Optimal soil sampling design based on the maxvol algorithm

TL;DR

This paper introduces a soil sampling method based on the maxvol algorithm, which optimizes sample locations to improve soil mapping efficiency and accuracy, outperforming traditional methods especially for large datasets.

Contribution

The paper presents a novel soil sampling design using the maxvol algorithm, demonstrating its effectiveness and computational efficiency over existing methods.

Findings

Outperforms popular sampling methods in soil taxa prediction.

Handles large agricultural datasets efficiently.

Shows high potential for practical soil survey applications.

Abstract

Spatial soil sampling is an integral part of a soil survey aimed at creating a soil map. We propose considering the soil sampling procedure as a task of optimal design. In practical terms, optimal experiments can reduce experimentation costs, as they allow the researcher to obtain one optimal set of points. We present a sampling design, based on the fundamental idea of selecting sample locations by performing an optimal design method called the maxvol algorithm. It is shown that the maxvol-base algorithm has a high potential for practical usage. Our method outperforms popular sampling methods in soil taxa prediction based on topographical features of the site and deals with massive agricultural datasets in a reasonable time.