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

• Topic--Smart Farming of Field Crops • Previous Articles     Next Articles

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

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

CLC Number: