Title :
Monitoring wheat quality protein content in critical period based division by remote sensing
Author :
Wang Dacheng ; Li Yufei ; Fan Wenjie ; Qin Qiming
Abstract :
Based on the research on the relationship between different vegetation indexes (VIs) at different growth stages of winter wheat, we used the ecological parameters and remote sensing data to construct the winter wheat remote sensing quality model. The results showed that the correlation of NDVI green value on May 11 the grain protein was reached a significant level, which according to optimal as the research object in Beijing area, remote sensing and ecological parameters comprehensive quality model had good prediction effect than the other two models. Therefore, it is feasible and accurate to use remote sensing and ecological data to set up a comprehensive quality monitoring model.
Keywords :
crops; ecology; proteins; remote sensing; Beijing; China; NDVI green value; critical period based division; ecological parameters; remote sensing; vegetation index; wheat quality protein content; winter wheat; Biological system modeling; Data models; Indexes; Monitoring; Predictive models; Proteins; Remote sensing; quality division; remote sensing; vegetation indexes (VIs); wheat quality;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6352085