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United States Department of Agriculture

Agricultural Research Service

Research Project: SYSTEMS AND TECHNOLOGIES FOR SUSTAINABLE SITE-SPECIFIC SOIL AND CROP MANAGEMENT

Location: Cropping Systems and Water Quality Research

Title: Model Testing in Precision Agriculture – Comparing Measures of Variation

Authors
item Sadler, Edward
item Sudduth, Kenneth
item Braga, Ricardo - INST. POLYTECH. PORTUGAL
item Paz, Joel - UNIVERSITY OF GEORGIA
item Jones, Jimmy - UNIVERSITY OF FLORIDA

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: November 4, 2007
Publication Date: November 4, 2007
Citation: Sadler, E.J., Sudduth, K.A., Braga, R., Paz, J., Jones, J. 2007. Model testing in precision agriculture – comparing measures of variation. ASA-CSSA-SSSA Annual Meeting [abstract]. ASA-CSSA-SSSA Annual Internation Meeting, November 4-8, 2007, New Orleans, Louisiana. p.285-19.

Technical Abstract: Statistical tests that compare means are widely known and used; tests that compare variation are less so. However, evaluating performance of a simulation model over a range of results requires both. In precision agriculture, comparing simulated results to measured results is usually done using linear regression. However, many researchers using this test have mixed spatial and temporal variation, which confounds the analysis and usually inflates the performance measure. Further, relationships exist between the correlation coefficient and the slope that need to be acknowledged to interpret the results. Finally, linear regression cannot address whether the spatial structure that exists in the measured data is simulated or not. We propose comparing semivariograms for this latter evaluation and will illustrate the process and results with an existing dataset of yield variation amenable to semivariogram analysis. We will discuss the estimation of measurement error and how it could be included in the tests of model performance. The suite of comparisons should provide a framework for performance testing of models in precision agriculture.

Last Modified: 4/17/2014
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