Radiometric correction of multispectral Lidar data

现有的LiDAR传感器利用单频激光脉冲进行数据采集。多光谱机载LiDAR传感器最近被制造用于获取不同红外光谱中的数据。由于系统和环境引起的失真，从这种LiDAR传感器收集的数据具有系统性和随机性噪声。为了最大限度地利用多光谱激光雷达传感器进行表面分类和生物物理指标的推导，某些数据校准和校正方案应适用于收集的激光雷达数据。该ENGAGE赠款有助于调查多光谱LiDAR传感器收集的数据的辐射质量。此外，赠款提出了实用的数据校正方案的基础上辐射校正和归一化模型。该项目将有助于部署

Existing LiDAR sensors utilize single frequency of laser pulse for data acquisition. Multispectral airborne LiDAR sensors are recently manufactured to acquire data in different infrared spectrum. Due to the system and environmental-induced distortions, the data collected from such LiDAR sensors has systematic and random noises. In order to maximize the benefits of using the multispectral LiDAR sensor for surface classification and derivation of bio-physical indices, certain data calibration and correction schemes should be applied to the collected LiDAR data. This ENGAGE grant facilitates the efforts to investigate the radiometric quality of the data collected by the multispectral LiDAR sensor. In addition, the grant proposing practical data correction scheme based on radiometric correction and normalization models. The project would facilitate the deployment