Improving yield mapping accuracy using remote sensing

R. Gonçalves Trevisan, L. S. Shiratsuchi, D. S. Bullock, N. F. Martin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The objective of this work was to investigate the use of remotely sensed vegetation indices to improve the quality of yield maps. The method was applied to the yield data of twelve cornfields from the Data Intensive Farm Management project. The results revealed the need to time shift the yield values up to three seconds to better match the sensor readings with the geographic coordinates. The residuals of the yield prediction model were used to identify points with unlikely yield values for that location, as an alternative to traditional approaches using local spatial statistics, without any assumption of spatial dependence or stationarity. The temporal and spatial distribution of the standardized coefficients for each experimental unit highlighted the presence of trends in the data. At least five out of the twelve fields presented trends that could have been induced by data collection.

Original languageEnglish (US)
Title of host publicationPrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019
EditorsJohn V. Stafford
PublisherWageningen Academic Publishers
Pages901-908
Number of pages8
ISBN (Electronic)9789086863372
DOIs
StatePublished - Jan 1 2019
Event12th European Conference on Precision Agriculture, ECPA 2019 - Montpellier, France
Duration: Jul 8 2019Jul 11 2019

Publication series

NamePrecision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019

Conference

Conference12th European Conference on Precision Agriculture, ECPA 2019
CountryFrance
CityMontpellier
Period7/8/197/11/19

Keywords

  • Data filtering
  • Error correction
  • Normalized difference vegetation index
  • On-farm precision experimentation

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Computer Science Applications

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  • Cite this

    Gonçalves Trevisan, R., Shiratsuchi, L. S., Bullock, D. S., & Martin, N. F. (2019). Improving yield mapping accuracy using remote sensing. In J. V. Stafford (Ed.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (pp. 901-908). (Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_111