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Assessing the quality and reliability of visual estimates in determining plant cover on railway embankments
Dalarna University, School of Technology and Business Studies, Computer Engineering.
Dalarna University, School of Technology and Business Studies, Information Systems.ORCID iD: 0000-0003-4812-4988
2016 (English)In: Web Information Systems Engineering – WISE 2016: 17th International Conference, Shanghai, China, November 8-10, 2016, Proceedings, Part II / [ed] Wojciech Cellary, Mohamed F. Mokbel, Jianmin Wang, Hua Wang, Rui Zhou, Yanchun Zhang, 2016, Vol. 10042, 404-410 p.Conference paper, Published paper (Refereed)
Abstract [en]

This study has investigated the quality and reliability of manual assessments on railway embankments within the domain of railway maintenance. Manually inspecting vegetation on railway embankments is slow and time consuming. Maintenance personnel also require extensive knowledge of the plant species, ecology and bio-diversity to be able to recommend appropriate maintenance action. The overall objective of the study is to investigate the reliable nature of manual inspection routines in favour an automatic approach. Visual estimates of plant cover reported by domain experts’ have been studied on two separate railway sections in Sweden. The first study investigated visual estimates using aerial foliar cover (AFC) and sub-plot frequency (SF) methods to assess the plant cover on a railway section in Oxberg, Alvdalsbanan, Sweden. The second study investigated visual estimates using aerial canopy cover method on a railway section outside Vetlanda, Sweden. Visual estimates of the domain experts were recorded and analysis-of-variance (ANOVA) tests on the mean estimates were investigated to see whether if there were disagreements between the raters’. ICC(2, 1) was used to study the differences between the estimates. Results achieved in this work indicate statistically significant differences in the mean estimates of cover (p < 0.05) reported by the domain experts on both the occasions.

Place, publisher, year, edition, pages
2016. Vol. 10042, 404-410 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10042
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Complex Systems – Microdata Analysis; Complex Systems – Microdata Analysis, Automatisk detektering och karakterisering av vegetation längs järnvägen
Identifiers
URN: urn:nbn:se:du-23463DOI: 10.1007/978-3-319-48743-4_33ISI: 000389505500033ISBN: 978-3-319-48742-7 (print)ISBN: 978-3-319-48743-4 (electronic)OAI: oai:DiVA.org:du-23463DiVA: diva2:1049146
Conference
17th International Conference on Web Information Systems Engineering – WISE 2016
Available from: 2016-11-23 Created: 2016-11-23 Last updated: 2017-03-31Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
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