@article{c1ae2577a9cd4024ba93e2baa523de77,
title = "OpenCLC: An open-source software tool for similarity assessment of linear hydrographic features",
abstract = "The National Hydrography Dataset (NHD) is a foundational geospatial data source in the United States that enables extensive and diverse environmental research and supports decision-making in numerous contexts. However, the NHD requires regular validation and update given possible inconsistent initial collection and hydrographic changes. Furthermore, systems or tools that use NHD data must manage regular updates that occur within the high-resolution version of the NHD (NHD HR). This research contributes to filling this gap by establishing an open-source software tool named OpenCLC, which automatically identifies matching and mismatching line features between two sets of hydrographic flowlines. Aside from identifying differences among two version of NHD lines, results can be applied to improve the quality of NHD HR content. OpenCLC significantly outperforms the best available commercial off-the-shelf software in computational scalability, and it is made widely available as part of the CyberGIS Toolkit to benefit broad environmental and geospatial science communities.",
keywords = "CyberGIS, Hydrography, Line similarity assessment, National Hydrography Dataset",
author = "Ting Li and Stanislawski, {Lawrence V.} and Tyler Brockmeyer and Shaowen Wang and Ethan Shavers",
note = "Funding Information: This paper and associated materials are based in part upon work supported by the U.S. Geological Survey under grant number G14AC00244 and the National Science Foundation (NSF) under grant numbers 1443080 and 1664119 . The work used the ROGER supercomputer, which is supported by NSF under grant number 1429699 . Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. Assistance received from Anand Padmanabhan and Zewei Xu at the CyberGIS Center for Advanced Digital and Spatial Studies at the University of Illinois at Urbana-Champaign on data processing and software testing is greatly appreciated. Funding Information: This paper and associated materials are based in part upon work supported by the U.S. Geological Survey under grant number G14AC00244 and the National Science Foundation (NSF) under grant numbers 1443080 and 1664119. The work used the ROGER supercomputer, which is supported by NSF under grant number 1429699. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. Assistance received from Anand Padmanabhan and Zewei Xu at the CyberGIS Center for Advanced Digital and Spatial Studies at the University of Illinois at Urbana-Champaign on data processing and software testing is greatly appreciated. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Publisher Copyright: {\textcopyright} 2020 The Authors",
year = "2020",
month = jan,
day = "1",
doi = "10.1016/j.softx.2020.100401",
language = "English (US)",
volume = "11",
journal = "SoftwareX",
issn = "2352-7110",
publisher = "Elsevier BV",
}