| 引用本文: | 罗达，林杭生，金钊，郑涵，宋怡，冯立，郭庆华.2019.无人机数字摄影测量与激光雷达在地形地貌与地表覆盖研究中的应用及比较[J].地球环境学报,10(3):213-226 |
| LUO Da, LIN Hangsheng, JIN Zhao, ZHENG Han, SONG Yi, FENG Li, GUO Qinghua.2019.Applications of UAV digital aerial photogrammetry and LiDAR in geomorphology and land cover research[J].Journal of Earth Environment,10(3):213-226 |
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| 无人机数字摄影测量与激光雷达在地形地貌与地表覆盖研究中的应用及比较 |
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罗达，林杭生，金钊，郑涵，宋怡，冯立，郭庆华
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1.中国科学院地球环境研究所 黄土与第四纪地质国家重点实验室，西安 710061
2.中国科学院大学，北京 100049
3. Department of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA 16802, USA
4.中国科学院第四纪科学与全球变化卓越创新中心，西安 710061
5.长安大学 环境科学与工程学院 旱区地下水与生态效应教育部重点实验室，西安 710054
6.中国科学院植物研究所植被与环境变化国家重点实验室，北京 100093
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| 摘要: |
| 无人机数字摄影测量（UAV-DAP）与激光雷达（LiDAR）凭借其机动灵活、高效便捷和高分辨率的特点，在地形地貌、生态监测、工程勘察、环境规划、林业资源清查等领域得到广泛应用。本文针对数字摄影测量与激光雷达的技术特征和应用趋势，着重比较两者在数据采集、数据处理、应用领域以及成本耗费等方面的区别，分析了两种技术在林业资源清查、地形地貌研究、灾害防控等领域的最新应用动态，并且基于两者的技术特点和发展动态提出了进一步的可能应用前景。基于运动结构重建算法的数字摄影测量技术获得的数字地表模型在一定条件下可以达到激光雷达技术的超高空间分辨率程度（如0.2 m×0.2 m），但是数字摄影无法穿透植被冠层，而激光雷达可以较好地穿透植被层从而获取植被及地表信息。然而数字摄影测量技术设备简单、操作方便，成本低廉，并具有较高的空间分辨率，因而能够和高精度、高耗费、大数据量的激光雷达技术形成优势互补。无人机数字摄影测量与激光雷达技术是林业资源清查、地形地貌研究、灾害防控等领域在快速响应、高精度调查、多时期扫描等方面进一步发展的重要突破口。 |
| 关键词: 无人机 数字摄影测量 激光雷达 地形地貌 地表覆盖 |
| DOI：10.7515/JEE181008 |
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| 基金项目:国家自然科学基金项目（41790444，31700414） |
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| Applications of UAV digital aerial photogrammetry and LiDAR in geomorphology and land cover research |
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LUO Da, LIN Hangsheng, JIN Zhao, ZHENG Han, SONG Yi, FENG Li, GUO Qinghua
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1. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. Department of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA 16802, USA
4. Center for Excellence in Quaternary Science and Global Change, Chinese Academy of Sciences, Xi’an 710061, China
5. Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Environmental Science and Engineering, Chang’an University, Xi’an 710054, China
6. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
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| Abstract: |
| Background, aim, and scope The unmanned aerial vehicle (UAV) digital aerial photogrammetry (DAP) and aerial lidar scanning (ALS) have been widely applied in geomorphology research, ecosystem monitoring, engineering investigation, environmental planning, and forest inventory due to their advantages of high flexibility, high efficiency, and high resolution. Photogrammetry is the science of measuring ranges from photographs, especially for recovering the space positions of optical surface points. Photogrammetry can be dated back to mid-19th century when it was the beginning of modern photography. LiDAR (Light Detection and Ranging) is a ranging technique that measures distance to a target by illuminating the target with pulsed laser light and measuring the reflected pulse with a sensor. At the end of 20th century, photogrammetry was caught up by LiDAR because of its series of shortcomings, such as heavy equipment, low efficiency, and high expense. It did not take long before LiDAR went beyond photogrammetry in many applications. However, photogrammetry came back to the stage due to the fast development of small UAV, digital imaging devices, computational advance, photogrammetry algorithm, and related software development during the past decade. In this study, we aim to compare DAP and ALS and discuss their future trends. Materials and methods This paper reviews current major advantages, applications and perspectives of UAV DAP and ALS. We briefly analyzed the fundamental techniques and principles of DAP and ALS through typical research and study cases. We focused on the differences between these two technologies in data acquisition, data processing, flight planning, cost, advantages, and applications through synthesizing published scientific results as well as practical operational considerations. Results The UAV remote sensing technologies, including digital aerial photogrammetry, aerial lidar scanning, and high spectrum imaging, have provided a flexible platform for terrain- and vegetation-based surface observations. The resolution of DAP can be equal to that of ALS, and the former is much more flexible and economical. Discussion ALS needs much more complex facilities than DAP to launch an aerial survey, which is difficult and expensive to operate and mostly contracted out to professional companies. In contrast, DAP is rather easy, for a small UAV with a digital camera can carry out an entire aerial survey in short time. The data processing of ALS is “direct” due to the raw outcome of ALS is point cloud. While DAP needs to extract point clouds from aligned images in the first place, the whole process is rather efficient owing to the Sf M (structure from motion) algorithm based professional software, which mostly have applied the CUDA (compute unified device architecture) techniques to accelerate the whole processing. DAP and ALS have been applied to forest inventory, geomorphology evolution, glacier change, gully erosion, and many other fields, and the resolution of derived DSM (digital surface model), DEM (digital terrain model), CHM (canopy height model) can be comparable between DAP and ALS, though ALS has more advantages in high resolution research. Conclusions UAV-based DAP and ALS technologies have four features: quick response, quick deployment, quick result, and high resolution. DAP and ALS complement each other in topography study, landform research, gully erosion, glacier change, forest inventory, and ecosystem survey. These two technologies plus high spectrum imaging offer significant complement to earth surface observations in satellite-based remote sensing, which often has limitations in spatial and temporal resolutions. The resolution of Sf M-based DAP results can be as high as 0.5 m×0.5 m and even 0.2 m×0.2 m, which makes DAP competitive to ALS. But DAP cannot take the place of ALS as lidar can penetrate tree canopy and retrieve point clouds of terrain surface and subjects above the surface, such as trees and buildings. DAP must be carried out in a bright environment, which means a sunny day, while ALS aerial survey can be conducted in a cloudy day. The Sf M-based DAP requires photos having enough overlapping areas, 30% to 50%, to ensure right alignment. However, DAP has a vital advantage over ALS in terms of cost (the cost of the former can be one third of the latter). A small UAV (such as DJI phantom 4) with digital camera, which is only 1280 grams, can carry out a DAP aerial survey in a short time, whereas a lidar sensor can be twice the weight of a DJI phantom 4. It is quicker and easier for DAP to operate in scenario response, aerial deployment, and result presentation than those of ALS. DAP technology can complement ALS in geomorphology research in the Loess Plateau, and the former can take the place under certain circumstances. DAP can acquire rather “real” terrain surface data in the Loess Plateau during winter and early spring when slopes and gullies are covered with sparse trees. With the help of historical high-resolution terrain data (lidar-derived DEM), the DAP results can be more accurate when generating DSM, DEM, and CHM. Recommendations and perspectives DAP and ALS have competed over years. These two technologies have contributed revolutionary changes in observation and quantification of the Earth’s surface study. Consequently, DAP and ALS offer tremendous opportunities in complementary ways in forest inventory, ecosystem survey, geomorphology investigation, and land cover research. |
| Key words: UAV digital photogrammetry LiDAR geomorphology land cover |
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