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Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference

Many current precision agriculture applications involve on-the-go field measurements of soil and plant properties that require accurate georeferencing. Specific equipment configuration characteristics or data transmission, reception, or logging delays may cause a mismatch between the logged data and...

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Autores principales: González Jiménez, Alfonso, Pachepsky, Yakov, Gómez Flores, José Luis, Ramos Rodríguez, Mario, Vanderlinden, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874400/
https://www.ncbi.nlm.nih.gov/pubmed/35214397
http://dx.doi.org/10.3390/s22041496
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author González Jiménez, Alfonso
Pachepsky, Yakov
Gómez Flores, José Luis
Ramos Rodríguez, Mario
Vanderlinden, Karl
author_facet González Jiménez, Alfonso
Pachepsky, Yakov
Gómez Flores, José Luis
Ramos Rodríguez, Mario
Vanderlinden, Karl
author_sort González Jiménez, Alfonso
collection PubMed
description Many current precision agriculture applications involve on-the-go field measurements of soil and plant properties that require accurate georeferencing. Specific equipment configuration characteristics or data transmission, reception, or logging delays may cause a mismatch between the logged data and the GPS coordinates because of time and position lags that occur during data acquisition. We propose a simple coordinate translation along the measurement tracks to correct for such positional inaccuracies, based on the local travel speed and time lag, which is estimated by minimizing the average ln-transformed absolute difference with the nearest neighbors. The correction method is evaluated using electromagnetic induction soil-sensor data for different spatial measurement layouts and densities and by comparing variograms for raw and modified coordinates. Time lags of 1 s are shown to propagate into the spatial correlation structure up to lag distances of 10 m. The correction method performs best when repeated measurements in opposite driving directions are used and worst when measurements along parallel driving tracks are only repeated at the headland turns. In the latter case, the performance of the method is further improved by limiting the search neighborhood to adjacent measurement tracks. The proposed coordinate correction method is useful for improving the positional accuracy in a wide range of soil- and plant-sensing applications, without the need to grid the data first.
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spelling pubmed-88744002022-02-26 Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference González Jiménez, Alfonso Pachepsky, Yakov Gómez Flores, José Luis Ramos Rodríguez, Mario Vanderlinden, Karl Sensors (Basel) Communication Many current precision agriculture applications involve on-the-go field measurements of soil and plant properties that require accurate georeferencing. Specific equipment configuration characteristics or data transmission, reception, or logging delays may cause a mismatch between the logged data and the GPS coordinates because of time and position lags that occur during data acquisition. We propose a simple coordinate translation along the measurement tracks to correct for such positional inaccuracies, based on the local travel speed and time lag, which is estimated by minimizing the average ln-transformed absolute difference with the nearest neighbors. The correction method is evaluated using electromagnetic induction soil-sensor data for different spatial measurement layouts and densities and by comparing variograms for raw and modified coordinates. Time lags of 1 s are shown to propagate into the spatial correlation structure up to lag distances of 10 m. The correction method performs best when repeated measurements in opposite driving directions are used and worst when measurements along parallel driving tracks are only repeated at the headland turns. In the latter case, the performance of the method is further improved by limiting the search neighborhood to adjacent measurement tracks. The proposed coordinate correction method is useful for improving the positional accuracy in a wide range of soil- and plant-sensing applications, without the need to grid the data first. MDPI 2022-02-15 /pmc/articles/PMC8874400/ /pubmed/35214397 http://dx.doi.org/10.3390/s22041496 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
González Jiménez, Alfonso
Pachepsky, Yakov
Gómez Flores, José Luis
Ramos Rodríguez, Mario
Vanderlinden, Karl
Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title_full Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title_fullStr Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title_full_unstemmed Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title_short Correcting On-the-Go Field Measurement–Coordinate Mismatch by Minimizing Nearest Neighbor Difference
title_sort correcting on-the-go field measurement–coordinate mismatch by minimizing nearest neighbor difference
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8874400/
https://www.ncbi.nlm.nih.gov/pubmed/35214397
http://dx.doi.org/10.3390/s22041496
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