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This article in SSSAJ

  1. Vol. 74 No. 5, p. 1763-1774
    Received: Jan 31, 2010

    * Corresponding author(s): henrylin@psu.edu


Repeated Electromagnetic Induction Surveys for Improved Soil Mapping in an Agricultural Landscape

  1. Qing Zhua,
  2. Henry Lin *a and
  3. James Doolittleb
  1. a Dep. of Crop and Soil Sciences, 116 ASI Building, Pennsylvania State Univ., University Park, PA 16802
    b USDA–NRCS, National Soil Survey Center, 11 Campus Blvd., Suite 200, Newtown Square, PA 19073


Soil apparent electrical conductivity (ECa) measured by electromagnetic induction (EMI) has been widely used to interpret soil spatial variability. We investigated the use of repeated EMI surveys, in combination with depth to bedrock and terrain attributes, to improve soil mapping in a 19.5-ha agricultural landscape. The first two surveys were done in 1997 and 2006, in which different meters (EM38, EM31, and Dualem-2), dipole orientations, and geometries were compared. The EM38 operated in vertical dipole orientation was then used in another six surveys in different seasons from 2008 to 2009. Results showed that the optimal use of EMI depends on the targeted soil properties, landscape characteristics, specific EMI meter and its setting, and the timing of the survey. The EM31 operated in vertical dipole orientation provided the deepest measurement depth (6 m) among the three meters used and showed the strongest relationship with depth to bedrock in the study area (r 2 = 0.58). Because the top 2 m of soil profiles exhibited distinct textural differences across the landscape, the EM31 operated in horizontal dipole orientation and Dualem-2 operated in horizontal co-planar geometry (both with 3-m measurement depth) showed the best correlation with silt content (r 2 = 0.45–0.47). The best EMI mapping of major soil distribution across this landscape requires optimal timing (wet period) and an appropriate meter and setting. No single EMI survey or the relative difference in ECa of repeated EMI surveys was sufficient to obtain the best possible soil map for the study area. Instead, a combination of repeated EMI surveys, depth to bedrock, and terrain attributes provided the best mapping of soils in this agricultural landscape and doubled the accuracy of map unit purity compared with the existing second-order soil map.

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