Analyzing the Errors Caused by FOV Effect on the Ground Observations of Directional Brightness Temperature over a Row Structured Canopy
垄行作物玉米方向亮温野外测量中视场角影响的简单分析

Composite scene of row crops induced an unavoidable error in ground observations due to the use of wide field of view (FOV) in the measurements. The measurements vary with sample size and position, detector height and view direction, and bias due to project principle, which is called FOV effect. This study focused on the estimation of FOV effect on the measurements of maize canopy directional brightness temperature (DBT) using a computational geometric 2D model. The model was developed to simulate the fractional variations of canopy brightness temperature components. In this research, the maize canopy was classified into three brightness temperature components: sunlit soil, shaded soil and vegetation, each component has a unique brightness temperature value. The simulation results revealed that the errors caused by wide FOV have complex features due to canopy geometry and measurement geometry. Generally, vegetation fraction is always over counted in the nadir, errors increase dramatically with the decrease of detector height as well as the enlargement of sample size, and the deviation of the error corresponding to sample position is small. In oblique view, the errors are limited to a low level due to the compensation effect. The best approach to reduce this kind of error is to set the detector to a higher altitude as the model suggested.