高程数据源对二维水力建模的影响

IF 2 4区 地球科学 Q2 GEOCHEMISTRY & GEOPHYSICS Acta Geophysica Pub Date : 2016-12-02 DOI:10.1515/acgeo-2016-0030
K. Bakuła, Mateusz StĘpnik, Z. Kurczynski
{"title":"高程数据源对二维水力建模的影响","authors":"K. Bakuła, Mateusz StĘpnik, Z. Kurczynski","doi":"10.1515/acgeo-2016-0030","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to analyse the influence of the source of various elevation data on hydraulic modelling in open channels. In the research, digital terrain models from different datasets were evaluated and used in two-dimensional hydraulic models. The following aerial and satellite elevation data were used to create the representation of terrain–digital terrain model: airborne laser scanning, image matching, elevation data collected in the LPIS, EuroDEM, and ASTER GDEM. From the results of five 2D hydrodynamic models with different input elevation data, the maximum depth and flow velocity of water were derived and compared with the results of the most accurate ALS data. For such an analysis a statistical evaluation and differences between hydraulic modelling results were prepared. The presented research proved the importance of the quality of elevation data in hydraulic modelling and showed that only ALS and photogrammetric data can be the most reliable elevation data source in accurate 2D hydraulic modelling.","PeriodicalId":50898,"journal":{"name":"Acta Geophysica","volume":"64 1","pages":"1176-1192"},"PeriodicalIF":2.0000,"publicationDate":"2016-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/acgeo-2016-0030","citationCount":"9","resultStr":"{\"title\":\"Influence of Elevation Data Source on 2D Hydraulic Modelling\",\"authors\":\"K. Bakuła, Mateusz StĘpnik, Z. Kurczynski\",\"doi\":\"10.1515/acgeo-2016-0030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to analyse the influence of the source of various elevation data on hydraulic modelling in open channels. In the research, digital terrain models from different datasets were evaluated and used in two-dimensional hydraulic models. The following aerial and satellite elevation data were used to create the representation of terrain–digital terrain model: airborne laser scanning, image matching, elevation data collected in the LPIS, EuroDEM, and ASTER GDEM. From the results of five 2D hydrodynamic models with different input elevation data, the maximum depth and flow velocity of water were derived and compared with the results of the most accurate ALS data. For such an analysis a statistical evaluation and differences between hydraulic modelling results were prepared. The presented research proved the importance of the quality of elevation data in hydraulic modelling and showed that only ALS and photogrammetric data can be the most reliable elevation data source in accurate 2D hydraulic modelling.\",\"PeriodicalId\":50898,\"journal\":{\"name\":\"Acta Geophysica\",\"volume\":\"64 1\",\"pages\":\"1176-1192\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2016-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1515/acgeo-2016-0030\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Geophysica\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1515/acgeo-2016-0030\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Geophysica","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1515/acgeo-2016-0030","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 9

摘要

本文的目的是分析各种高程数据来源对明渠水力建模的影响。在研究中,对来自不同数据集的数字地形模型进行了评估,并将其用于二维水力模型。使用以下航空和卫星高程数据来创建地形数字地形模型的表示:机载激光扫描,图像匹配,在LPIS, EuroDEM和ASTER GDEM中收集的高程数据。从5个不同输入高程数据的二维水动力模型的结果出发,导出了最大水深和水流速度,并与最精确的ALS数据结果进行了比较。为了进行这样的分析,准备了统计评估和水力模拟结果之间的差异。本研究证明了高程数据质量在水力建模中的重要性,并表明只有ALS和摄影测量数据才能成为精确的二维水力建模中最可靠的高程数据源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Influence of Elevation Data Source on 2D Hydraulic Modelling
The aim of this paper is to analyse the influence of the source of various elevation data on hydraulic modelling in open channels. In the research, digital terrain models from different datasets were evaluated and used in two-dimensional hydraulic models. The following aerial and satellite elevation data were used to create the representation of terrain–digital terrain model: airborne laser scanning, image matching, elevation data collected in the LPIS, EuroDEM, and ASTER GDEM. From the results of five 2D hydrodynamic models with different input elevation data, the maximum depth and flow velocity of water were derived and compared with the results of the most accurate ALS data. For such an analysis a statistical evaluation and differences between hydraulic modelling results were prepared. The presented research proved the importance of the quality of elevation data in hydraulic modelling and showed that only ALS and photogrammetric data can be the most reliable elevation data source in accurate 2D hydraulic modelling.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Acta Geophysica
Acta Geophysica 地学-地球化学与地球物理
CiteScore
3.90
自引率
13.00%
发文量
251
审稿时长
5.3 months
期刊介绍: Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.
期刊最新文献
Correction to: Groundwater-level prediction in Visakhapatnam district, Andhra Pradesh, India, using Bayesian Neural Networks Investigating the spatial and temporal variation of aerosols and cloud parameters over South Asia using remote sensing Novel hybrid computational intelligence approaches for predicting daily solar radiation SMAP products for prediction of surface soil moisture by ELM network model and agricultural drought index Identification of sediment–basement structure in West Papua province, Indonesia, using gravity and magnetic data inversion as an Earth’s crust stress indicator
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1