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Laboratory-based Vis–NIR spectroscopy and partial least square regression with spatially correlated errors for predicting spatial variation of soil organic matter content

Auteur(s) et Affiliation(s)

CONFORTI, M.
CNR - Inst. for Agricultural and Forest Systems in the Mediterranean (ISAFOM), Rende, Italie
CRA - Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Bari, Italie
DiBEST, Univ. of Calabria, Rende, Italie
DiBEST, Univ. of Calabria, Rende, Italie
STELLUTI, M.
CRA - Consiglio per la Ricerca e la Sperimentazione in Agricoltura, Bari, Italie
CNR - Inst. for Agricultural and Forest Systems in the Mediterranean (ISAFOM), Rende, Italie


Description :
The AA. aim to test the potential of laboratory Vis–NIR spectroscopy to develop an approach of partial least square regression (PLSR) with correlated errors for estimating spatially varying soil organic matter (SOM) content from laboratory-based soil Vis–NIR spectra and producing a continuous map using a geostatistical method. The study area was the Turbolo watershed (Calabria, southern Italy), which is representative of Mediterranean areas being highly susceptible to soil degradation. It is highlighted that this approach is particularly advantageous when the data exhibit a pronounced spatial autocorrelation and could be used in digital soil mapping.


Type de document :
Article de périodique

Source :
Catena (Giessen), issn : 0341-8162, 2015, vol. 124, p. 60-67, nombre de pages : 8, Références bibliographiques : 63 ref.

Date :
2015

Editeur :
Pays édition : Allemagne, Cremlingen-Destedt, Catena

Langue :
Anglais
Droits :
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