The popularity of LiDAR devices and sensor technology has gradually empowered users from autonomous driving to forest monitoring, and research on 3D LiDAR has made remarkable progress over the years. Unlike 2D images, whose focused area is visible and rich in texture information, understanding the point distribution can help companies and researchers find better ways to develop point-based 3D applications. In this work, we contribute an unreal-based LiDAR simulation tool and a 3D simulation dataset named LiDAR-Forest, which can be used by various studies to evaluate forest reconstruction, tree DBH estimation, and point cloud compression for easy visualization. The simulation is customizable in tree species, LiDAR types and scene generation, with low cost and high efficiency.

翻译：激光雷达设备与传感器技术的普及逐步赋能从自动驾驶到森林监测的各类用户，近年来3D激光雷达研究已取得显著进展。与聚焦区域可见且纹理信息丰富的二维图像不同，理解点分布特性能够帮助企业与研究人员探索更优的基于点云的3D应用开发路径。本文贡献了一套基于Unreal引擎的激光雷达仿真工具及名为LiDAR-Forest的三维仿真数据集，可被多领域研究用于评估森林重建、树木胸径估算及面向可视化简易化的点云压缩任务。该仿真支持树种类型、激光雷达型号及场景生成的定制化配置，兼具低成本与高效率优势。