Airborne LiDAR data artifacts : what we know thus far

Abstract

Data artifacts are a common occurrence in airborne lidar point clouds and their derivatives [e.g., intensity images and digital elevation models (DEMs)]. Defects, such as voids, holes, gaps, speckles, noise, and stripes, not only degrade lidar visual quality but also compromise subsequent data-driven analyses. Despite significant progress in understanding these defects, end users of lidar data confronted with artifacts are stymied by the scarcities of both resources for the dissemination of topical advances and analytic software tools. The situation is exacerbated by the wide-ranging array of potential internal and external factors, with examples including weather/atmospheric/Earth surface conditions, system settings, and laser receiver–transmitter axial alignment, that underlie most data artifact issues. In this article, we provide a unified overview of artifacts commonly found in airborne lidar point clouds and their derivatives and survey the existing literature for solutions to resolve these issues. The presentation is from an end-user perspective to facilitate rapid diagnoses of issues and efficient referrals to more specialized resources during data collection and processing stages. We hope that the article can also serve to promote coalescence of the scientific community, software developers, and system manufacturers for the ongoing development of a comprehensive airborne lidar point cloud processing bundle. Achieving this goal would further empower end users and move the field forward.