太阳辐射强度与观测角度对冬小麦冠层反射高光谱的影响

Effect of solar radiation intensity and observation angle on canopy reflectance hyperspectra for winter wheat

掌握冠层反射光谱二向性反射特征,对提高遥感应用精度有重要意义。该文利用地面自动遥感平台对冬小麦冠层进行了连续观测,获取了大量的多角度高光谱遥感数据,分析了多种因素对冠层反射光谱的影响,并进行了NDVI与EVI的对比分析。结果表明:冠层反射光谱对天气有响应,随着太阳辐射增加冠层反射光谱增高,晴天变化更明显;观测角度的改变导致冠层反射光谱的差异,可用"热点效应"加"镜面反射"解释;与上述条件相适应,NDVI与EVI也表现出与冠层反射光谱相似变化;受红光和近红外波段的变化影响,NDVI与EVI之间的变化趋势较一致,两者相关系数R2>0.72,且P<0.01,呈极显著相关。该研究结果可为遥感观测角度的选择设计和植被指数的应用提供理论参考。

In recent years, as spectral resolution is being accurate to nanometer level, hyperspectral remote sensing has a unique advantage in the detection of plant life information and the analysis of vegetation growth status. Grasping bidirectional reflectance characteristics of the canopy reflectance spectrum is significant to improve the accuracy of remote sensing applications. Many scholars at home and abroad measured and analyzed the vegetation reflectance rate with the change of view angle, variation of solar zenith angle and season, but they mainly focused on the meadows and forests, and the systematical sensitivity analysis on crop reflectance spectrum was less involved. This paper got a lot of multi-angle hyperspectral remote sensing data based on surface automatic remote sensing platforms. Different from the traditional field spectrometer（ASD Fieldspec）, Jaz-Combo 2 spectrometer（Ocean Optics, America） uses the field automatic observation system and has some advantages of low cost, continuous observation all day and real-time automatic remote sensing. This paper continuously observed multi-angel canopy reflectance spectra for winter wheat, and analyzed how various factors influenced the canopy reflectance spectra and 2 commonly used vegetation indices NDVI（normalized difference vegetation index） and EVI（ enhanced vegetation index）. The results showed that the fluctuation form for the measured canopy reflectance spectra from the self-designed ground automatic remote sensing platforms was found to be consistent with that simulated by the PROSAIL（PROPECT＋SAIL） model and also similar to the results studied by Hiker T and Coops N C, et al.The above results demonstrate the measured canopy reflectance spectral data are effective and available, and the calculation method of data is also proved to be reasonable and feasible. With the solar radiation increasing, the canopy reflectance spectra showed an increasing trend and were more obvious in response to weather conditions on sunny days than cloudy days. ＂Hot spot effect＂and ＂specular reflection＂can be used to explain the phenomenon that with the changes of view angle, the canopy reflectance spectra show different distributions. When the direction of observation and the incidence direction of the sun were on the same side（backscatter）, the field of view（direct radiating portion of solar rays） coinciding with the incidence direction of the sun had the strongest point of reflection; when the direction of observation and the incidence direction of the sun were on the opposite side（forward scatter）, the field of view（direct radiating portion of solar rays） coinciding with the incidence direction of the sun had the weakest point of reflection. Under the above described conditions, vegetation index NDVI and EVI also showed similar variation with canopy reflectance spectra. Influenced by the red band and near infrared band, the change trend of NDVI and EVI was very consistent. The multi-angle relevant analysis of vegetation index NDVI and EVI showed they had a highly significant linear correlation（R20.72, P〈0.01）. So there were no obvious advantages or disadvantages between NDVI and EVI for uniform growth status and full coverage of vegetation,and they would provide the theoretical reference for the choice and design of remote sensing＇s view angle and the application of vegetation indices. In this paper, the observations only occurred in the field under uniform growth conditions which was fully covered by the late growth winter wheat, so that the data analysis was not sufficient. In subsequent studies,the data need to be further analyzed with different methods, and crop varieties, crop species and growth period are also needed to verify the findings.