Correcting coordinate-measurement mismatch of on-the-go field measurements by optimizing nearest neighbor statistics

Authors: GONZALEZ JIMENEZ, ALFONSO - IFAPA CENTRO ALAMEDA DEL OBISPO; Pachepsky, Yakov; GOMEZ FLORES, JOSE LUIS - IFAPA CENTRO ALAMEDA DEL OBISPO; RAMONS RODRIGUEZ, MARIO - IFAPA CENTRO ALAMEDA DEL OBISPO; VANDERLINDEN, KARL - IFAPA CENTRO ALAMEDA DEL OBISPO

Submitted to: Sensors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/10/2022
Publication Date: 2/15/2022
Citation: Gonzalez Jimenez, A., Pachepsky, Y.A., Gomez Flores, J., Ramons Rodriguez, M., Vanderlinden, K. 2022. Correcting coordinate-measurement mismatch of on-the-go field measurements by optimizing nearest neighbor statistics. Sensors. 22(4):1496. https://doi.org/10.3390/s22041496.
DOI: https://doi.org/10.3390/s22041496

Interpretive Summary: Fine-scale soil surveys with geophysical sensors provide valuable information on soil’s potential response to management and ecological changes. In such surveys, the sensors are mounted on vehicles that travel study areas. Time lags are often encountered, which cause a mismatch between the coordinate recording and soil property recording. That impairs the quality of soil property mapping. The objective of this work was to develop the correction for the recording times’ mismatch. The correction was based on the assumption that the optimal value of the time lag results in the minimum absolute differences between measurements in pairs of nearest locations. Results of this work will be useful in soil geophysical surveys in that their application will substantially improve the quality of soil mapping products of those surveys.

Technical Abstract: On-the-go field measurements of soil and plant characteristics, including yield, are commonplace in current Precision Agriculture applications. Yet, such measurements can be affected by positional inaccuracies that result from equipment configuration or operational characteristics (e.g. GPS antenna position with respect to sensor position) and delays in the data transmission, reception or logging. The resulting time and position lags cause a mismatch between the measurements and their attributed GPS position. To compensate for this effect a simple coordinate translation along the measurement track is proposed, depending on the local velocity and a field- and measurement configuration-specific time lag, which is estimated by minimizing the average absolute difference between the nearest neighbors. The correction procedure is demonstrated using electromagnetic induction data with different spatial configurations and by comparing variograms for corrected and non-corrected coordinates, showing that 1 s time lags propagate into the spatial correlation structure up to distances of 10 m. The correction method performs best when overlapping measurements are available, obtained in opposite driving directions, while the worst results are found when no overlapping measurements exist or only those corresponding to headland turns. Further improvements in the nearest neighbor search algorithm are discussed, e.g. by imposing the search only in adjacent measurement swaths. The results of this work are useful beyond motorized soil sensing applications.