In this study, wheat at the filling stage of Hongzehu farm in Sihong County was used as the research object, and the wheat was monitored for head blight through an UAV equipped with a multi-spectral camera. The correlation analysis between 17 commonly used spectral vegetation indexes and wheat head blight disease index (DI) was carried out, and the 3 vegetation indexes with the highest correlation were obtained: normalize difference vegetation index (NDVI), structure insensitive pigment index (SIPI), triangle vegetation index (TVI), the wheat head blight monitoring model based on vegetation index was constructed and model evaluation was carried out. The results showed that the correlation between NDVI and DI value was the highest, and the coefficient of determination (R2 ) reached 0.8516. The stepwise regression equation model constructed with the three most correlated indexes as variables performed best. The coefficient of determination of model testing was 0.8787, and the root mean squared error (RMSE) was 4.1%. The comprehensive analysis shows that UAV multi-spectral remote sensing combined with the measured value of canopy wheat scab DI can realize the real-time monitoring of wheat scab in the field.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.