Biometrics parameters and fluxes estimation in Mediterranean mountainous grassland with remote sensing techniques
Author(s)
Balzarolo, Manuela
Date Issued
April 23, 2008
Type
Doctoral Thesis
Abstract
European mountain grasslands, which include also Alps, Apennines and Pyrenees, are subject
to relatively fast changes in both human activities and climatic conditions. Their role in the
biogeochemical cycles is still highly uncertain and unknown and, in addition, the European
Mediterranean mountain areas are unique and under-represented study cases. Therefore, their
knowledge can therefore introduce new avenues in the understanding of the whole grassland
ecosystem.
Remote sensing techniques appear as very useful tools in assessing and predicting productivity,
quantity and quality of grassland over larger areas, whit higher temporal resolutions and lower
cost than traditional methods of grassland sampling.
In this study we analyzed the biometric parameters of three different land uses of the
Mediterranean grassland of Amplero (Abruzzo region, Italy): meadow (managed by harvesting
and grazing that is the typical management in Amplero and in Appenines areas), natural (areas
to exclude all external impacts) and pasture (used for animal grazing). Aim of this study has
been the evaluation of the potentiality of remote sensing in the prediction or of biometric
parameters, such as biomass and its partitioning, and LAI or Net Primary Productivity (NPP)
and carbon fluxes (Net Ecosystem Exchange, NEE; Gross primary productivity, GPP) of a
Mediterranean grassland. For this reason, we applied the following independent approaches:
agronomic destructive sampling inventory, hyperspectral radiometric measurements, satellite
images processing and micrometeorological methods.
We note that different management activities cause a broad variation in biomass dynamics.
Cutting/harvesting and grazing have the same effects on the ecosystem reducing the quantity of
available herbage and blocking the grassland growth. The effect of management on biomass
quantity and quality can be detected by hyperspectral indexes and its relationships with
investigated biometric parameters. Moreover, these relationships change also as consequence of
growing vegetation phase and for this reason can be performed for analyzing the vegetation
phenological status and characteristics of each type of managements present in the whole
grassland area of Amplero. Finally, the estimation of GPP using radiometric methods it is
possible to predict this variable both continuously and locally by CNR1 radiometer both
discontinuously but on a larger area by MODIS images.
Additional information
Dottorato di ricerca in Ecologia Forestale
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