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利用单光子激光雷达对大面积区域进行快速、高分辨率森林结构和地形测绘。

Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar.

作者信息

Swatantran Anu, Tang Hao, Barrett Terence, DeCola Phil, Dubayah Ralph

机构信息

Department of Geographical Sciences, University of Maryland College Park, MD, 20742, USA.

Sigma Space Corporation, 4600 Forbes Blvd, Lanham-Seabrook, MD, 20706, USA.

出版信息

Sci Rep. 2016 Jun 22;6:28277. doi: 10.1038/srep28277.

DOI:10.1038/srep28277
PMID:27329078
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4916424/
Abstract

Single photon lidar (SPL) is an innovative technology for rapid forest structure and terrain characterization over large areas. Here, we evaluate data from an SPL instrument - the High Resolution Quantum Lidar System (HRQLS) that was used to map the entirety of Garrett County in Maryland, USA (1700 km(2)). We develop novel approaches to filter solar noise to enable the derivation of forest canopy structure and ground elevation from SPL point clouds. SPL attributes are compared with field measurements and an existing leaf-off, low-point density discrete return lidar dataset as a means of validation. We find that canopy and ground characteristics from SPL are similar to discrete return lidar despite differences in wavelength and acquisition periods but the higher point density of the SPL data provides more structural detail. Our experience suggests that automated noise removal may be challenging, particularly over high albedo surfaces and rigorous instrument calibration is required to reduce ground measurement biases to accepted mapping standards. Nonetheless, its efficiency of data collection, and its ability to produce fine-scale, three-dimensional structure over large areas quickly strongly suggests that SPL should be considered as an efficient and potentially cost-effective alternative to existing lidar systems for large area mapping.

摘要

单光子激光雷达(SPL)是一项用于大面积快速表征森林结构和地形的创新技术。在此,我们评估了来自一台SPL仪器——高分辨率量子激光雷达系统(HRQLS)的数据,该仪器被用于绘制美国马里兰州加勒特县的全境地图(面积为1700平方千米)。我们开发了新颖的方法来滤除太阳噪声,以便从SPL点云数据中推导森林冠层结构和地面高程。将SPL属性与实地测量数据以及一个现有的落叶期、低点密度离散回波激光雷达数据集进行比较,以此作为验证手段。我们发现,尽管波长和采集周期存在差异,但SPL的冠层和地面特征与离散回波激光雷达相似,不过SPL数据的较高点密度提供了更多的结构细节。我们的经验表明,自动去除噪声可能具有挑战性,尤其是在高反照率表面,并且需要进行严格的仪器校准,以将地面测量偏差降低到可接受的制图标准。尽管如此,其数据采集效率以及在大面积区域快速生成精细尺度三维结构的能力,有力地表明SPL应被视为现有激光雷达系统在大面积制图方面的一种高效且可能具有成本效益的替代方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/0bdaa60f4694/srep28277-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/0637147e8b16/srep28277-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/ebfda0fbc81a/srep28277-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/133a3c5ed6fb/srep28277-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/29218a537854/srep28277-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/16551f132909/srep28277-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/962837b33fe9/srep28277-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/acbc4ab6b534/srep28277-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/0bdaa60f4694/srep28277-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/0637147e8b16/srep28277-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/ebfda0fbc81a/srep28277-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/133a3c5ed6fb/srep28277-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/29218a537854/srep28277-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/16551f132909/srep28277-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/962837b33fe9/srep28277-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/acbc4ab6b534/srep28277-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6022/4916424/0bdaa60f4694/srep28277-f8.jpg

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