3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction

To explore the idea of using LiDAR intensity data to assess LWC we normalized (for both angular effects and leaf surface properties) shortwave infrared TLS data (1550 nm). A reflectance model describing both diffuse and specular reflectance was applied to remove strong specular backscatter intensity at a perpendicular angle. Leaves with different surface properties were collected from eight broadleaf plant species for modeling the relationship between LWC and backscatter intensity. Reference reflectors (Spectralon from Labsphere, Inc.) were used to build a look-up table to compensate for incidence angle effects.为探究利用激光雷达（LiDAR）强度数据评估叶片含水量（LWC）的可行性，我们针对角度效应与叶片表面特性，对波长1550 nm的短波红外地面激光扫描（TLS）数据开展归一化处理。我们采用了同时描述漫反射与镜面反射的反射模型，以去除垂直角度下的强镜面后向散射强度。我们从8种阔叶植物中采集了具有不同表面特性的叶片，用于构建叶片含水量（LWC）与后向散射强度之间的关联模型。我们使用蓝菲光学（Labsphere, Inc.）生产的Spectralon参考反射板构建查找表，以补偿入射角效应带来的影响。