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Real-Time Kinematic Imagery-Based Automated Levelness Assessment System for Land Leveling

Author

Listed:
  • Senlin Guan

    (Division of Crop Rotation Research for Lowland Farming, Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, 496 Izumi, Chikugo, Fukuoka 833-0041, Japan)

  • Kimiyasu Takahashi

    (Division of Crop Rotation Research for Lowland Farming, Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, 496 Izumi, Chikugo, Fukuoka 833-0041, Japan)

  • Keiko Nakano

    (Division of Crop Rotation Research for Lowland Farming, Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, 496 Izumi, Chikugo, Fukuoka 833-0041, Japan)

  • Koichiro Fukami

    (Division of Crop Rotation Research for Lowland Farming, Kyushu-Okinawa Agricultural Research Center, National Agriculture and Food Research Organization, 496 Izumi, Chikugo, Fukuoka 833-0041, Japan)

  • Wonjae Cho

    (Division of Intelligent Agricultural Machinery Research, Institute of Agricultural Machinery, National Agriculture and Food Research Organization, 1-31-1 Kannondai, Tsukuba, Ibaraki 305-0856, Japan)

Abstract

Many cropping systems, notably for rice or soybean production, rely largely on arable land levelness. In this study, an automated levelness assessment system (ALAS) for evaluating lowland levelness is proposed. The measurement accuracy of total station, real-time kinematic (RTK) receiver, and RTK unmanned aerial vehicle (UAV) instruments used at three study sites was evaluated. The ALAS for assessing the levelness of agricultural lowlands (rice paddy fields) was then demonstrated using UAV-based imagery paired with RTK geographical data. The ALAS (also a program) enabled the generation of an orthomosaic map from a set of RTK images, the extraction of an orthomosaic map of a user-defined field, and the visualization of the ground altitude surface with contours and grade colors. Finally, the output results were obtained to assess land levelness before and after leveling. The measurement accuracy results of the instruments used indicated that the average horizontal distance difference between RTK-UAV and total station was 3.6 cm, with a standard deviation of 1.7 cm and an altitude root mean squared error of 3.3 cm. A visualized ground altitude surface and associated altitude histogram provided valuable guidance for land leveling with the ALAS; the ratios of the ground altitude of ± 5 cm in the experiment fields ( F 1 and F 2) increased from 78.6% to 98.6% and from 71.0% to 96.9%, respectively, making the fields more suitable for rice production. Overall, this study demonstrates that ALAS is promising for land leveling and effective for further use cases such as prescription mapping.

Suggested Citation

  • Senlin Guan & Kimiyasu Takahashi & Keiko Nakano & Koichiro Fukami & Wonjae Cho, 2023. "Real-Time Kinematic Imagery-Based Automated Levelness Assessment System for Land Leveling," Agriculture, MDPI, vol. 13(3), pages 1-16, March.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:3:p:657-:d:1094468
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    References listed on IDEAS

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    1. Anbumozhi, V. & Yamaji, E. & Tabuchi, T., 1998. "Rice crop growth and yield as influenced by changes in ponding water depth, water regime and fertigation level," Agricultural Water Management, Elsevier, vol. 37(3), pages 241-253, September.
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    Cited by:

    1. Senlin Guan & Kimiyasu Takahashi & Shunichiro Watanabe & Katsunori Tanaka, 2024. "Unmanned Aerial Vehicle-Based Techniques for Monitoring and Prevention of Invasive Apple Snails ( Pomacea canaliculata ) in Rice Paddy Fields," Agriculture, MDPI, vol. 14(2), pages 1-16, February.

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