Estimation of Canopy Chlorophyll Content Using Hyperspectral Data
DONG Jing-jing1, 2, WANG Li1, NIU Zheng1
1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
Abstract：Many researches have developed models to estimate chlorophyl content at leaf and canopy level, but they were species-specific. The objective of the present paper was to develop a new model. First, canopy reflectance was simulated for different species and different canopy architecture using radiative transfer models. Based on the simulated canopy reflectance, the relationship between canopy reflectance and canopy chlorophyll content was studied, and then a chlorophyll estimation model was built using the method of spectral index. The coefficient of determination (Ｒ2) between spectral index based model and canopy chlorophyll content reached 0.75 for simulated data. To investigate the applicability of this chlorophyll model, the authors chose a field sample area in Gansu Province to carry out the measurement of leaf chlorophyll content, canopy reflectance and other parameters. Besides, the authors also ordered the synchronous Hyperion data, a hyperspectral image with a spatial resolution of 30 m. Canopy reflectance from field measurment and reflectance from Hyperion image were respectively used as the input parameter for the chlorophyll estimation model. Both of them got good results, which indicated that the model could be used for accurate canopy chlorophyll estimation using canopy reflectance. However, while using spaceborne hyperspectral data to estimate canopy chlorophyll content, good atmospheric correction is required.
Key words：Canopy chlorophyll content;Spectral index;Radiative transfer model
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