Positioning Accuracy of RTK-GNSS-Enabled Drones and Their Performance in Agricultural Crop Sensing

Highlights The performance of RTK-GNSS-enabled drones without GCPs was assessed in agricultural applications. A centimeter-level positioning accuracy was achieved when drones were functioning with RTK-GNSS-enabled. RTK-GNSS-enabled drones without GCPs performed competitively with GCP-based methods in plant height estimation. Using RTK-enabled drones without GCPs provides a time- and labor-saving solution for agricultural practices. ABSTRACT. Commercial drones equipped with Real-Time Kinematic GNSS (RTK-GNSS) technology have been available for several years and are now a standard feature in modern models. This technology has the potential to eliminate the need for ground control points (GCPs). However, despite its widespread adoption and the positioning accuracy claimed in product specifications, limited literature exists on quantifying and systematically evaluating its performance in agricultural field settings for specific applications, such as measuring canopy height profiles. This study aimed to evaluate the potential of RTK-GNSS-enabled drones to estimate plant height without GCPs by comparing it to a benchmark method that uses GCPs across three crops: triticale, maize, and soybean. Three methods were compared: (A) regular-GNSS with GCPs, (B) RTK-GNSS with GCPs, and (C) RTK-GNSS without GCPs. Prior to evaluating the performance in height estimation, the positioning accuracy of RTK-GNSS-enabled drones was assessed, and results confirmed the centimeter-level positioning accuracy achieved by drones with RTK-GNSS-enabled. For plant height estimation, Method-C (RTK-GNSS without GCPs) performed competitively with GCP-based methods, achieving R 2 values from 0.84 to 0.99 for drone-estimated versus manually measured plant heights for the three crops, with a mean RMSE of 12.15 cm (compared to Method-A R 2 of 0.86 to 0.99 with a mean RMSE of 11.86 cm, and Method-B R 2 of 0.84 to 0.97 with a mean RMSE of 11.49 cm). Results suggest that RTK-GNSS-enabled drones can reliably estimate plant height without GCPs, offering a time- and labor-saving solution for field measurements in breeding research and agricultural production. Keywords: Keywords.,Global positioning system (GPS), Ground control point (GCP), High-throughput plant phenotyping, Plant height, Structure-from-motion, Unmanned aerial vehicle (UAV).

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Publication Details

Journal
Journal of the ASABE
Published
2025-01-01
DOI
https://doi.org/10.13031/ja.16306
Citations
2
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
3.50
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article

Positioning Accuracy of RTK-GNSS-Enabled Drones and Their Performance in Agricultural Crop Sensing

Pascal Izere, Biquan Zhao, James C. Schnable, Yeyin Shi et al.
2 citations
Journal of the ASABE
Smart Agriculture and AI
3.50
article

Positioning Accuracy of RTK-GNSS-Enabled Drones and Their Performance in Agricultural Crop Sensing

Pascal Izere, Biquan Zhao, James C. Schnable, Yeyin Shi, Yufeng Ge
article en
2 citations

Abstract

Highlights The performance of RTK-GNSS-enabled drones without GCPs was assessed in agricultural applications. A centimeter-level positioning accuracy was achieved when drones were functioning with RTK-GNSS-enabled. RTK-GNSS-enabled drones without GCPs performed competitively with GCP-based methods in plant height estimation. Using RTK-enabled drones without GCPs provides a time- and labor-saving solution for agricultural practices. ABSTRACT. Commercial drones equipped with Real-Time Kinematic GNSS (RTK-GNSS) technology have been available for several years and are now a standard feature in modern models. This technology has the potential to eliminate the need for ground control points (GCPs). However, despite its widespread adoption and the positioning accuracy claimed in product specifications, limited literature exists on quantifying and systematically evaluating its performance in agricultural field settings for specific applications, such as measuring canopy height profiles. This study aimed to evaluate the potential of RTK-GNSS-enabled drones to estimate plant height without GCPs by comparing it to a benchmark method that uses GCPs across three crops: triticale, maize, and soybean. Three methods were compared: (A) regular-GNSS with GCPs, (B) RTK-GNSS with GCPs, and (C) RTK-GNSS without GCPs. Prior to evaluating the performance in height estimation, the positioning accuracy of RTK-GNSS-enabled drones was assessed, and results confirmed the centimeter-level positioning accuracy achieved by drones with RTK-GNSS-enabled. For plant height estimation, Method-C (RTK-GNSS without GCPs) performed competitively with GCP-based methods, achieving R 2 values from 0.84 to 0.99 for drone-estimated versus manually measured plant heights for the three crops, with a mean RMSE of 12.15 cm (compared to Method-A R 2 of 0.86 to 0.99 with a mean RMSE of 11.86 cm, and Method-B R 2 of 0.84 to 0.97 with a mean RMSE of 11.49 cm). Results suggest that RTK-GNSS-enabled drones can reliably estimate plant height without GCPs, offering a time- and labor-saving solution for field measurements in breeding research and agricultural production. Keywords: Keywords.,Global positioning system (GPS), Ground control point (GCP), High-throughput plant phenotyping, Plant height, Structure-from-motion, Unmanned aerial vehicle (UAV).

Journal of the ASABEVol. 68(4)
Openalex Percentile: Top 8%
Smart Agriculture and AI
3.50
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