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Geospatial Analysis Application to Forecast Wildfire Occurrences in South Carolina
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.
Geospatial Analysis Application to Forecast Wildfire Occurrences in South Carolina
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.
Geospatial Analysis Application to Forecast Wildfire Occurrences in South Carolina
Stephen L. Sperry (Autor:in) / Christopher J. Post (Autor:in) / Thomas J. Straka (Autor:in) / Joel A. Feltman (Autor:in)
2012
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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