A novel vegetation index (MPRI) of corn canopy by vehicle-borne dynamic prediction

• Published in: Guang pu xue yu guang pu fen xi Vol. 34; no. 6; p. 1605
• Main Authors: Li, Shu-qiang, Li, Min-zan, Sun, Hong
• Format: Journal Article
• Language: Chinese
• Published: China 01.06.2014
• Subjects: Agriculture; Chlorophyll - analysis; Models, Theoretical; Plant Leaves - chemistry; Zea mays
• ISSN: 1000-0593
• DOI: 10.3964/j.issn.1000-0593(2014)06-1605-05

Ground-based remote sensing system is a significant way to understand the growth of corn and provide accurate and scientific data for precision agriculture. The vehicle-borne system is one of the most important tools for corn canopy monitoring. However, the vehicle-borne growth monitoring system cannot maintain steady operations due to the row spacing of corn. The reflectance of corn canopy, which was used to construct the model for the chlorophyll content, was disturbed by the reflectance of soil background. The background interference with the reflectance could not be removed effectively, which would result in a deviation in the growth monitoring. In order to overcome this problem, a novel vegetation index named MPRI was developed in the present paper. The tests were carried out by the vehicle-borne system on the cornfield. The sensors which configured the vehicle-borne system had 4 bands, being respectively 550, 650, 766 and 850 nm. It would obtain the spectral data while the vehicle moved along the row di