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Proceedings Paper

Using MODIS/NDVI imagery for the validation and calibration of a live vegetation moisture content model
Author(s): Paolo Fiorucci; Francesco Gaetani; Riccardo Minciardi; Fulvia Rosso
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Paper Abstract

Vegetation moisture dynamics plays a key role in wildland fire risk assessment. While dead fuel moisture can be considered only dependent on the dynamics of the meteorological variables, live fuel dynamics is also related to the phenological state of the considered species as well as the soil water content. Minimal variations in live moisture content can cause a great effect in wildfire risk condition, since the fine fuel load is mainly composed by live vegetation. This work presents a model able to predict the moisture content of live fine fuel starting from the phenological principles of leaf growth cycle. This approach assumes that the phenological state of a given group of vegetation at a given time instant (day of the year) can be modelled as a function of the local meteorological conditions, the soil parameters, and some vegetational parameters. The Vegetation Index products of MODIS sensor have been used to parameterize and calibrate the model. To this end, experimental parcels, fully representative of the Mediterranean vegetation cover of Liguria Region (Italy), were used as test areas. Such areas are equipped with a suite of meteorological sensors, and are periodically subject to sampling campaign aiming at characterizing the phenological state and the moisture contents of their different vegetation species. The data collected during the field campaigns were completed by the observations of MODIS-NDVI from 2001 to 2006. The paper provides a calibration procedure of phenological module carried on using the whole data sets (meteorological data, phenological and physiological data, NDVI imagery), and formalized through a mathematical programming approach. The phenological model was implemented with reference to five areas placed on the Italian territory.

Paper Details

Date Published: 9 October 2007
PDF: 11 pages
Proc. SPIE 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX, 67420Q (9 October 2007); doi: 10.1117/12.738991
Show Author Affiliations
Paolo Fiorucci, Ctr. di Ricerca Interuniv. in Monitoraggio Ambientale (Italy)
Francesco Gaetani, Ctr. di Ricerca Interuniv. in Monitoraggio Ambientale (Italy)
Riccardo Minciardi, Ctr. di Ricerca Interuniv. in Monitoraggio Ambientale (Italy)
Fulvia Rosso, Ctr. di Ricerca Interuniv. in Monitoraggio Ambientale (Italy)


Published in SPIE Proceedings Vol. 6742:
Remote Sensing for Agriculture, Ecosystems, and Hydrology IX
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)

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