Influence of atmospheric correction on the estimation of biophysical parameters of crop canopy using satellite remote sensing
A quantitative approach has been made for the estimation of biophysical parameters of a vegetation canopy by the inversion of a vegetation canopy reflectance model. Model inversion has been done using a non-linear optimization scheme against directional reflectance data over the canopy. A quasi-Newton algorithm has been employed that searches the minimum of a function iteratively using the functional values only. The technique provides a reasonably good estimation of the biophysical parameters. A study has been conducted to quantify the error related to the estimation of biophysical parameters of vegetation with simulated satellite data corrected with improper values of atmospheric aerosol and water vapour contents. In the visible, atmospheric correction of satellite data with improper values of atmospheric aerosol content results in a modification of the amplitude and angular pattern of the directional reflectance for both low-density and high-density vegetation canopies. However, in the near-infrared, the atmospheric correction of data with improper values of aerosol and water vapour contents changes the amplitude of directional reflectance, but, no significant changes in angular pattern are noticed. This study indicates that parameter estimation can be significantly influenced by using improper values of both aerosol and water vapour contents during data correction in the visible and near-infrared regions of the solar spectrum. The estimation accuracy is higher for a low-density canopy than for a dense vegetation canopy. Retrievals of all the surface parameters are not equally affected by such improper atmospheric correction of data. Particularly, estimations of soil reflectance and leaf area index are significantly influenced by such improper correction for a high-density vegetation canopy. However, the accuracy of the retrieved parameter values is higher in the near-infrared than in the visible for both high-density and low-density canopies.
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Document Type: Research Article
Affiliations: Bangladesh Space Research and Remote Sensing Organization (SPARRSO), Agargaon, Sher-E-Bangla Nagar, Dhaka-1207, Bangladesh
Publication date: May 20, 2001