Fires {bestglm} | R Documentation |
Forest fires in Montesinho natural park. Standardized inputs.
Description
The forest fire data were collected during January 2000 to December 2003 for fires in the Montesinho natural park located in the northeast region of Portugal. The response variable of interest was area burned in ha. When the area burned as less than one-tenth of a hectare, the response variable as set to zero. In all there were 517 fires and 247 of them recorded as zero. The region was divided into a 10-by-10 grid with coordinates X and Y running from 1 to 9. The categorical variable xyarea indicates the region in this grid for the fire.
Usage
data(Fires)
Format
A data frame with 517 observations on the following 12 variables. All quantitative variables have been standardized.
xyarea
a factor with 36 levels
month
an ordered factor with 12 levels
day
an ordered factor with 7 levels
FFMC
fine fuel moisture code
DMC
Duff moisture code
DC
drought code
ISI
initial spread index
temp
average ambient temperature
RH
a numeric vector
wind
wind speed
rain
rainfall
lburned
log(x+1), x is burned area with x=0 for small fires
Details
The original data may be found at the website below as well
as an analysis.
The quantitative variables in this dataset have been standardized.
For convenience, the original data is provided in
MontesinhoFires
.
Source
http://archive.ics.uci.edu/ml/datasets/Forest+Fires
References
P. Cortez and A. Morais, 2007. A Data Mining Approach to Predict Forest Fires using Meteorological Data. In J. Neves, M. F. Santos and J. Machado Eds., New Trends in Artificial Intelligence, Proceedings of the 13th EPIA 2007 - Portuguese Conference on Artificial Intelligence, December, Guimaraes, Portugal, pp. 512-523, 2007.
See Also
Examples
data(Fires)
names(Fires)
#ANOVA for xyarea is significant at 1.1%.
summary(aov(lburned~xyarea, data=Fires))