7th Workshop on Forest Fire Management - EARSeL, European ...

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II - VALIDATION OF RS PRODUCTS FOR FIRE MANAGEMENT
5 - Conclusions
We have shown that it is feasible to assess dead fuel moisture content by
means of remote sensing data. Air temperature and relative humidity have
been estimated with MSG-SEVIRI data in a meteorological station in Spain.
The main source of error is due to unexplained variance in the retrieval of
the vapour pressure. Future research will be focused on improving the estimation
of water vapour with precipitable water content. A more robust relationship
will be addressed by increasing the number of meteorological data
trying to cover the whole Spanish territory.
N MAE RMSE a b R U bias U slope U error
e a (kPa) 59 0.17 0.22 0.32 0.76 0.61 0.25 0.04 0.71 T
(ºC) 364 2.51 3.37 1.84 0.85 0.89 0.20 0.08 0.72
RH (%) 364 9.09 12.59 12.22 0.75 0.68 0.12 0.08 0.80
10h (%) 364 2.12 3.28 3.85 0.64 0.62 0.08 0.15 0.77
Table 1. Error measurements of retrieved parameters. N, number of elements; MAE, mean
absolute error; RMSE, root mean square error; a and b, intercept and slope of the regression
between observed versus predicted; r, Pearson correlation between observed and predicted;
U bias , proportion of RMSE associated with mean differences between observed and predicted
values; U slope , proportion of RMSE associated with deviations from the 1:1 line; U error , proportion
of RMSE associated with unexplained variance.
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