CONICET | Buscador de Institutos y Recursos Humanos

Information on fuel material is one of the basic inputs for fire management. Theaim of this work was to generate a fuel model for the Complejo Fluvio-Literol del Rio Paraná(Paraná River Fluvio Littoral Complex, referred to as CFLRP) using field and remote sensingdata. Fuel Moisture Content (FMC), proportion and size of woody fuel for different plant cover,(forests / shrubs / tall and low height grass) and compartment (aerial-litterfall) were estimated inthe flood season (late fall/winter) and during drought (end of spring / summer) between 2010and 2013. The results obtained for each of these 3 variables were weighed to make the modelfuel. The model may assume a range of values between 1 and 9 depending on the behavior ofeach of the three variables. Low model values represent areas with high FMC, low proportionof woody material and low proportion of thick woody material, while high values in the modelare indicative of areas with low FMC, high proportion of wood material and high ratio of thickwoody material. In order to know the spatial distribution of the proposed model, the resultsobtained for each sampling site were integrated onto a map generated from a multitemporalunsupervised classification of vegetation covers (Kmean, 60 classes and 10 iterations) using 2Landsat 8 OLI images images (winter / spring 2013) (12 bands), segmented with a factor scaleof 100, color (0.9) and form (0.1). The vector resulting from this classification was associated toan estimated NDVI value trend from a MODIS (MOD13Q1) temporal serie. This allowed theassigning of values of model fuel to a particular type of (vegetal) cover and areas with similarNDVI trends. The result obtained was a map of the spatial distribution of fuel associated to theprobability of fire occurrences in the CFLRP. The results of the models were validated usingfield data of land cover. Thus we propose a methodology for the cartography of fuel modelsapplicable in the CFLRP, that can be brought upto date periodically and takes into considerationthe different vegetal covers and seasonality.