期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 83, 期 -, 页码 58-73出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2016.04.026
关键词
Lidar; High resolution topography; Geodesics; Channel heads; Channel network; Channel morphology
类别
资金
- National Science Foundation [GSS/BCS 1063228, CAREER/EAR-1350336, FESD/EAR-1135427]
- USGS John Wesley Powell Center
- Directorate For Geosciences
- Division Of Earth Sciences [1350336, 1339015] Funding Source: National Science Foundation
Extracting hydrologic and geomorphic features from high resolution topography data is a challenging and computationally demanding task. We illustrate the new capabilities and features of GeoNet, an open source software for the extraction of channel heads, channel networks, and channel morphology from high resolution topography data. The method has been further developed and includes a median filtering operation to remove roads in engineered landscapes and the calculation of hillslope lengths to inform the channel head identification procedure. The software is now available in both MATLAB and Python, allowing it to handle datasets larger than the ones previously analyzed. We present the workflow of GeoNet using three different test cases; natural high relief, engineered low relief, and urban landscapes. We analyze default and user-defined parameters, provide guidance on setting parameter values, and discuss the parameter effect on the extraction results. Metrics on computational time versus dataset size are also presented. We show the ability of GeoNet to objectively and accurately extract channel features in terrains of various characteristics. (C) 2016 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据