Accepted: 16 May 2012 / Published: 25 May 2012
Wildfire occurrence and intensity have increased over the last few decades and, at times, have been national news. Wildfire occurrence is somewhat predictable based on physical factors like meteorological conditions, fuel loads, and vegetation dynamics. Socioeconomic factors have been not been widely used in wildfire occurrence models. We used a geospatial (or geographical information system) analysis approach to identify socioeconomic variables that contribute to wildfire occurrence. Key variables considered were population change, population density, poverty rate, educational level, geographic mobility, and road density (transportation network). Hot spot analysis was the primary research tool. Wildfire occurrence seemed to be positively related to low population densities, low levels of population change, high poverty rate, low educational attainment level, and low road density. Obviously, some of these variables are correlated and this is a complex problem. However, socioeconomic variables appeared to contribute to wildfire occurrence and should be considered in development of wildfire occurrence forecasting models. View Full-Text
Keywords: wildfire occurrence; wildfire; geographical information system; GIS; geospatial analysis wildfire occurrence; wildfire; geographical information system; GIS; geospatial analysis
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Feltman, J.A.; Straka, T.J.; Post, C.J.; Sperry, S.L. Geospatial Analysis Application to Forecast Wildfire Occurrences in South Carolina. Forests 2012, 3, 265-282.

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