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EMI needs calibration with a reduced number of soil samples analyzed in the lab.
PCA was conducted to reduce the number of soil chemistry variables that may differ between populations of C. arietinum, C. echinospermum, and C. reticulatum.
For instance, it is difficult to predict a large number of soil properties simultaneously, while preserving the relationships between them.
However, given the large number of soil properties that need to be understood and mapped, cost-effective methods are required.
The country is also short of capacity to acquire such information with a declining number of soil surveyors and limited capability and resourcing of soil analytical laboratories.
Both the individual density and the number of soil faunal groups were significantly higher in soil organic layer than those in mineral soil layer.
The analysis of variance indicated that land use significantly influenced macroporosity, the mean macropore equivalent diameter, and the number of soil macropore.
The required number of soil samples could be decreased by 45% with a simultaneous sampling of forest floor and upper mineral soil, leading to more reliable SOC inventories.
Each field object consists of a number of soil layer objects, each of which contains routines to calculate its water balance and carbon and nitrogen dynamics.
In this paper a number of soil and landscape criteria were identified and their weights specified as a result of discussions with local experts.
The incoming point cloud was previously filtered using the Random Sample Consensus (RANSAC) algorithm, by reducing the number of soil points until a threshold value was reached.
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