Titlebook: Digital Soil Morphometrics; Alfred E. Hartemink,Budiman Minasny Book 2016 Springer International Publishing Switzerland 2016 Soil profile

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2352-4774 tial to enhance our understanding of soils and how we view them. The book presents highlights from The IUSS Inaugural Global Workshop on Digital Soil Morphometrics held in June 2015 in Madison, USA..978-3-319-80318-0978-3-319-28295-4Series ISSN 2352-4774 Series E-ISSN 2352-4782

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https://doi.org/10.1007/978-3-030-01560-2 partial least-squares regression modeling. Calibration and validation datasets showed statistically similar mean and variance. The root-mean-square error of prediction for sand, silt, and clay content is 5.47, 5.18, and 5.39 g 100 g., respectively. The R. for validation is 0.30, 0.59, and 0.69 for

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The Securitization of Rogue States in the USo-dimensional soil profiles or to generate three-dimensional interactive models that allow rotation, scaling, and other forms of visual explorations. The procedural modeling technique enables the user to generate the soil profile visual representation with only a small amount of data. The images do

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Security in the Persian Gulf Regionntly positive correlation was also found between RM and clay content (. = 0.32*, . < 0.05), indicating clay might determine the formation of RM. Moreover, the ratios of iron activity (Fe./Fe.) and iron crystalline ((Fe.-Fe.)/Fe.) could also be good indices for ARD prediction. The Mn./Fe. seemed an i

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