Radiometrically Calibrated Features of Full-Waveform Lidar Point Clouds Based on Statistical Moments

Abstract

Full-waveform lidar has gained increasing attention in 3-D remote sensing and related disciplines during the last decade due to its capability of delivering both geometric and radiometric information in the same spatial resolution. Radiometric information may either be related to the echo, e.g., echo amplitude and width, or to the target itself, e.g., the backscatter cross section (BCS). Echo parameters, often obtained by Gaussian decomposition, as well as target properties, which are (geo)physical properties and therefore independent of data acquisition mission parameters, are considered as additional features of the point cloud generated by laser scanning. The BCS commonly is derived by performing a deconvolution which results in its temporal derivative, the differential backscatter cross-section (dBCS), and subsequent integration. The temporal shape of the dBCS has gained little attention in the literature so far. In this letter, we discuss the derivation of additional target parameters, namely the statistical moments of the respective target dBCS. Besides discussing the applicability of established deconvolution approaches for the extraction of statistical moments in the dBCS, special emphasis is laid on their derivation in B-spline-based deconvolution. Uniform B-splines allow for linear deconvolution and subsequent radiometric calibration. We illustrate the potential of the proposed method by a sample data set stemming from an airborne lidar campaign in complex mountainous terrain.