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These results showed that the support vector machines are feasible and reliable in the identification of soil texture classes.
The identification of soil algae is difficult, because of insufficient available morphological data or similar morphological characteristics for the microorganisms grown in similar biotopes (Řeháková et al., 2007).
The analytical methods were selected and designed based on two main aspects: identification of soil type and characterization of physico-chemical factors influencing soil corrosivity.
The conventional identification of soil water with pre-event water limits deep insights into the involvement of stationary and mobile soil water in subsurface hydrological processes.
The results showed that both identification methods could produce some errors in the identification of soil thermal and physical parameters under different experimental parameters.
This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination.
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Identification of soil-foundation dynamic stiffness parameters from real-life data, especially earthquake-induced response signals, is arguably one of the most challenging problems in structural/geotechnical earthquake engineering.
Most constitutive models for unsaturated soils are based on identification of soil-water suction with the capillary component of the matrix potential, ignoring the contribution of adsorption to this potential.
The identification of soils with accelerated atrazine mineralization to guide selection of adequate management strategies and achieve good atrazine performance in adapted soils is critical.
Given that there are only 3,131 ground surveys in the 5 million square kilometer Brazilian Amazon basin, precision identification of soils and vegetation types is only possible for the RADAM data records and even these may not be precise given local environmental heterogeneity within the area of the botanical survey.
This is in agreement with findings of Zuluaga, 1990; Vincent et al.,1996; Dehaan and Taylor, 2002 that field derived spectra of salinised soils and vegetation indexes are good indicators of irrigation induced soil salinisation for identification of saline soil regions.
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