Brief description
We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer. These spectra provide an integrative measure that provides information on the fundamental characteristics and composition of the soil, including colour, iron oxide, clay and carbonate mineralogy, organic matter content and composition, the amount of water present and particle size. This soil information content of the spectra was summarised using a principal component analysis (PCA). We used model trees to derive statistical relationships between the scores of the PCA and 31 predictors that were readily available and we thought might best represent the factors of soil formation (climate, organisms, relief, parent material, time and the soil itself). The models were validated and subsequently used to produce digital maps of the information content of the spectra, as summarised by the PCA, with estimates of prediction error at 3-arc seconds (around 90 m) pixel resolution. The maps might be useful in situations requiring high-resolution, quantitative soil information e.g. in agricultural, environmental and ecologic modelling and for soil mapping and classification.Attributes:
Units of measurement:
1.\tPrincipal component 1;
2.\tPrincipal component 3;
3.\tPrincipal component 3.
For interpretations please see Viscarra Rossel & Chen (2011).
Data Type: Float Grid.
Map Projection: Geographic.
Datum: GDA94.
Map units: Decimal degrees.
Resolution: 0.00083333333 degrees.
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Available: 2015-08-28
Subjects
Digital soil mapping |
Environmental Sciences |
Predictive modelling |
Principal components analysis |
Soil mapping |
Soil Sciences |
Soil Sciences Not Elsewhere Classified |
Soil visible-near infrared spectra |
Soil-landscape modelling |
TERN_Soils |
TERN_Soils_DSM |
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