2016
DOI: 10.3188/szf.2016.0136
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Der Datensatz «Walderschliessungsstrassen 2013» des Schweizerischen Landesforstinventars

Abstract: The Swiss National Forest Inventory dataset «Forest Access Roads 2013» Information on forest accessibility is important for forest management. For example, it helps to determine the potential wood supply and identify areas difficult to access. In 2013–2014, a survey was conducted in Switzerland to update the Forest Access Roads geo-dataset within the framework of the Swiss National Forest Inventory (NFI). The resulting nationwide dataset contains valuable information on truck-accessible forest r… Show more

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Cited by 4 publications
(2 citation statements)
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“…However, this dataset currently does not contain information on road width, bearing capacity and surface material relevant to the usability for forestry operations. This information has been collected by the NFI in an interview survey with foresters of all foresting districts in every inventory cycle since 1983 (Brassel and Lischke 2001;Fraefel and Fischer 2019;Müller et al 2016). The resulting dataset consists of the swissTLM 3D geometries and additional attributes from the survey.…”
Section: Input Datamentioning
confidence: 99%
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“…However, this dataset currently does not contain information on road width, bearing capacity and surface material relevant to the usability for forestry operations. This information has been collected by the NFI in an interview survey with foresters of all foresting districts in every inventory cycle since 1983 (Brassel and Lischke 2001;Fraefel and Fischer 2019;Müller et al 2016). The resulting dataset consists of the swissTLM 3D geometries and additional attributes from the survey.…”
Section: Input Datamentioning
confidence: 99%
“…Vector datasets included the NFI forest road dataset with information indicating the type of truck that can be used on each road segment and a point dataset giving connection points where the roads from the forest connect to the superordinate road network (Fig. 4; Müller et al (2016)).…”
Section: Input Datamentioning
confidence: 99%