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\nmeasurements use generally very wideFOV(often between 10°and 40°) in order to obtain representative\nsampling size. This difference may introduce some large errors. The objective of this paper is to propose a\npracticalmodelingmethod and evaluate field ofview effecton the field reflectancemeasurements for row crops.\nThemodel considers a row crop as a repetition of rectangularwalls and then translates to a grid mi age with\nsufficient spatial resolution. The wideFOVreflectance is determined by averaging the reflectance of the\nelements. Thismodelhas been used for studying a typical row structure crop (maize canopy) for observation\nangles (from -60°to +60°with step of5°) and for threeFOV(10°, 25°, 45°). The results show thatwide\nFOVmeasurements generally underestmi ate the reflectance in the red domain (up to -25% of relative\nreflectancewhen a 25°ofFOV) and have overestmi ation in the near infrared domain (up to 10% of relative\nreflectancewhen a 25°ofFOV). For different viewing angles, the vegetation contribution is overestmi ated in\nthe illumination direction and underestmi ated in the opposite direction; in the thermal infrared domain, the\nbrightness temperature is generally underestmi ated for viewing angle less than 20°. This study can be used not\nonly to analyze thatFOVeffects, but also tomake optmi al design of observation geometry(FOV, measurement\nheight, measurement spatial size etc. ) for minmi izing the measurement errors, and/or to introduce some\ncorrections to reduce theFOVeffects.