Dynamic monitoring crop growth can keep track of the crop growth status, seedlings, soil moisture, nutriture and their changes and then the appropriate management strategies will be taken to ensure timely the normal growth and development. This study represented the potential of satellite hyperspectral imagery to monitor winter wheat biophysical and biochemical characteristics through narrow-band indices in Beijing. Three hyperspectral images (HSI, 100m, 115Bands, 460.04–951.54nm) of Environment and Disaster Monitoring and Forecasting of Small Satellite Constellation A (HJ-1A) were acquired in 5th April, 2009. Canopy spectral reflectance, leaf area index (LAI) and chlorophyll content (CHLa, CHLb) of winter wheat were measured synchronously with HJ1-1A visited. Firstly, the Gaussian function is taken to simulate the response function of HSI, and then the ground hyperspectral data is matched to the HSI channels to get the simulated HSI. Secondly, the correlation relationships between the simulated HSI and its mathematical transforms (derivative HSI, normalized spectral index (NDSI), subtraction index (SSI)) and the observed LAI and CHL were analyzed, respectively, to select the sensitive bands of the LAI and CHL. Finally, the indexes NDSI(748.2,765.11) and SSI(759.39,776.82), which were built with these above sensitive bands, were chosen to estimate LAI and CHL, respectively. On basis of the above analysis, these constructed indexes were applied in observed HSI. The HSI data were processed by radiometric calibration, vertical stripes elimination, atmospheric correction, and geometric correction. And then, mapping the LAI and CHL to quantitatively monitor the crop growth.
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