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Maps of iron oxides and the color of Australian soil 

Ver: v1
Status of Data: Data not provided
Update Frequency: Data not provided
Security Classification: unclassified
Record Last Modified: 2015-08-28
Viewed 69 times
Accessed 18 times
Dataset Created: 2015-08-28
Dataset Published: 2015-08-28
Data can be accessed from the following links:
HTTPPoint-of-truth metadata URLHTTP22999?index=1
How to cite this collection:
Viscarra Rossel, R., McKenzie, N., Bui, E. & de Caritat, P. (2015). Maps of iron oxides and the color of Australian soil. Version v1. Commonwealth Scientific and Industrial Research Organisation. Dataset. https://dx.doi.org/10.4225/08/55DFFC6C56916 
Iron (Fe) oxide mineralogy in most Australian soils is poorly characterized, even though Fe oxides play an important role in soil function. Fe oxides reflect the conditions of pH, redox potential, moisture, and temperature in the soil environment. The strong pigmenting effect of Fe oxides gives most soils their color, which is largely a reflection of the soil’s Fe mineralogy. Visible-near-infrared (vis-NIR) spectroscopy can be used to identify and measure the abundance of certain Fe oxides in soil, and the visible range can be used to derive tristimuli soil color information. We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer with a wavelength range of 350-2500 nm. We determined the Fe oxide abundance for each sample using the diagnostic absorption features of hematite (near 880 nm) and goethite (near 920 nm) and derived a normalized iron oxide difference index (NIODI) to better discriminate between them. The NIODI was generalized across Australia with its spatial uncertainty using sequential indicator simulation, which resulted in a map of the probability of the occurrence of hematite and goethite. We also derived soil RGB color from the spectra and mapped its distribution and uncertainty across the country using sequential Gaussian simulations. The simulated RGB color values were made into a composite true color image and were also converted to Munsell hue, value, and chroma. These color maps were compared to the map of the NIODI, and both were used to interpret our results. The maps were validated by randomly splitting the data into training and test data sets, as well as by comparing our results to existing studies on the distribution of Fe oxides in Australian soils. Attributes: Units of measurement: 1. Munsell Hue; 2. Munsell Chroma; 3. Munsell value; 4. NIODI; 5. NIODI uncertainty. For details please see Viscarra Rossel et al. (2010). Data Type: Float Grid. Map projection: Lambert Conformal Conic. Datum: GDA94. Map units: Decimal degrees. Resolution: 10,000 metres. File Header Information: ncols 392; nrows 361; xllcorner -2032461.3; yllcorner -4936305.3; cellsize 10000; NODATA_value -9999; byteorder LSBFIRST. 
Credit
All Rights (including copyright) CSIRO Australia 2014. 
Purpose
Data not provided. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Temporal Coverage
From undefined to on going 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

ANZSRC - FOR
Pedology and pedometrics
Soil sciences not elsewhere classified
User Defined
geostatistical simulations
goethite
hematite
soil color
soil colour
soil mapping
TERN_Soils
TERN_Soils_DSM
visible-near-infrared reflectance
Author
Viscarra Rossel, Raphael A.
McKenzie, Neil
Bui, Elisabeth
de Caritat, Patrice
Publisher
Commonwealth Scientific and Industrial Research Organisation
Viscarra Rossel, R. A., E. N. Bui, P. de Caritat, and N. J. McKenzie (2010), Mapping iron oxides and the color of Australian soil using visible-near-infrared reflectance spectra, J. Geophys. Res., 115, F04031, doi:10.1029/2009JF001645.
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