Monitoring of maize canopy SPAD value under drought stress based on UAV multi-spectral remote sensing
Received date: 2022-10-08
Revised date: 2022-11-27
Online published: 2023-08-03
The accurate and dynamic monitoring of the relative content of chlorophyll in corn canopy under drought stress can improve the early warning level of corn drought and help realize precise irrigation. In this study, multispectral images captured by unmanned aerial vehicles (UAVs) were used as data sources, and various vegetation indices with clear physical significance and strong correlation with soil and plant analyzer development (SPAD) values of the chlorophyll relative content in corn canopy were selected. Multiple stepwise regression, support vector machine, the back propagation neural network (BPNN), and a remote sensing monitoring model of the corn canopy SPAD value were established and verified. The optimal estimation model was selected to extract corn canopy SPAD values under various degrees of drought stress in different growth periods. Furthermore, the changes in the corn canopy SPAD value in different growth periods were analyzed to investigate the effects of various degrees of drought stress on the corn canopy SPAD value. The results revealed that the chlorophyll-sensitive vegetation index of corn canopy was different at different growth stages. Furthermore, the inversion models with the best estimation ability varied at different growth stages. Comparing the three modeling methods revealed that the modeling results and verification results of the BPNN model were the best, which indicated that the BPNN model exhibited the best estimation ability and stability performance and can be used as the optimal method for the modeling of the SPAD value of corn canopy based on UAV multispectrum. Furthermore, drought stress can reduce the estimation accuracy of the SPAD value of corn canopy by using a remote sensing monitoring model. This reduction in accuracy affects the seedling stage. Mild drought did not significantly affect the SPAD value of corn canopy, which indicated that corn exhibited a certain adaptability and resistance to drought stress. Therefore, the BPNN model based on the vegetation index can estimate the SPAD value and can be a novel method for SPAD value monitoring based on UAV remote sensing. Furthermore, the model can be used as a reference for the nondestructive monitoring of the summer corn canopy SPAD value and precise field water management under drought stress.
Key words： maize; UAV; multi-spectral remote sensing; chlorophyll relative content
Shiyao LI , Shixiang CONG , Rongrong WANG , Hailong YU , Juying HUANG . Monitoring of maize canopy SPAD value under drought stress based on UAV multi-spectral remote sensing[J]. Arid Land Geography, 2023 , 46(7) : 1121 -1132 . DOI: 10.12118/j.issn.1000-6060.2022.503
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