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Evaluating the effects of physiographic parameters on the road cross section in mountain forests (Case study: northern forests of Iran)

Author

Listed:
  • S. Peyrov

    (Faculty of Natural Resources, College of Natural Resources, Tarbiat Modares University, Iran)

  • A. Najafi

    (Faculty of Natural Resources, Tarbiat Modares University, Iran)

  • J. Nourizadeh

    (Faculty of Information Technology, Qom IT University, Iran)

Abstract

Road cross section, as one the main effective factors in relation to fill and cut volume, was effective in costs and disturbance of forest road constructions. In this research, the effect of a few physiographic parameters on forest road cross section was evaluated. For this purpose, 192 cross sections on forest roads were delineated selectively in mountain forests in the north of Iran. The physiographic factors including elevation, hillside slope, slope aspect, rock base, and soil texture as well as cross section width were measured. After evaluating the data in terms of normality and homogeneity, it was analysed by Spearman's and Pearson's correlation tests using SPSS20. One-way ANOVA, two-way ANOVA, and Duncan grouping tests were used to determine the effect of the above-mentioned factors both separately and simultaneously. Results showed that the parameters including hillside slope, rock base, and soil texture had a significant effect. Elevation was recognized as a regional parameter due to the lack of any relationship with cross section. There was no significant relation between slope aspect and cross section. The hillside slope was defined as the most effective parameter on the cross section.

Suggested Citation

  • S. Peyrov & A. Najafi & J. Nourizadeh, 2016. "Evaluating the effects of physiographic parameters on the road cross section in mountain forests (Case study: northern forests of Iran)," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 62(1), pages 1-7.
    • Handle: RePEc:caa:jnljfs:v:62:y:2016:i:1:id:89-2015-jfs
    DOI: 10.17221/89/2015-JFS
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    Cited by:

    1. S. Peyrov & A. Najafi & A.R. Nourodini, 2016. "Predicting the earthwork width and determining the annual growth loss due to forest road construction using artificial neural network and ArcGIS," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 62(7), pages 337-344.

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