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Smart Agriculture ›› 2022, Vol. 4 ›› Issue (4): 35-48.doi: 10.12133/j.smartag.SA202206004

• 专题--大田作物智慧种植 • 上一篇    下一篇

无人机遥感在饲草作物生长监测中的应用研究进展

卓越1(), 丁峰1,2, 严海军1,3(), 徐婧4   

  1. 1.中国农业大学 水利与土木工程学院,北京 100083
    2.新疆农业科学院土壤肥料与农业节水研究所,新疆 乌鲁木齐 830091
    3.农业节水与水资源教育部工程研究中心,北京 100083
    4.沧州市农林科学院,河北 沧州 061001
  • 收稿日期:2022-10-06 出版日期:2022-12-30
  • 基金项目:
    国家重点研发计划项目(2022YFD1300804);河北省现代农业产业体系草业创新团队专项资金资助项目(HBCT2018160202);自治区区域协同创新专项(科技援疆计划)(2021E02056);国家牧草产业技术体系(CARS-34);河北省重点研发计划项目(21327406D)
  • 作者简介:卓 越(1997-),男,硕士,研究方向为精准灌溉与信息化技术研究。E-mail:zhuoyue0402@126.com
  • 通信作者: 严海军(1974-),男,博士,教授,研究方向为节水灌溉技术与装备研究。E-mail:yanhj@cau.edu.cn

Advances in Forage Crop Growth Monitoring by UAV Remote Sensing

ZHUO Yue1(), DING Feng1,2, YAN Haijun1,3(), XU Jing4   

  1. 1.College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
    2.Research Institute of Soil, Fertilizer and Agricultural Water Conservation, Xinjiang Academy of Agricultural Sciences, Urumqi 830091, China
    3.Engineering Research Center of Agricultural Water-Saving and Water Resources, Ministry of Education, Beijing 100083, China
    4.Cangzhou Academy of Agriculture and Forestry Sciences, Cangzhou 061001, China
  • Received:2022-10-06 Online:2022-12-30
  • Foundation items:National Key Research and Development Program of China (2022YFD1300804); Hebei Province Modern Agricultural Industry System Grassland Innovation Team Special Fund Project (HBCT2018160202); Autonomous Region Regional Collaborative Innovation Special Fund (Science and Technology Aid Xinjiang Plan) (2021E02056); National Grassland Industry Technology System (CARS-34); National Key Research and Development Program of Hebei Province  (21327406D)
  • About author:ZHUO Yue, E-mail:zhuoyue0402@126.com
  • Corresponding author:YAN Haijun, E-mail:yanhj@cau.edu.cn

摘要:

饲草作物生长的动态监测与定量估算对于饲草规模化生产具有重要意义。无人机遥感分辨率高、灵活性强、成本低,近年来在饲草作物生长监测领域发展迅速,应用场景不断拓展。为了掌握无人机在饲草监测的国内外应用现状,确定重点发展方向,本文首先从数据获取、数据处理和饲草作物生长监测关键技术三个方面简述了无人机遥感在饲草作物监测中的基本研究方法。其次按照传感器类型从可见光、多光谱、高光谱、热红外和激光雷达遥感五个方面阐述了无人机遥感饲草作物生长监测的应用现状。最后针对研究应用中尚未解决的关键技术问题展望了未来的发展方向,提出融合饲草作物时空尺度数据和多源遥感数据、进一步拓展数据获取手段、研发智能化数据分析综合平台是未来饲草作物监测领域应用创新的关键所在。

关键词: 无人机, 遥感, 饲草作物, 生长监测, 传感器, 生物量

Abstract:

Dynamic monitoring and quantitative estimation of forage crop growth are of great importance to the large-scale production of forage crop. UAV remote sensing has the advantages of high resolution, strong flexibility and low cost. In recent years, it has developed rapidly in the field of forage crop growth monitoring. In order to clarify the development status of forage crop growth monitoring and find the development direction, first, methods of UAV crop remote sensing monitoring were briefly described from two aspects of data acquisition and processing. Second, three key technologies of forage crop including canopy information extraction, spectral feature optimization and forage biomass estimation were described. Then the development trend of related research in recent years was analyzed, and it was pointed out that the number of papers published on UAV remote sensing forage crop monitoring showed an overall trend of rapidly increasing. With the rapid development of computer information technology and remote sensing technology, the application potential of UAV in the field of forage crop monitoring has been fully explored. Then, the research progress of UAV remote sensing in forage crop growth monitoring was described in five parts according to sensor types, i.e., visible, multispectral, hyperspectral, thermal infrared and LiDAR, and the research of each type of sensor were summarized and reviewed, pointing out that the current researches of hyperspectral, thermal infrared and LiDAR sensors in forage crop monitoring were less than that of visible and multispectral sensors. Finally, the future development directions were clarified according to the key technical problems that have not been solved in the research and application of UAV remote sensing forage crop growth monitoring: (1) Build a multi-temporal growth monitoring model based on the characteristics of different growth stages and different growth years of forage crops, carry out UAV remote sensing monitoring of forage crops around representative research areas to further improve the scope of application of the model. (2) Establish a multi-source database of UAV remote sensing, and carry out integrated collaborative monitoring combined with satellite remote sensing data, historical yield, soil conductivity and other data. (3) Develop an intelligent and user-friendly UAV remote sensing data analysis system, and shorten the data processing time through 5G communication network and edge computing devices. This paper could provide relevant technical references and directional guidelines for researchers in the field of forage crops and further promote the application and development of precision agriculture technology.

Key words: UAV, remote sensing, forage crop, growth monitoring, sensor, biomass

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