Near earth sensing from uncrewed aerial vehicles or UAVs has emerged as a potential approach for fine-scale environmental monitoring. These systems provide a cost-effective and repeatable means to acquire remotely sensed images in unprecedented spatial detail and a high signal-to-noise ratio. It is increasingly possible to obtain both physiochemical and structural insights into the environment using state-of-art light detection and ranging (LiDAR) sensors integrated onto UAVs. Monitoring sensitive environments, such as swamp vegetation in longwall mining areas, is essential yet challenging due to their inherent complexities. Current practices for monitoring these remote and challenging environments are primarily ground-based. This is partly due to an absent framework and challenges of using UAV-based sensor systems in monitoring such sensitive environments. This research addresses the related challenges in developing a LiDAR system, including a workflow for mapping and potentially monitoring highly heterogeneous and complex environments. This involves amalgamating several design components, including hardware integration, calibration of sensors, mission planning, and developing a processing chain to generate usable datasets. It also includes the creation of new methodologies and processing routines to establish a pipeline for efficient data retrieval and generation of usable products. The designed systems and methods were applied to a peat swamp environment to obtain an accurate geo-spatialised LiDAR point cloud. Performance of the LiDAR data was tested against ground-based measurements on various aspects, including visual assessment for generation LiDAR metrices maps, canopy height model, and fine-scale mapping.

无人驾驶飞行器或无人机的近地传感已成为精细环境监测的潜在方法。这些系统提供了一种经济高效且可重复的方法，以前所未有的空间细节和高信噪比获取遥感图像。使用集成在无人机上的最先进的光探测和测距 (LiDAR) 传感器，越来越有可能获得对环境的物理化学和结构洞察力。由于其固有的复杂性，监测敏感环境（例如长壁矿区的沼泽植被）是必不可少的，但也具有挑战性。目前监测这些偏远和具有挑战性的环境的做法主要是基于地面的。这部分是由于缺乏框架和使用基于无人机的传感器系统来监测这种敏感环境的挑战。这项研究解决了开发 LiDAR 系统的相关挑战，包括用于映射和潜在监控高度异构和复杂环境的工作流程。这涉及合并多个设计组件，包括硬件集成、传感器校准、任务规划以及开发处理链以生成可用数据集。它还包括创建新方法和处理例程，以建立有效数据检索和生成可用产品的管道。将设计的系统和方法应用于泥炭沼泽环境，以获得准确的地理空间化 LiDAR 点云。