机载激光雷达数据伪像:我们目前所知

IF 16.2 1区 地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS IEEE Geoscience and Remote Sensing Magazine Pub Date : 2023-09-01 DOI:10.1109/MGRS.2023.3285261
Wai Yeung Yan
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引用次数: 0

摘要

数据伪影在机载激光雷达点云及其衍生物中很常见[例如,强度图像和数字高程模型(DEM)]。空洞、孔洞、间隙、斑点、噪声和条纹等缺陷不仅会降低激光雷达的视觉质量,还会影响后续的数据驱动分析。尽管在理解这些缺陷方面取得了重大进展,但面对伪影的激光雷达数据的最终用户却因缺乏传播热门进展和分析软件工具的资源而受阻。一系列潜在的内部和外部因素加剧了这种情况,例如天气/大气/地球表面条件、系统设置和激光接收器-发射器轴向对准,这些都是大多数数据伪影问题的基础。在这篇文章中,我们对机载激光雷达点云中常见的伪影及其衍生物进行了统一的概述,并调查了现有文献,以寻求解决这些问题的解决方案。该演示文稿从最终用户的角度出发,有助于在数据收集和处理阶段快速诊断问题并有效地转介到更专业的资源。我们希望这篇文章也能促进科学界、软件开发商和系统制造商的联合,以开发全面的机载激光雷达点云处理包。实现这一目标将进一步增强最终用户的能力,推动该领域向前发展。
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Airborne Lidar Data Artifacts: What we know thus far
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.
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来源期刊
IEEE Geoscience and Remote Sensing Magazine
IEEE Geoscience and Remote Sensing Magazine Computer Science-General Computer Science
CiteScore
20.50
自引率
2.70%
发文量
58
期刊介绍: The IEEE Geoscience and Remote Sensing Magazine (GRSM) serves as an informative platform, keeping readers abreast of activities within the IEEE GRS Society, its technical committees, and chapters. In addition to updating readers on society-related news, GRSM plays a crucial role in educating and informing its audience through various channels. These include:Technical Papers,International Remote Sensing Activities,Contributions on Education Activities,Industrial and University Profiles,Conference News,Book Reviews,Calendar of Important Events.
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