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A comparison of linear and non-linear kriging techniques for predicting the probability of exceeding a threshold value

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dc.contributor.advisor Umphrey, Gary
dc.contributor.author Dance, Timothy
dc.date.accessioned 2018-09-14T15:23:41Z
dc.date.available 2018-09-14T15:23:41Z
dc.date.copyright 2018-09
dc.date.created 2018-09-04
dc.date.issued 2018-09-14
dc.identifier.uri http://hdl.handle.net/10214/14297
dc.description.abstract This study investigates the effectiveness of different kriging techniques to predict the probability that the value of a variable at a location exceeds a threshold value, with particular application to variable rate application of fertilizer in agriculture. Most often, disjunctive kriging using Hermite polynomials is used to create probability maps of predictions, but it is shown here that simpler kriging techniques can be used to make predictions of similar quality when certain assumptions can be satisfied. Data was collected in 2017 using tractor mounted sensors on a farm in Southwestern Ontario. A measure of greenness, NDVI, was calculated and linked to GPS coordinates, which was then used to predict the harvestability of the land. Both linear and non-linear methods show high predictive ability, suggesting that linear kriging is a viable alternative. Additional data collection and analysis is suggested to validate these results and further refine the models. en_US
dc.language.iso en en_US
dc.subject Precision Agriculture en_US
dc.subject Remote Sensing en_US
dc.subject Turfgrass en_US
dc.subject Kriging en_US
dc.title A comparison of linear and non-linear kriging techniques for predicting the probability of exceeding a threshold value en_US
dc.type Thesis en_US
dc.degree.programme Mathematics and Statistics en_US
dc.degree.name Master of Science en_US
dc.degree.department Department of Mathematics and Statistics en_US
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