Journal Article10.1016/J.GEODERMA.2014.02.026
Revisiting the pseudo continuous pedotransfer function concept: impact of data quality and data mining method
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TL;DR: In this article, the authors investigated the impact of two elements on the performance of a pseudo continuous pedotransfer function (PTF) in predicting soil hydraulic properties, particularly the water retention curve (WRC).
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About: This article is published in Geoderma. The article was published on 01 Aug 2014. The article focuses on the topics: Pedotransfer function & Water retention curve.
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Citations
Pedotransfer functions in Earth system science: challenges and perspectives
Kris Van Looy,Johan Bouma,Michael Herbst,John Koestel,Budiman Minasny,Umakant Mishra,Carsten Montzka,Attila Nemes,Yakov Pachepsky,José Padarian,Marcel G. Schaap,Brigitta Tóth,Brigitta Tóth,Anne Verhoef,Jan Vanderborght,Martine van der Ploeg,Lutz Weihermüller,Steffen Zacharias,Yonggen Zhang,Yonggen Zhang,Harry Vereecken +20 more
TL;DR: In this article, a review of the existing PTFs and new generation of PTF developed in the different disciplines of Earth system science is presented, emphasizing that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTF models correctly represent the spatial heterogeneity of soils.
482
Perspectives on delineating management zones for variable rate irrigation
Amir Haghverdi,Brian G. Leib,Robert A. Washington-Allen,Paul D. Ayers,Michael J. Buschermohle +4 more
TL;DR: The ECa achieved the highest Kappa coefficient (=0.79) among ancillary attributes, hence exhibited a considerable potential for irrigation zoning, and a new zoning method was designed and evaluated for center pivot irrigation systems with limited speed control capability.
132
Multi-algorithm comparison to predict soil organic matter and soil moisture content from cell phone images
TL;DR: In this paper, a set of 24 supervised regression and machine learning prediction models including six Linear Regression Models, three Decision/Regression Trees, six Support Vector Machines (SVM), four Gaussian Process Regression (GPR) Models, four Ensembles of Trees including random forest and cubist, and other models including Artificial Neural Network (ANN) were compared in this study to predict SOM and SMC.
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Comparison of statistical regression and data-mining techniques in estimating soil water retention of tropical delta soils.
Phuong Minh Nguyen,Phuong Minh Nguyen,Amir Haghverdi,Jan De Pue,Yves-Dady Botula,Khoa Van Le,Willem Waegeman,Wim Cornelis +7 more
TL;DR: In this article, the optimal structural dependency between basic soil properties and soil water retention characteristics (SWRC) was formulated by various regression methods, including Artificial Neural Networks (ANN), Support Vector Machine for Regression (SVR), and k-Nearest Neighbors (kNN) methods.
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Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale
TL;DR: In this paper, the authors evaluated the performance of established pedotransfer functions in estimating saturated hydraulic conductivity (Ks) in a specific field and improved PTFs to arrive at a locally adapted estimation result for Ks.
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