Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2021, Vol. 37 ›› Issue (19): 134-142.doi: 10.11924/j.issn.1000-6850.casb2020-0229

Special Issue: 油料作物

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Inversion of Soybean Leaf Area Index Based on UAV Multispectral Remote Sensing

Wang Jun1(), Jiang Yun2()   

  1. 1The Second Geomatics Cartography Institute, Ministry of Natural Resource, Harbin 150080
    2School of Public Administration and Law, Northeast Agricultural University, Harbin 150030
  • Received:2020-07-01 Revised:2020-09-09 Online:2021-07-05 Published:2021-07-29
  • Contact: Jiang Yun E-mail:dreamgis@163.com;remotesense@163.com

Abstract:

In order to provide basic data for the scientific management of soybean, the inversion and estimation of LAI was realized by using the multispectral remote sensing data of UAV. Five indices with good correlation with LAI were selected from various spectral vegetation indices, and the remote sensing inversion model of soybean leaf area index in northeast China was analyzed and discussed. The results show that except NDVI, the other four vegetation index models have better precision, and the determination coefficient R2 is more than 0.6; support vector machine model, the determination coefficient R2 is 0.688, and the root mean square error is 0.016, which has better prediction ability. Both models show that the UAV multispectral remote sensing system can quickly retrieve the soybean leaf area index in the field, which has practical significance in guiding precision agricultural production.

Key words: UAV, vegetation index, regression analysis, support vector machine, soybean, leaf area index

CLC Number: