Leaf litter decomposition is a key process for the functioning of natural ecosystems. An important limiting factor for this process is detritus availability, which we have estimated by remote sensed indices of canopy green biomass (NDVI). Here, we describe the use of multivariate geostatistical analysis to couple in situ measures with hyper-spectral and multi-spectral remote-sensed data for producing maps of litter decomposition. A direct relationship between the decomposition rates in four different CORINE habitats and NDVI, calculated at different scales from Landsat ETM+ multi-spectral data and MIVIS hyper-spectral data was found. Variogram analysis was used to evaluate the spatial properties of each single variable and their common interaction. Co-variogram and co-kriging analysis of the two variables turned out to be an effective approach for decomposition mapping from remote-sensed spatial explicit data.
Mapping litter decomposition by remote-detected indicators / Sabetta, Letizia; Zaccarelli, Nicola; Mancinelli, Giorgio; Mandrone, Stefania; Salvatori, Rosamaria; Costantini, Maria Letizia; Zurlini, Giovanni; Rossi, Loreto. - In: ANNALS OF GEOPHYSICS. - ISSN 1593-5213. - 49:1(2006), pp. 219-226. (Intervento presentato al convegno Conference on Airborne Remote Sensing for Geophysical and Environmental Application tenutosi a Rome, ITALY nel APR 14-16, 2003) [10.4401/ag-3172].
Mapping litter decomposition by remote-detected indicators
Mancinelli, Giorgio;Mandrone, Stefania;SALVATORI, ROSAMARIA;Costantini, Maria Letizia;Rossi, Loreto
2006
Abstract
Leaf litter decomposition is a key process for the functioning of natural ecosystems. An important limiting factor for this process is detritus availability, which we have estimated by remote sensed indices of canopy green biomass (NDVI). Here, we describe the use of multivariate geostatistical analysis to couple in situ measures with hyper-spectral and multi-spectral remote-sensed data for producing maps of litter decomposition. A direct relationship between the decomposition rates in four different CORINE habitats and NDVI, calculated at different scales from Landsat ETM+ multi-spectral data and MIVIS hyper-spectral data was found. Variogram analysis was used to evaluate the spatial properties of each single variable and their common interaction. Co-variogram and co-kriging analysis of the two variables turned out to be an effective approach for decomposition mapping from remote-sensed spatial explicit data.File | Dimensione | Formato | |
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