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This article in SSSAJ

  1. Vol. 65 No. 5, p. 1547-1558
     
    Received: Feb 28, 2000


    * Corresponding author(s): mueller@pop.uky.edu
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doi:10.2136/sssaj2001.6551547x

Map Quality for Site-Specific Fertility Management

  1. T. G. Mueller *a,
  2. F. J. Pierceb,
  3. O. Schabenbergerc and
  4. D. D. Warncked
  1. a Dep. of Agronomy, Univ. of Kentucky N-122 Ag. Science North, Lexington, KY 40546-0091
    b Center for Precision Agricultural Systems, Washington State Univ., Irrigated Agricultural Research and Extension Center, 24106 N. Bunn Road, Prosser, WA 99350-8694
    c Dep. of Statistics, Virginia Polytechnic Institute and State Univ., 211 Hutcheson Hall, Blacksburg, VA 24061-0439
    d Dep. of Crop and Soil Science, Michigan State Univ., E. Lansing, MI 48824-1325

Abstract

The quality of soil fertility maps affects the efficacy of site-specific soil fertility management (SSFM). The purpose of this study was to evaluate how different soil sampling approaches and grid interpolation schemes affect map quality. A field in south central Michigan was soil sampled using several strategies including grid-point (30- and 100-m regular grids), grid cell (100-m cells), and a simulated soil map unit sampling. Soil fertility [pH, P, K, Ca, Mg, and cation-exchange capacity (CEC)] data were predicted using ordinary kriging, inverse distance weighted (IDW), and nearest neighbor (NN) interpolations for the various data sets. Each resulting map was validated against an independent data (n = 62) set to evaluate map quality. While soil properties were spatially structured, kriging predictions were marginal (prediction efficiencies ≤48%) at high sample densities and poor at lower densities (i.e., 61- and 100-m grids; prediction efficiencies <21%). The average optimal distance exponent at each scale of measurement was 1.5. The performance of kriging relative to IDW methods (with a distance exponent of 1.5) improved with increasing sampling intensity (i.e., IDW was superior to kriging for 100% of cases with the 100-m grid, 79% of the cases with the 61.5-m grid scale, and 67% of the cases with the 30-m grid). Practically, there was little difference between these interpolation methods. Grid sampling with a 100-m grid, grid cell sampling, and simulated soil map unit sampling yielded similar prediction efficiencies to those for the field average approach, all of which were generally poor.

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Copyright © 2001. Soil Science SocietyPublished in Soil Sci. Soc. Am. J.65:1547–1558.