Abstract Airborne laser scanning (ALS) is a remote sensing technology known for its applicability in natural resources management. By quantifying the three-dimensional structure of vegetation and underlying terrain using laser technology, ALS has been used extensively for enhancing geospatial knowledge in the fields of forestry and ecology. Structural descriptions of vegetation provide a means of estimating a range of ecologically pertinent attributes, such as height, volume, and above-ground biomass. The efficient processing of large, often technically complex datasets requires dedicated algorithms and software. The continued promise of ALS as a tool for improving ecological understanding is often dependent on user-created tools, methods, and approaches. Due to the proliferation of ALS among academic, governmental, and private-sector communities, paired with requirements to address a growing demand for open and accessible data, the ALS community is recognising the importance of free and open-source software (FOSS) and the importance of user-defined workflows. Herein, we describe the philosophy behind the development of the lidR package. Implemented in the R environment with a C/C++ backend, lidR is free, open-source and cross-platform software created to enable simple and creative processing workflows for forestry and ecology communities using ALS data. We review current algorithms used by the research community, and in doing so raise awareness of current successes and challenges associated with parameterisation and common implementation approaches. Through a detailed description of the package, we address the key considerations and the design philosophy that enables users to implement user-defined tools. We also discuss algorithm choices that make the package representative of the ‘state-of-the-art’ and we highlight some internal limitations through examples of processing time discrepancies. We conclude that the development of applications like lidR are of fundamental importance for developing transparent, flexible and open ALS tools to ensure not only reproducible workflows, but also to offer researchers the creative space required for the progress and development of the discipline.

中文翻译：

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LidR：用于分析机载激光扫描 (ALS) 数据的 R 包

摘要 机载激光扫描 (ALS) 是一种遥感技术，以其在自然资源管理中的适用性而闻名。通过使用激光技术量化植被和下伏地形的三维结构，ALS 已被广泛用于增强林业和生态领域的地理空间知识。植被的结构描述提供了一种估算一系列生态相关属性的方法，例如高度、体积和地上生物量。对大型、通常技术上复杂的数据集的有效处理需要专用的算法和软件。ALS 作为提高生态理解工具的持续承诺通常取决于用户创建的工具、方法和方法。由于 ALS 在学术界、政府和私营部门社区中的扩散，为了满足对开放和可访问数据日益增长的需求，ALS 社区正在认识到免费和开源软件 (FOSS) 的重要性以及用户定义工作流程的重要性。在这里，我们描述了lidR 包开发背后的理念。在带有 C/C++ 后端的 R 环境中实施，lidR 是免费、开源和跨平台的软件，旨在为使用 ALS 数据的林业和生态社区提供简单和创造性的处理工作流。我们回顾了研究界使用的当前算法，并通过这样做提高了对与参数化和常见实现方法相关的当前成功和挑战的认识。通过对包的详细描述，我们解决了使用户能够实施用户定义工具的关键考虑因素和设计理念。我们还讨论了使包代表“最先进”的算法选择，并通过处理时间差异的示例强调了一些内部限制。我们得出的结论是，lidR 等应用程序的开发对于开发透明、灵活和开放的 ALS 工具至关重要，不仅可以确保可重复的工作流程，而且还可以为研究人员提供学科进步和发展所需的创造性空间。