Traditionally fuel maps are built in terms of ‘fuel types’, thus considering the structural characteristics of vegetation only. The aim of this work is to derive a phenological fuel map based on the functional attributes of coarse-scale vegetation phenology, such as seasonality and productivity. MODIS NDVI 250m images of Sardinia (Italy), a large Mediterranean island with high frequency of fire incidence, were acquired for the period 2000–2012 to construct a mean annual NDVI profile of the vegetation at the pixel-level. Next, the following procedure was used to develop the phenological fuel map: (i) image segmentation on the Fourier components of the NDVI profiles to identify phenologically homogeneous landscape units, (ii) cluster analysis of the phenological units and post-hoc analysis of the fire-proneness of the phenological fuel classes (PFCs) obtained, (iii) environmental characterization (in terms of land cover and climate) of the PFCs. Our results showed the ability of coarse-resolution satellite time-series to characterize the fire-proneness of Sardinia with an adequate level of accuracy. The remotely sensed phenological framework presented may represent a suitable basis for the development of fire distribution prediction models, coarse-scale fuel maps and for various biogeographic studies.
Consiglio per la Ricerca in Agricoltura e L’analisi Dell’Economia Agraria, Research Unit for Climatology and Meteorology applied to Agriculture (CRA-CMA), Rome, Italy;Aristotle University of Thessaloniki, School of Forestry and Natural Environment, Thessaloniki, Greece;Aristotle University of Thessaloniki, School of Forestry and Natural Environment, Thessaloniki, Greece;Consiglio per la Ricerca in Agricoltura e L’analisi Dell’Economia Agraria, Research Unit for Climatology and Meteorology applied to Agriculture (CRA-CMA), Rome, Italy;Consiglio per la Ricerca in Agricoltura e l’Analisi Dell’Economia, Research Centre for Soil-Plant System studies (CRA-RPS), Rome, Italy;University of Roma La Sapienza, Department of Environmental Biology, Rome, Italy
Recommended Citation:
Sofia Bajocco,Eleni Dragoz,Ioannis Gitas,et al. Mapping Forest Fuels through Vegetation Phenology: The Role of Coarse-Resolution Satellite Time-Series[J]. PLOS ONE,2015-01-01,10(3)