Journal of Surveying Engineering最新文献

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Amphibious Uncrewed Ground Vehicle for Coastal Surfzone Survey 海岸带勘测两栖无人地面车辆
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2023-01-01 DOI: 10.1061/jsued2.sueng-1381
A. Bak, P. Durkin, B. Bruder, Matthew J. Saenz, M. Forte, K. Brodie
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引用次数: 0
Tolerance for Growing Errors of Observations as a Measure Describing Global Robustness of Msplit Estimation and Providing New Information on Other Methods 作为描述Msplit估计全局鲁棒性和为其他方法提供新信息的观测值增长误差容忍度度量
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2023-01-01 DOI: 10.1061/jsued2.sueng-1451
R. Duchnowski, P. Wyszkowska
{"title":"Tolerance for Growing Errors of Observations as a Measure Describing Global Robustness of Msplit Estimation and Providing New Information on Other Methods","authors":"R. Duchnowski, P. Wyszkowska","doi":"10.1061/jsued2.sueng-1451","DOIUrl":"https://doi.org/10.1061/jsued2.sueng-1451","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58597660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Investigating the Congruence between Gravimetric Geoid Models over India 印度大地水准面重力模型的一致性研究
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2023-01-01 DOI: 10.1061/jsued2.sueng-1382
R. Goyal, S. Claessens, W. Featherstone, O. Dikshit
{"title":"Investigating the Congruence between Gravimetric Geoid Models over India","authors":"R. Goyal, S. Claessens, W. Featherstone, O. Dikshit","doi":"10.1061/jsued2.sueng-1382","DOIUrl":"https://doi.org/10.1061/jsued2.sueng-1382","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58597648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Iterative Optimization Adjustment Method for Ballastless Track Irregularity of High-Speed Railway 高速铁路无砟轨道不平顺度的迭代优化调整方法
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-11-01 DOI: 10.1061/(asce)su.1943-5428.0000406
Yangtenglong Li, Ping Wang, Minyi Cen, Qing He
{"title":"Iterative Optimization Adjustment Method for Ballastless Track Irregularity of High-Speed Railway","authors":"Yangtenglong Li, Ping Wang, Minyi Cen, Qing He","doi":"10.1061/(asce)su.1943-5428.0000406","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000406","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45737197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Houston GNSS Network for Subsidence and Faulting Monitoring: Data Analysis Methods and Products 休斯顿全球导航卫星系统沉降和故障监测网络:数据分析方法和产品
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-11-01 DOI: 10.1061/(asce)su.1943-5428.0000399
Guoquan Wang, Ashley Greuter, Christina M. Petersen, M. Turco
{"title":"Houston GNSS Network for Subsidence and Faulting Monitoring: Data Analysis Methods and Products","authors":"Guoquan Wang, Ashley Greuter, Christina M. Petersen, M. Turco","doi":"10.1061/(asce)su.1943-5428.0000399","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000399","url":null,"abstract":"Harris-Galveston Subsidence District (HGSD), in collaboration with several other agencies, has been operating a dense Global Navigation Satellite System (GNSS) network for subsidence and faulting monitoring within the Greater Houston region since the early 1990s. The GNSS network is designated HoustonNet, comprising approximately 250 permanent GNSS stations as of 2021. This paper documents the methods used to produce position time series, transform coordinates from the global to regional reference frames, identify outliers and steps, analyze seasonal movements, and estimate site velocities and uncertainties. The GNSS positioning methods presented in this paper achieve 2–4-mm RMS accuracy for daily positions in the north–south and east–west directions and 5–8-mm accuracy in the vertical direction within the Greater Houston region. Five-year or longer continuous observations are able to achieve submillimeter-per-year uncertainties (95% confidence interval) for both horizontal and vertical site velocities. Two decades of GNSS observations indicate that Katy in Fort Bend County, Jersey Village in northwestern Harris County, and The Woodlands in southern Montgomery County have been the areas most affected by subsidence (1–2 cm=year) since the 2000s; the overall subsidence rate and the size of subsiding area (>5 mm=year) have been decreasing as a result of the groundwater regulations enforced by HGSD and other local agencies. HoustonNet data and products are released to the public through HGSD. The primary products are the daily East-North-Up (ENU) position time series and site velocities with respect to the International GNSS Service (IGS) Reference Frame 2014 (IGS14), the stable Gulf of Mexico Reference Frame (GOM20), and the stable Houston Reference Frame (Houston20). The ENU position time series with respect to Houston20 are recommended for delineating subsidence and faulting within the Greater Houston region. The ENU time series with respect to GOM20 are recommended for studying subsidence and faulting within the Gulf coastal plain and sea-level changes along the Gulf Coast. The entire HoustonNet data set is reprocessed every a few years with updated positioning software, IGS and regional reference frames, and data analysis tools. We recommend that users use the most recent release of HoustonNet data products and avoid mixing old and new positions. DOI: 10.1061/ (ASCE)SU.1943-5428.0000399. This work is made available under the terms of the Creative Commons Attribution 4.0 International license, https://creativecommons.org/licenses/by/4.0/. Author keywords: Faulting; Global navigation satellite system (GNSS); Houston; Reference frame; Seasonal motion; Subsidence.","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44822022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Dam Settlement Prediction Based on Random Error Extraction and Multi-Input LSTM Network 基于随机误差提取和多输入LSTM网络的大坝沉降预测
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-08-01 DOI: 10.1061/(asce)su.1943-5428.0000400
Yaming Xu, Pai Pan, C. Xing
{"title":"Dam Settlement Prediction Based on Random Error Extraction and Multi-Input LSTM Network","authors":"Yaming Xu, Pai Pan, C. Xing","doi":"10.1061/(asce)su.1943-5428.0000400","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000400","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45373420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
High-Precision Trigonometric Leveling Based on Correction with Atmospheric Refraction Coefficient Model 基于大气折射系数模型校正的高精度三角高程测量
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-08-01 DOI: 10.1061/(asce)su.1943-5428.0000401
Lianhuan Wei, Jiaqi Zhang, Meng Ao, Shanjun Liu, Yachun Mao
{"title":"High-Precision Trigonometric Leveling Based on Correction with Atmospheric Refraction Coefficient Model","authors":"Lianhuan Wei, Jiaqi Zhang, Meng Ao, Shanjun Liu, Yachun Mao","doi":"10.1061/(asce)su.1943-5428.0000401","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000401","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46195377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
First Assessment Results of Surveying Engineering Labs in Immersive and Interactive Virtual Reality 沉浸式交互虚拟现实测量工程实验室首次评估结果
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-02-01 DOI: 10.1061/(asce)su.1943-5428.0000388
D. Bolkas, Jeffrey Chiampi, J. Fioti, Donovan Gaffney
{"title":"First Assessment Results of Surveying Engineering Labs in Immersive and Interactive Virtual Reality","authors":"D. Bolkas, Jeffrey Chiampi, J. Fioti, Donovan Gaffney","doi":"10.1061/(asce)su.1943-5428.0000388","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000388","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49133049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Erratum for “New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model” by Jie Han, Songlin Zhang, and Jingchang Li 韩、张松林、李景昌“变量误差模型中参数的一阶近似精度估计新方法”勘误表
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-02-01 DOI: 10.1061/(asce)su.1943-5428.0000378
Jie Han, Songlin Zhang, Jingchang Li
{"title":"Erratum for “New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model” by Jie Han, Songlin Zhang, and Jingchang Li","authors":"Jie Han, Songlin Zhang, Jingchang Li","doi":"10.1061/(asce)su.1943-5428.0000378","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000378","url":null,"abstract":"","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47564799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The 95% Confidence Interval for GNSS-Derived Site Velocities GNSS衍生站点速度的95%置信区间
IF 1.9 3区 工程技术
Journal of Surveying Engineering Pub Date : 2022-02-01 DOI: 10.1061/(asce)su.1943-5428.0000390
Guoquan Wang
{"title":"The 95% Confidence Interval for GNSS-Derived Site Velocities","authors":"Guoquan Wang","doi":"10.1061/(asce)su.1943-5428.0000390","DOIUrl":"https://doi.org/10.1061/(asce)su.1943-5428.0000390","url":null,"abstract":"Linear trends, or site velocities, derived from global navigation satellite system (GNSS) positional time series have been commonly applied to site stability assessments, structural health monitoring, sea-level rise, and coastal submergence studies. The uncertainty of the velocity has become a big concern for stringent users targeting structural or ground deformation at a few millimeters per year. GNSSderived positional time series are autocorrelated. Consequently, conventional methods for calculating the standard errors of the linear trends result in unrealistically small uncertainties. This article presents an approach to accounting for the autocorrelation with an effective sample size (Neff). A robust methodology has been developed to determine the 95% confidence interval (95%CI) for the site velocities. It is found that the 95%CI fits an inverse power-law relationship over the time span of the time series (vertical direction: 95%CI 1⁄4 5.2T−1.25; east–west or north–south directions: 95%CI 1⁄4 1.8T−1.0). For static GNSS monitoring projects, continuous observations longer than 2.5 and 4 years are recommended to achieve a 95%CI below 1 mm=year for the horizontal and vertical site velocities, respectively; continuous observations longer than 7 years are recommended to achieve a 95%CI below 0.5 mm=year for the vertical land movement rate (subsidence or uplift). The 95%CI from 7-year GNSS time series is equivalent to the 95%CI of the sea-level trend derived from 60-year tide gauge observations. The method and the empirical formulas developed through this study have the potential for broad applications in geosciences, sea-level and coastal studies, and civil and surveying engineering. DOI: 10.1061/(ASCE)SU.1943-5428.0000390. © 2021 American Society of Civil Engineers. Author keywords: Autoregressive model; Effective sample size; Global navigation satellite system (GNSS); Linear trend; Site velocity; Sea-level rise; Uncertainty; 95% confidence interval.","PeriodicalId":54366,"journal":{"name":"Journal of Surveying Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48895048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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