Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar.
Rapid, High-Resolution Forest Structure and Terrain Mapping over Large Areas using Single Photon Lidar.
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DOI：
10.1038/srep28277
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发表时间：
2016-06-22
影响因子：
4.6
通讯作者：
Dubayah R
中科院分区：
文献类型：
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作者：
Swatantran A;Tang H;Barrett T;DeCola P;Dubayah R
单光子激光雷达(SPL)是一种用于大面积森林结构和地形快速表征的创新技术。在这里，我们评估来自SPL仪器-高分辨率量子激光雷达系统(HRQLS)的数据，该系统用于绘制美国马里兰州加勒特县的整个地图(1700 平方公里)。我们开发了滤除太阳噪声的新方法，以便能够从SPL点云中推导出森林冠层结构和地面高程。将SPL属性与现场测量和现有的叶状、低点密度离散返回激光雷达数据集进行比较，作为验证的一种手段。我们发现，SPL的冠层和地面特征与离散返回激光雷达相似，尽管在波长和采集周期上有所不同，但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，自动去噪可能具有挑战性，特别是在高反照率表面上，需要严格的仪器校准，以将地面测量偏差减少到可接受的测绘标准。尽管如此，SPL的数据收集效率以及在大范围内快速产生精细三维结构的能力强烈表明，SPL应被视为现有激光雷达系统的一种高效且潜在的成本效益较高的大面积测绘替代方案。
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 km2). 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.