Retrieval Of canopy chlorophyll content for spring corn using multispectral remote sensing data

Nitrogen is an important organic element during the growth of the crop, the accuracy of estimation for the crop N status may improve fertilizer N use efficiency. The chlorophyll content has a close relationship with the Nitrogen content. The multispectral remote sensing data may be used to assess crop N status by estimating chlorophyll content. This paper used the statistical model and the physical model to estimate the canopy chlorophyll content. As the statistical model, a few typical VI(vegetation index), Normalized Difference Vegetation Index (NDVI), Green chlorophyll index (CIgreen), Triangular greenness index(TGI), Enhanced vegetation index(EVI), Optimized Soil-Adjusted Vegetation Index(OSAVI) were used to assess the canopy chlorophyll content. For the physical model, the PROSAIL radiative transfer model and the lookup-table(LUT) method were used. The result showed these two methods have advantages and disadvantages respectively. In terms of the estimation accuracy for the chlorophyll content, the physical model is a better choice.