The paper shows some operational techniques for the characterisation and mapping of pastoral resources in mountain areas. The utility of multispectral images was evaluated to produce thematic cartography of the studied pastures and to determine their pastoral value, a useful parameter for management purposes. Data collected by the multispectral ASTER sensor, with a 15 m spatial resolution in the VISNIR, 30 m in the SWIR, and 90 m in TIR, and the MODIS sensor, with a daily temporal step and a 250 m spatial resolution, were used. The images are classified using a maximum likelihood algorithm, while multivariate locally calibrated regression is applied to extend the pastoral value over the whole area. Results show a low capability of the satellite images in discriminating the different pasture vegetation types, whereas the assessment of pastoral value produces more promising achievements (r = 0.647;, RMSE = 6.99).

Analisi e valutazione di pascoli montani attraverso l’integrazione di dati multispettrali e ausiliari / G. Argenti; L. Bottai; M. Chiesi; F. Maselli; N. Staglianò; S. Targetti. - In: RIVISTA ITALIANA DI TELERILEVAMENTO. - ISSN 1129-8596. - STAMPA. - 43:(2011), pp. 45-57.

Analisi e valutazione di pascoli montani attraverso l’integrazione di dati multispettrali e ausiliari

ARGENTI, GIOVANNI;STAGLIANO', NICOLINA;TARGETTI, STEFANO
2011

Abstract

The paper shows some operational techniques for the characterisation and mapping of pastoral resources in mountain areas. The utility of multispectral images was evaluated to produce thematic cartography of the studied pastures and to determine their pastoral value, a useful parameter for management purposes. Data collected by the multispectral ASTER sensor, with a 15 m spatial resolution in the VISNIR, 30 m in the SWIR, and 90 m in TIR, and the MODIS sensor, with a daily temporal step and a 250 m spatial resolution, were used. The images are classified using a maximum likelihood algorithm, while multivariate locally calibrated regression is applied to extend the pastoral value over the whole area. Results show a low capability of the satellite images in discriminating the different pasture vegetation types, whereas the assessment of pastoral value produces more promising achievements (r = 0.647;, RMSE = 6.99).
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45
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G. Argenti; L. Bottai; M. Chiesi; F. Maselli; N. Staglianò; S. Targetti
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/406248
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