Autonomous Collection of Forest Field Reference-The Outlook and a First Step with UAV Laser Scanning
Autonomous Collection of Forest Field Reference-The Outlook and a First Step with UAV Laser Scanning
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DOI：
10.3390/rs9080785
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发表时间：
2017-08-01
期刊：
影响因子：
5
通讯作者：
Wang, Yunsheng
中科院分区：
文献类型：
--
作者：
Jaakkola, Anttoni;Hyyppa, Juha;Wang, Yunsheng
长期以来，人们一直期待找到一种准确和自动收集森林实地数据的紧凑解决方案，并在应用各种遥感技术方面作出了巨大努力。采用先进技术，如基于智能手机的relascope、地面和移动的摄影测量以及激光扫描，取得了稳步进展，从而将其应用推向了实用阶段。然而，所有最近的策略都需要人工操作来进行数据采集，或者将仪器放置在现场（例如，地面激光扫描，TLS）或由操作者携带仪器（例如，个人激光扫描，PLS），这仍然是费力和昂贵的。本文提出了一种新的自主森林野外调查的概念，它包括通过集成无人驾驶飞机（UAV）和自主驾驶的森林冠层上方和内部的数据采集。作为实现这一概念的第一步，评估了小型无人机激光扫描系统自动化树木水平实地测量的可行性。“低成本”Velodyne Puck LITE激光扫描仪用于测试。结果表明，利用上述冠层飞行数据，孤立树和优势树的检测率为100%。由于系统和方法学误差传播，从点云直接测量胸高直径（DBH）的精度在5.5和6.8 cm之间。另一方面，从点云度量估计胸径的精度为2.6厘米，这与使用移动的激光扫描（MLS）、TLS或摄影测量点云进行地面调查获得的精度相当。该方法能以小于20%的RMSE估算出单木断面积、蓄积量和生物量，适用于林木水平的野外参考测量。研究结果表明，基于无人机激光扫描的自动化树木级野外参考文献采集的概念是可行的，但整个课题还需要进一步研究。
A compact solution for the accurate and automated collection of field data in forests has long been anticipated, and tremendous efforts have been made by applying various remote sensing technologies. The employment of advanced techniques, such as the smartphone-based relascope, terrestrial and mobile photogrammetry, and laser scanning, have led to steady progress, thus steering their applications to a practical stage. However, all recent strategies require human operation for data acquisition, either to place the instrument on site (e.g., terrestrial laser scanning, TLS) or to carry the instrument by an operator (e.g., personal laser scanning, PLS), which remained laborious and expensive. In this paper, a new concept of autonomous forest field investigation is proposed, which includes data collection above and inside the forest canopy by integrating an unmanned aircraft vehicle (UAV) with autonomous driving. As a first step towards realizing this concept, the feasibility of automated tree-level field measurements from a mini-UAV laser scanning system is evaluated. A "low-cost" Velodyne Puck LITE laser scanner is applied for the test. It is revealed that, with the above canopy flight data, the detection rate was 100% for isolated and dominant trees. The accuracy of direct measurements on the diameter at breast height (DBH) from the point cloud is between 5.5 and 6.8 cm due to the system and the methodological error propagation. The estimation of DBH from point cloud metrics, on the other hand, showed an accuracy of 2.6 cm, which is comparable to the accuracies obtained with terrestrial surveys using mobile laser scanning (MLS), TLS or photogrammetric point clouds. The estimation of basal area, stem volume and biomass of individual trees could be obtained with less than 20% RMSE, which is adequate for field reference measurements at tree level. Such results indicate that the concept of UAV laser scanning-based automated tree-level field reference collection can be feasible, even though the whole topic requires further research.