Generalized Additive Models (Texts in Statistical Science)
Generalized Additive Models (Texts in Statistical Science)
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This paper presents a method to evaluate the wildfires risk using the Receiver Operating Characteristic (ROC) curve and Terra moderate resolution imaging spectroradiometer (MODIS) images. To evaluate the wildfires risk fuel moisture content (FMC) was used, the relationship between satellite images and field collected FMC data was based on two methodologies; empirical relations and statistical models based on simulated reflectances derived from radiative transfer models (RTM). Both models were applied to the same validation data set to compare their performance. FMC of grassland and shrublands were estimated using a 5-year time series (2001-2005) of Terra moderate resolution imaging spectroradiometer (MODIS) images. The simulated reflectances were based on the leaf level PROSPECT coupled with the canopy level SAILH RTM. The simulated spectra were generated for grasslands and shrublands according to their biophysical parameters traits and FMC range. Both RTM-based models, empirical and statistical, offered similar accuracy with better determination coefficients for grasslands. In this work, we have evaluated the accuracy of (MODIS) images to discriminate between situations of high and low fire risk based on the FMC, by using the Receiver Operating Characteristic (ROC) curve. Our results show that none of the MODIS bands have a good discriminatory capacity (0.9984) when used separately, but the joint information provided by them offer very small misclassification errors.