Interpolation of Data Measured by Field Harvesters: Deployment, Comparison and Verification
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Abstract
Yield is one of the key indicators in agriculture. The most common practices provide only one yield value for a whole field according to the weight of the harvested crop. On the contrary, precision agriculture techniques discover spatial patterns within a field to minimise the environmental burden caused by agricultural activities. Field harvesters equipped with sensors provide more detailed and spatially localised values. The measurements from such sensors need to be filtered and interpolated for the purposes of follow-up analyses and interpretations. This study verified the differences between three methods of interpolation (Inverse Distance Weighted, Inverse Distance Squared and Ordinary Kriging) derived from field sensor measurements that were (1) obtained directly from the field harvester, (2) processed by global filters, and (3) processed by global and local filters. Statistical analyses evaluated the results of interpolations from three fully operational Czech fields. The revealed spatial patterns, as well as recommendations regarding the suitability of the interpolation methods used, are presented at the end of this paper.
Keywords
Data filtering Field harvester Interpolation Inverse Distance Squared Inverse Distance Weighted Ordinary Kriging Yield mappingNotes
Acknowledgments
This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 818346 titled “Sino-EU Soil Observatory for Intelligent Land Use Management” (SIEUSOIL). Kateřina Trojanová, Tomáš Pavelka and Šimon Leitgeb were also supported by funding from Masaryk University under grant agreement No. MUNI/A/1576/2018. The authors would like to thank all persons from the Rostěnice Farm who participated in the study.
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