Fuel characteristics play an important role in driving fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to vegetation phenology. In this view, the NDVI profiles obtained from high temporal resolution satellites, like MODIS, are an effective tool for monitoring the coarse-scale vegetation seasonal timing. The aim of this paper is twofold: our first objective consists in classifying by means of multitemporal NDVI profiles the coarse-scale vegetation of Sardinia into 'phenological clusters' in which fire incidence is higher (preferred) or lower (avoided) than expected from a random null model. If fires would burn unselectively, then fires would occur randomly across the landscape such that the number of fires in a given phenological cluster would be nearly proportional to the relative area of that land cover type in the analyzed landscape. Actually, certain vegetation types are more fire-prone than others. That is, they are burnt more frequently than others. In this framework, our second objective consists in investigating the temporal parameters of the remotely sensed NDVI profiles that best characterize the observed phenology-fire selectivity relationship. The results obtained show a good association between the NDVI temporal profiles and the spatio-temporal wildfire distribution in Sardinia, emphasizing the role of bioclimatic timing in driving fire regime characteristics.
Phenological variability drives the distribution of wildfires in Sardinia / A., De Angelis; Sofia, Bajocco; Ricotta, Carlo. - In: LANDSCAPE ECOLOGY. - ISSN 0921-2973. - STAMPA. - 27:10(2012), pp. 1535-1545. [10.1007/s10980-012-9808-2]
Phenological variability drives the distribution of wildfires in Sardinia
RICOTTA, Carlo
2012
Abstract
Fuel characteristics play an important role in driving fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to vegetation phenology. In this view, the NDVI profiles obtained from high temporal resolution satellites, like MODIS, are an effective tool for monitoring the coarse-scale vegetation seasonal timing. The aim of this paper is twofold: our first objective consists in classifying by means of multitemporal NDVI profiles the coarse-scale vegetation of Sardinia into 'phenological clusters' in which fire incidence is higher (preferred) or lower (avoided) than expected from a random null model. If fires would burn unselectively, then fires would occur randomly across the landscape such that the number of fires in a given phenological cluster would be nearly proportional to the relative area of that land cover type in the analyzed landscape. Actually, certain vegetation types are more fire-prone than others. That is, they are burnt more frequently than others. In this framework, our second objective consists in investigating the temporal parameters of the remotely sensed NDVI profiles that best characterize the observed phenology-fire selectivity relationship. The results obtained show a good association between the NDVI temporal profiles and the spatio-temporal wildfire distribution in Sardinia, emphasizing the role of bioclimatic timing in driving fire regime characteristics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.