遥感地面辐射观测中的视场效应问题研究

Field of View Effect on the Remote Sensing Field Radiometric Measurements

以典型的垄行作物玉米为研究对象,提出了一种新的视场效应分析方法:网格模型法。该方法将目标空间和测量空间网格化,然后在网格空间计算观测视场内的组分比例,进而确定组合信号值。本文采用网格模型法分析了垄行作物亮叶、暗叶、亮土、暗土四分量在传感器视场中面积权重变化、空隙率的变化、方向亮温的变化、红波段反射率的变化、红外波段反射率的变化以及植被指数NDVI的变化率,研究了不同观测角度情况下视场效应的变化。

Satellite observations use very narrow field of view （FOV） （less than 0. 01°） but the field measurements use generally very wide FOV（often between 10° and 40°） in order to obtain representative sampling size. This difference may introduce some large errors. The objective of this paper is to propose a practical modeling method and evaluate field of view effect on the field reflectance measurements for row crops. The model considers a row crop as a repetition of rectangular walls and then translates to a grid image with sufficient spatial resolution. The wide FOV reflectance is determined by averaging the reflectance of the elements. This model has been used for studying a typical row structure crop （maize canopy） for observation angles （from -60° to ＋60° with step of 5°） and for three FOV（ 10°, 25°, 45°）. The results show that wide FOV measurements generally underestimate the reflectance in the red domain （up to - 25% of relative reflectance when a 25° of FOV） and have overestimation in the near infrared domain （ up to 10% of relative reflectance when a 25° of FOV）. For different viewing angles, the vegetation contribution is overestimated in the illumination direction and underestimated in the opposite direction; in the thermal infrared domain, the brightness temperature is generally underestimated for viewing angle less than 20°. This study can be used not only to analyze that FOV effects, but also to make optimal design of observation geometry（ FOV, measurement height, measurement spatial size etc. ） for minimizing the measurement errors, and/or to introduce some corrections to reduce the FOV effects.