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

Remote Sensing-based Mapping of fuel types using Multisensor, Multiscale and Multitemporal data set 101
The selection of Fuel type classes, training data, and classification procedure
is a key step that strongly influence the final results and the accuracy
levels.
Fuel type classes considered in this study are an adaptation of the
Prometheus model as in Lasaponara and Lanorte (2007), Fieldwork fuel type
recognitions, performed before, after and during the acquisition of remote
sensing data, were used as ground-truth dataset to assess the results
obtained for the considered test area. Results from different classification
strategy must compared in order to assess which performs better.
The method comprised the following three basic steps: (I) adaptation of
Prometheus fuel types for obtaining a standardization system useful for
remotely sensed classification of fuel types and properties in the considered
Mediterranean ecosystems; (II) model construction for the spectral
characterization and mapping of fuel types based on supervised classification
techniques (III) evaluation for Quickbird, Landsat TM, ASTER, and
MODIS -based results with ground-truth.
Figure 2 - Quickbird - based MLC classification for a test area in Calabria.