基于无人机遥感的小麦无人驾驶系统作业质量评估

doi:10.13733/j.jcam.issn.2095-5553.2023.06.021

摘要/Abstract

摘要： 为探究不同作业模式对小麦生长的影响，通过无人机影像对小麦人工驾驶作业、小麦辅助驾驶系统作业、小麦无人驾驶系统作业区出苗率及长势进行对比性分析，研究结果表明：基于无人驾驶系统作业的小麦出苗率及小麦长势指数最好，分别为79.56%和0.853；基于辅助驾驶系统作业的小麦出苗率及小麦长势次之，分别为78.91%和0.806；基于人工驾驶作业的小麦出苗率及小麦长势最低，分别为60.43%和0.757。基于无人驾驶系统作业的小麦生长优于辅助驾驶作业优于人工驾驶作业，研究结果可为智能农机在小麦播种作业中的优势与价值提供参考，同时，本文所采用的基于无人机遥感的分析计算方法在评估小麦出苗率及长势方面也具有很好的参考价值。

关键词: 无人机, 无人驾驶系统, 小麦长势, 遥感监测, 出苗率

Abstract: Comparative analysis of wheat manual driving operation, wheat assisted driving system operation, and wheat unmanned driving system operation area emergence rate and growth trend through drone images, the results showed that wheat operated by the unmanned driving system had the highest wheat seedling emergence rate and wheat growth index, with values of 79.56% and 0.853, respectively. Wheat operated by the agricultural machinery auxiliary driving system had the secondhighest seedling emergence rate and wheat growth, with values of 78.91% and 0.806, respectively. Wheat operated by manual driving had the lowest emergence rate and wheat growth, with values of 60.43% and 0.757, respectively. The research results can provide a reference for the advantages and value of intelligent agricultural machinery in wheat sowing operations. The analysis and calculation method based on UAV remote sensing adopted in this paper also has good reference value in evaluating wheat emergence rate and growth.

Key words: UAV, unmanned systems, wheat growth, remote sensing monitoring, seedling emergence rate

中图分类号:

S512.1: S127

孙梦遥, 胡冰冰, 陈华, 陈玉梅, 吴才聪, 徐岚俊. 基于无人机遥感的小麦无人驾驶系统作业质量评估[J]. 中国农机化学报, 2023, 44(6): 148-154.

Sun Mengyao, Hu Bingbing, Chen Hua, Chen Yumei, Wu Caicong, Xu Lanjun. Operation quality assessment of unmanned wheat system based on UAV remote sensing[J]. Journal of Chinese Agricultural Mechanization, 2023, 44(6): 148-154.

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