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How good is your weed map? A comparison of spatial interpolators

Published online by Cambridge University Press:  20 January 2017

J. Anita Dille ,
Maribeth Milner ,
Jeremy J. Groeteke ,
David A. Mortensen  and
Martin M. Williams II
Maribeth Milner
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583
Jeremy J. Groeteke
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583
David A. Mortensen
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583
Martin M. Williams II
Affiliation:
Department of Agronomy, University of Nebraska, Lincoln, NE 68583
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Abstract

Recent interest in describing the spatial distribution of weeds and studying their association with site properties has increased the use of interpolation to estimate weed seedling density from spatially referenced data. In addition, farmers and consultants adopting elements of site-specific farming practices are using interpolation methods for mapping weed densities as well as soil properties. This study was conducted to compare the performance of four interpolation methods, namely inverse-distance weighting (IDW), ordinary point kriging (OPK), minimum surface curvature (MC), and multiquadric radial basis function (MUL), with respect to their ability to map weed-seedling densities. These methods were evaluated on data from four weed species, velvetleaf, hemp dogbane, common sunflower, and foxtail species, of contrasting biology and infestation levels in corn and soybean production fields in Nebraska. Mean absolute difference (MAD) and root mean square (RMS) between the observed point sample data and the estimated weed seedling density surfaces were used to evaluate the performance of the interpolation methods. Four neighborhood search types were compared within each interpolation method, and Search3 (12 to 16 neighboring locations) generated an interpolated surface with the smallest MAD and RMS indicating the highest precision. IDW with a power coefficient of p = 4 gave the smallest MAD and RMS, as did a test with an elliptical search and no anisotropy. The level of precision of all four interpolation methods was very poor for weed species with low infestation levels (> 75% of field weed-free; MAD ranged from 100 to 187% of the observed mean density), whereas precision was improved for weed species with high infestation levels (< 25% of field weed-free; MAD ranged from 45 to 85%). No single interpolator appears to be more precise than another. Implications of this study indicate that grid sample spacing and quadrat size are more important than the specific interpolation method chosen.

Keywords

Common sunflower, Helianthus annuus L. HELANfoxtail species, Setaria spp. SETSShemp dogbane, Apocynum cannabinum L. APCCAvelvetleaf, Abutilon theophrasti Medicus ABUTHcorn, Zea mays L.soybean, Glycine max (L.) MerrInverse-distance weightingkrigingminimum curvaturemultiquadricradial basis functionABUTHAPCCAHELANSETSS
Type
Research Article
Information
Weed Science , Volume 51 , Issue 1 , February 2003 , pp. 44 - 55
Copyright
Copyright © Weed Science Society of America 

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