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Silva Fennica 1926-1997
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Acta Forestalia Fennica
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Articles containing the keyword 'unpaved forest road'

Category: Research article

article id 10371, category Research article
Katalin Waga, Jukka Malinen, Timo Tokola. (2021). Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets. Silva Fennica vol. 55 no. 1 article id 10371. https://doi.org/10.14214/sf.10371
Keywords: ALS; DEM; forest road quality; reference DEM; unpaved forest road
Highlights: Airborne laser scanning is used to assess forest road quality; High-pulse data analysis classified roads with good performance; Two-step classification further improved the accuracy; A reference surface improved the classification results of the low pulse data; 66–75% of the roads were correctly classified using the reference surface.
Abstract | Full text in HTML | Full text in PDF | Author Info

Two different pulse density airborne laser scanning datasets were used to develop a quality assessment methodology to determine how airborne laser scanning derived variables with the use of reference surface can determine forest road quality. The concept of a reference DEM (Digital Elevation Model) was used to guarantee locally invariant topographic analysis of road roughness. Structural condition, surface wear and flatness were assessed at two test sites in Eastern Finland, calculating surface indices with and without the reference DEM. The high pulse density dataset (12 pulses m–2) gave better classification results (77% accuracy of the correctly classified road sections) than the low pulse density dataset (1 pulse m–2). The use of a reference DEM increased the precision of the road quality classification with the low pulse density dataset when the classification was performed in two-steps. Four interpolation techniques (Inverse Weighted Distance, Kriging, Natural Neighbour and Spline) were compared, and spline interpolation provided the best classification. The work shows that applying a spline reference DEM it is possible to identify 66% of the poor quality road sections and 78% of the good ones. Locating these roads is essential for road maintenance.

  • Waga, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland ORCID https://orcid.org/0000-0003-1496-7012 E-mail: katalin.waga@uef.fi (email)
  • Malinen, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland; Metsäteho Ltd., Vernissakatu 1, FI-01300 Vantaa, Finland ORCID https://orcid.org/0000-0002-5023-1056 E-mail: jukka.malinen@uef.fi
  • Tokola, Faculty of Science and Forestry, University of Eastern Finland, Yliopistokatu 7, FI-80100 Joensuu, Finland E-mail: timo.tokola@uef.fi

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