森林冠层多角度高光谱观测系统的实现与分析

为了进一步理解遥感观测中地表目标物二向性反射特性产生的影响,增强定量反演植被结构和生理参数的能力, 以江西千烟洲通量站为基地建立了多角度高光谱观测系统。此系统主要由UniSpec-DC双通道光谱仪、Pan-Tilt Unit 可水平垂直旋转的云台、电脑、电力供应系统、软件控制系统,以及数据转换器等配件组成。获得的光谱数据经白板校正、暗电流校正、超量程数据插补、异常数据删除、缺失角度插补等预处理后可用于冠层反射率和植被指数的计算与定量分析。多角度高光谱观测系统观测的辐照度与通量观测的光合有效辐射(PAR)具有较好的一致性(R² = 0.961 4, P<0.001)。利用2013年7月观测得到的光谱和通量数据计算得到光化学反射指数(PRI)与光能利用率(LUE),二者表现出明显的对数关系(R² = 0.514 2, P<0.001)。分析认为,多角度高光谱遥感是定量研究森林生态系统的重要手段,也是进一步理解航空航天遥感与样地观测尺度问题的有效方法。

Implementation and analysis of multi-angle hyperspectral observation system for forest canopy

For better understanding of bidirectional reflectance effects of heterogeneous surface observed via optical remote sensing, and to improve the ability of quantitative retrieval of canopy structure and physiological parameters, this study introduced an improved tower-based automatic canopy multi-angle hyperspectral observation system at Qianyanzhou flux station in Jiangxi Province. This system included a spectroradiometer(UniSpec-DC), a Pan-Tilt Unit(PTU), a power supplying system, a software control system, serial converters, and so on. A 45° angular holder is mounted on the tilt axis of PTU, which allows a full range of view zenith angle(θ_V)for canopy reflectance measurements, while the inherent motion range of tilt axis is only between -37° and 42° around the vertical axis. Several pre-processing methods, for example, sensor calibration, dark currency correction, abnormal data removal, and interpolations of missing angles and outrange data, were applied on the data obtained from the system. The pre-processed data then could be used to compute canopy reflectance, vegetation indices, and do quantitative analyses. Strong relationships(R² = 0.961 4, P<0.001)were observed between “photosynthetically active radiation”(PAR)from multi-angle hyperspectral observation system and tower measurements. Photochemical reflectance index(PRI)derived from reflectance data obtained by the system showed significant logarithmic relationships(R² = 0.514 2, P<0.001)with light use efficiency(LUE)calculated by flux tower data, which was well related to previous studies. Thus, multi-angle hyperspectral remote sensing is not only an important tool in quantitative researches of forest ecosystems, but also an effective way to further understanding the scaling issues of aero space remote sensing and filed measurements.