Modeling of soil thickness based on DEM derivatives calculated using different polynomials

Soil thickness is one of the most important soil quality indicators, and its mapping is essential to land management. In this research, the coefficients of second-order (Evans-Young algorithm) and third-order (Florinsky algorithm) polynomial models were utilized for soil thickness modeling using the...

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Bibliographic Details
Published in:Arabian journal of geosciences 2022, Vol.15 (7), Article 655
Main Author: Khanifar, Javad
Format: Article
Language:English
Subjects:
Algorithms
Coefficients
Digital Elevation Models
Earth and Environmental Science
Earth science
Earth Sciences
Land management
Mathematical models
Modelling
Morphometry
Original Paper
Polynomials
Soil
Soil quality
Soils
Spline functions
Splines
Statistical analysis
Statistical methods
Thickness
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Summary:Soil thickness is one of the most important soil quality indicators, and its mapping is essential to land management. In this research, the coefficients of second-order (Evans-Young algorithm) and third-order (Florinsky algorithm) polynomial models were utilized for soil thickness modeling using the multivariate adaptive regression splines (MARS) algorithm. The statistical analysis demonstrated that there is a significant difference between the coefficients p and q of the two polynomials. The MARS model fitted based on the coefficients of the third-order polynomial model (R-Sq. adjusted = 0.48, RMSE = 0.32) was more powerful and had higher accuracy in soil thickness prediction compared with the other fitted model. The utilization of the Florinsky algorithm in the digital soil modeling (DSM) is recommended based on the modeling results and its ability to compute third-order partial derivatives from the digital elevation model (DEM). The findings of this research suggest that polynomial coefficients can be used, especially when morphometric variables are not suitable as proxy variables.
ISSN:1866-7511
1866-7538
DOI:10.1007/s12517-022-09941-3