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Chlorophyll is one of the most important pigments for plant photosynthesis as a proxy of health of vegetation and photosynthetic capacity. In this study, estimation of chlorophyll content of corn of western regions of Jilin Province is conducted based on both the measured hyperspectral data and the environmental satellite hyperspectral image data (HJ-HSI). Four kinds of vegetation indices including NDVI, MSR, MCAVI/OSAVI and TCAVI/OSAVI, are used for the inversion of chlorophyll. Among these vegetation indices, NDVI performs the best in estimating chlorophyll, followed by MSR and TCAVI/OSAVI. Otherwise, using HSI data based on vegetation indices in modeling performs not very well but the verification accuracy is rather high (R>0.9). And the slopes of validated models are all less than 0.4, which indicate that these estimates are lower than the measured results. Key words—Vegetation indices; HJ-HSI; three-band model; chlorophyll content

Study on Hyperspectral Models in estimating Chlorophyll Content of Corn Based on Hyperspectral measured data and HJ-HSI