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ARS Home » Southeast Area » Stoneville, Mississippi » Crop Production Systems Research » Research » Publications at this Location » Publication #302990
Title: The impact of sensor field of view and distance on field measurements of directional reflectance factors: a simulation study for row crops

Author
item ZHAO, FENG - Beihang University
item LI, Y - Beihang University
item DAI, XU - Beihang University
item VERHOEF, WOUT - University Of Twente
item GUO, YIQING - Beihang University
item SHANG, HONG - Beihang University
item GU, XINGFA - Chinese Academy Of Sciences
item Huang, Yanbo

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/9/2014
Publication Date: 10/20/2014
Citation: Zhao, F., Li, Y., Dai, X., Verhoef, W., Guo, Y., Shang, H., Gu, X., Huang, Y. 2014. The impact of sensor field of view and distance on field measurements of directional reflectance factors: a simulation study for row crops. Remote Sensing of Environment. 156:129-142.

Interpretive Summary: Due to the heterogeneous characteristics of the surface on the earth, the natural surface has anisotropic optical reflectance properties. In order to capture the directional characteristics of the observed surface, the scientists from Beijing University of Aeronautics and Astronautics, State University of New York, University of Twente in Netherlands, Chinese Academy of Sciences, and USDA-ARS Crop Production Systems Research Unit collectively investigated to develop a method to conduct spectral measurements of the directional reflectance factor at ground level. In the study a Monte Carlo simulation model was built to analyze the impact of sensor field of view and measuring distance in the field. The study found that the directional reflectance factor can be obtained with a tolerable bias with a proper combination of sensor field of view and measuring distance. This study provided recommendations for the choice of sensor field of view and measuring distance to reduce the bias during field measurement for row crops.

Technical Abstract: It is well established that a natural surface exhibits anisotropic reflectance properties that depend on the characteristics of the surface. Spectral measurements of the directional reflectance factor (DRF) at ground level provide us a method to capture the directional characteristics of the observed surface. Various spectro-radiometers with different field of view (FOV) were used under different mounting conditions to measure crop reflectance. The impact and uncertainty of sensor FOV and distance from the target have rarely been considered. The issue can be compounded with the characteristic reflectance of discontinuous row crops. Because of the difficulty of accurately obtaining field measurements of crop reflectance under natural environments, a Monte Carlo model was proposed to study the impact of sensor FOV and distance on field measured DRFs. The weighted photon spread (WPS) model combined the photon spread method and the weight reduction concept to simulate radiation transfer in architecturally realistic canopies. Comparisons with an established computer simulation model as well as with field DRF measurements showed close agreement. DRFs were then simulated for a range of sensor FOV and distance combinations and compared with the reference values for two typical row canopy scenes and two homogeneous canopy scenes. Sensors with a finite FOV and distance from the target approximate the true DRFs and yield average values over FOV. Moreover, the perspective projection of the sensor causes a proportional distortion in the sensor FOV from the ideal directional observations. Though such sources of error exist, it was found that the DRF can be obtained with a tolerable bias on ground level with a proper combination of sensor FOV and distance, except for the hotspot direction and the directions around it. Recommendations for the choice of sensor FOV and distance are also made to reduce the bias during field DRF measurement for row crops.