Digital hemispherical photography (DHP) is widely used to measure the radiative environment and estimate sky view factors (SVF) in urban areas and leaf area index (LAI) in forests. However, a limitation is the difficulty to distinguish trees from buildings, or leaves from stems and branches. In this study, we collected and processed dual-wavelength photographs recording visible and near-infrared (NIR) light in order to classify pixels into sky, green and woody plant elements, and buildings. Three applications of the method are presented: calculation of partial SVFs accounting for the obstruction of sky by buildings and vegetation separately, the modelling of mean radiant temperature (T_mrt), and the correction of LAI estimates for light intercepted by woody elements and buildings. The obtained partial SVFs were in good agreement with values modelled based on digital surface models. Distinguishing between buildings and vegetation in the modelling of long-wave radiation fluxes in the SOLWEIG model resulted in differences in modelled T_mrt by up to 3 °C. The bias of LAI estimates in urban parks caused by the light interception by woody elements and buildings was found to be relatively small (3–4 %). However, the presented method shows a high potential for estimates of LAI of urban vegetation in densely built-up areas.

数字半球摄影（DHP）被广泛用于测量辐射环境并估算城市地区的天空视野因子（SVF）和森林中的叶面积指数（LAI）。但是，局限性在于难以将树木与建筑物区分开来，或者将树叶与茎杆和树枝区分开来。在这项研究中，我们收集并处理了记录可见光和近红外（NIR）光的双波长照片，以便将像素分类为天空，绿色和木质植物元素以及建筑物。提出了该方法的三个应用：分别计算建筑物和植被遮挡天空的部分SVF，平均辐射温度（T _mrt）的建模），以及对木质元素和建筑物拦截的光的LAI估算值的修正。获得的部分SVF与基于数字表面模型建模的值非常吻合。在SOLWEIG模型中对长波辐射通量进行建模时，建筑物与植被之间的区别导致建模T _mrt的差异高达3°C。发现木质元素和建筑物的光拦截引起的城市公园中LAI估计的偏差相对较小（3-4％）。然而，本文提出的方法显示了在密集建筑地区估计城市植被LAI的巨大潜力。