Despite the Normalised Difference Vegetation Index (NDVI) has been used to make predictions on forage quality, its relationship with bromatological field data has not been widely tested. This relationship was investigated in alpine grasslands of the Gran Paradiso National Park (Italian Alps). Predictive models were built using remotely sensed derived variables (NDVI and phenological information computed from MODIS) in combination with geo-morphometric data as predictors of measured biomass, crude protein, fibre and fibre digestibility, obtained from 142 grass samples collected within 19 experimental plots every two weeks during the whole 2012 growing season. The models were both crossvalidated and validated on an independent dataset (112 samples collected during 2013). A good predictability ability was found for the estimation of most of the bromatological measures, with a considerable relative importance of remotely sensed derived predictors; instead, a direct use of NDVI values as a proxy of bromatological variables appeared not to be supported.

MODIS time series contribution for the estimation of nutritional properties of alpine grassland / Luigi, Ranghetti; Bruno, Bassano; Giuseppe, Bogliani; Alberto, Palmonari; Andrea, Formigoni; Laura, Stendardi; Achaz von Hardenberg,. - In: EUROPEAN JOURNAL OF REMOTE SENSING. - ISSN 2279-7254. - STAMPA. - 49:1(2016), pp. 691-718. [10.5721/EuJRS20164936]

MODIS time series contribution for the estimation of nutritional properties of alpine grassland

Alberto Palmonari;Andrea Formigoni;
2016

Abstract

Despite the Normalised Difference Vegetation Index (NDVI) has been used to make predictions on forage quality, its relationship with bromatological field data has not been widely tested. This relationship was investigated in alpine grasslands of the Gran Paradiso National Park (Italian Alps). Predictive models were built using remotely sensed derived variables (NDVI and phenological information computed from MODIS) in combination with geo-morphometric data as predictors of measured biomass, crude protein, fibre and fibre digestibility, obtained from 142 grass samples collected within 19 experimental plots every two weeks during the whole 2012 growing season. The models were both crossvalidated and validated on an independent dataset (112 samples collected during 2013). A good predictability ability was found for the estimation of most of the bromatological measures, with a considerable relative importance of remotely sensed derived predictors; instead, a direct use of NDVI values as a proxy of bromatological variables appeared not to be supported.
2016
MODIS time series contribution for the estimation of nutritional properties of alpine grassland / Luigi, Ranghetti; Bruno, Bassano; Giuseppe, Bogliani; Alberto, Palmonari; Andrea, Formigoni; Laura, Stendardi; Achaz von Hardenberg,. - In: EUROPEAN JOURNAL OF REMOTE SENSING. - ISSN 2279-7254. - STAMPA. - 49:1(2016), pp. 691-718. [10.5721/EuJRS20164936]
Luigi, Ranghetti; Bruno, Bassano; Giuseppe, Bogliani; Alberto, Palmonari; Andrea, Formigoni; Laura, Stendardi; Achaz von Hardenberg,
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/567272
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