Topographic laser scanning is a remote sensing method to create detailed 3D point cloud representations of the Earth's surface. Since data acquisition is expensive, simulations can complement real data given certain premises are met: (i) models of 3D scene and scanner are available and (ii) modelling of the beam-scene interaction is simplified to a computationally feasible while physically realistic level. A number of laser scanning simulators for different purposes exist, which we enrich by presenting HELIOS++. HELIOS++ is an open-source simulation framework for terrestrial static, mobile, UAV-based and airborne laser scanning implemented in C++. The HELIOS++ concept provides a flexible solution for the trade-off between physical accuracy (realism) and computational complexity (runtime, memory footprint), as well as ease of use and of configuration. Features of HELIOS++ include the availability of Python bindings (pyhelios) for controlling simulations, and a range of model types for 3D scene representation. Such model types include meshes, digital terrain models, point clouds and partially transmissive voxels, which are especially useful in laser scanning simulations of vegetation. In a scene, object models of different types can be combined, so that representations spanning multiple spatial scales in different resolutions and levels of detail are possible. HELIOS++ follows a modular design, where the core components of platform, scene, and scanner can be individually interchanged, and easily configured. HELIOS++ further allows the simulation of beam divergence using a subsampling strategy, and is able to create full-waveform outputs as a basis for detailed analysis. We show how HELIOS++ positions among other VLS software in terms of input model support and simulation of beam divergence in a literature survey. We also perform a direct comparison of simulations with DART, where we employ a scene from the Radiative Transfer Model Intercomparison (RAMI). This example shows that HELIOS++ takes about 10 times longer than DART for parsing and preparing the 3D scene, but performs about 314,000 times faster in the beam simulation, achieving 200,000 rays/s. Comparing HELIOS++ to its predecessor, HELIOS, revealed reduced runtimes by up to 99%. Virtually scanned point clouds may be used for a broad range of applications as shown in literature. We could identify four main categories of use cases prevailing at present, which benefit from simulated LiDAR point clouds: data acquisition planning, method evaluation, method training and sensing experimentation. We conclude that a general-purpose LiDAR simulator can be employed for many different scientific applications, as long as it is ensured that the simulation adequately represents reality, which is specific to the given research question.

地形激光扫描是一种遥感方法，用于创建地球表面的详细 3D 点云表示。由于数据采集是昂贵的，如果满足某些前提，模拟可以补充真实数据：(i) 3D 场景和扫描仪的模型可用，以及 (ii) 光束-场景交互的建模被简化到计算上可行的同时物理现实水平。存在许多用于不同目的的激光扫描模拟器，我们通过展示 HELIOS++ 来丰富它们。HELIOS++ 是一个开源仿真框架，用于以 C++ 实现的地面静态、移动、基于无人机和机载激光扫描。HELIOS++ 概念为物理精度（真实性）和计算复杂性（运行时、内存占用）之间的权衡提供了灵活的解决方案，以及易于使用和配置。HELIOS++ 的特性包括 Python 绑定的可用性（幽门螺杆菌) 用于控制模拟，以及用于 3D 场景表示的一系列模型类型。此类模型类型包括网格、数字地形模型、点云和部分透射体素，它们在植被的激光扫描模拟中特别有用。在一个场景中，可以组合不同类型的对象模型，从而以不同的分辨率和细节级别跨越多个空间尺度的表示是可能的。HELIOS++采用模块化设计，平台、场景、扫描仪的核心组件可以单独互换，配置简单。HELIOS++ 进一步允许使用二次采样策略模拟光束发散，并能够创建全波形输出作为详细分析的基础。我们在文献调查中展示了 HELIOS++ 在输入模型支持和光束发散模拟方面如何在其他 VLS 软件中定位。我们还使用 DART 对模拟进行了直接比较，其中我们采用了辐射传输模型比对 (RAMI) 中的场景。此示例显示，HELIOS++ 解析和准备 3D 场景所需的时间比 DART 长约 10 倍，但在光束模拟中的执行速度约快 314,000 倍，达到 200,000 射线/秒。将 HELIOS++ 与其前身 HELIOS 进行比较，发现运行时间减少了 99%。虚拟扫描的点云可用于广泛的应用，如文献所示。我们可以确定目前流行的四大类用例，它们受益于模拟的 LiDAR 点云：数据采集规划、方法评估、方法训练和传感实验。我们得出的结论是，通用 LiDAR 模拟器可用于许多不同的科学应用，只要确保模拟充分代表特定于给定研究问题的现实。