Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data

doi:10.2172/1054709

GSTDTAP > 地球科学

DOI	10.2172/1054709
报告编号	INL/EXT-12-26969
来源ID	OSTI ID: 1054709
	Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data
	Danny L. Anderson
	2012-05-01
出版年	2012
语种	英语
国家	美国
领域	地球科学
英文摘要	Detailed hydrographic feature extraction from high-resolution light detection and ranging (LiDAR) data is investigated. Methods for quantitatively evaluating and comparing such extractions are presented, including the use of sinuosity and longitudinal root-mean-square-error (LRMSE). These metrics are then used to quantitatively compare stream networks in two studies. The first study examines the effect of raster cell size on watershed boundaries and stream networks delineated from LiDAR-derived digital elevation models (DEMs). The study confirmed that, with the greatly increased resolution of LiDAR data, smaller cell sizes generally yielded better stream network delineations, based on sinuosity and LRMSE. The second study demonstrates a new method of delineating a stream directly from LiDAR point clouds, without the intermediate step of deriving a DEM. Direct use of LiDAR point clouds could improve efficiency and accuracy of hydrographic feature extractions. The direct delineation method developed herein and termed âmDnâ, is an extension of the D8 method that has been used for several decades with gridded raster data. The method divides the region around a starting point into sectors, using the LiDAR data points within each sector to determine an average slope, and selecting the sector with the greatest downward slope to determine the direction of flow. An mDn delineation was compared with a traditional grid-based delineation, using TauDEM, and other readily available, common stream data sets. Although, the TauDEM delineation yielded a sinuosity that more closely matches the reference, the mDn delineation yielded a sinuosity that was higher than either the TauDEM method or the existing published stream delineations. Furthermore, stream delineation using the mDn method yielded the smallest LRMSE.
英文关键词	Feature Extraction Hydrology LiDAR Light Detection and Ranging Stream Channel Delineation
URL	查看原文
来源平台	US Department of Energy (DOE)
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/5636
专题	地球科学
推荐引用方式 GB/T 7714	Danny L. Anderson. Detailed Hydrographic Feature Extraction from High-Resolution LiDAR Data,2012.