Using targeted sampling to process multivariate soil sensing data

Viacheslav I. Adamchuk, Raphael A. Viscarra Rossel, David B. Marx, Ashok K Samal

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Most soil properties sensed on-the-go (e.g., electrical conductivity, capacitance, optical reflectance, mechanical resistance and soluble ion activity) are not directly related to the agronomic parameters used to make management decisions. Nonetheless, these sensors provide an opportunity to obtain fine-resolution data about the spatial variability of soil in agricultural fields, rapidly and at a relatively low cost. To process this information, a limited number of targeted samples must be collected and undergo conventional laboratory testing for site-specific calibration of the sensor data. Selecting sampling locations based on multiple sensor data layers is an important process and, in practice, is conducted in a very subjective manner. This paper discusses an analytical methodology to assess the quality of targeted sampling strategies for on-the-go soil sensor data calibration prior to site-specific soil treatments, and demonstrates the potential for the automated selection of sampling sites. The methodology uses an arbitrary objective function that maximizes the spread among sensor output, local homogeneity (spatial uniformity around each location), and physical coverage across an entire field. Soil pH and electrical conductivity maps of a 23-ha agricultural field were used to illustrate the applicability of this method. From those considered, a Latin hypercube sampling (LHS) procedure with homogeneity and field coverage constraints provided the highest probability of maximum objective function outcomes, when individual criteria were normalized by the median of a large number of random prescription sets.

Original languageEnglish (US)
Pages (from-to)63-73
Number of pages11
JournalGeoderma
Volume163
Issue number1-2
DOIs
StatePublished - Jun 15 2011

Fingerprint

sensor
sampling
application coverage
soil
homogeneity
electrical conductivity
calibration
capacitance
methodology
soil heterogeneity
spatial data
agricultural soils
soil treatment
reflectance
soil pH
soil properties
soil property
ions
ion
cost

Keywords

  • Electrical conductivity
  • On-the-go soil sensing
  • Soil pH
  • Targeted sampling

ASJC Scopus subject areas

  • Soil Science

Cite this

Using targeted sampling to process multivariate soil sensing data. / Adamchuk, Viacheslav I.; Viscarra Rossel, Raphael A.; Marx, David B.; Samal, Ashok K.

In: Geoderma, Vol. 163, No. 1-2, 15.06.2011, p. 63-73.

Research output: Contribution to journalArticle

Adamchuk, Viacheslav I. ; Viscarra Rossel, Raphael A. ; Marx, David B. ; Samal, Ashok K. / Using targeted sampling to process multivariate soil sensing data. In: Geoderma. 2011 ; Vol. 163, No. 1-2. pp. 63-73.
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