J. For. Sci., 2016, 62(6):264-268 | DOI: 10.17221/9/2016-JFS

Determining an optimal path for forest road construction using Dijkstra's algorithmOriginal Paper

A. Parsakhoo, M. Jajouzadeh
Department of Forestry, Faculty of Forest Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

From an economic point of view a well-designed road path with the minimum construction cost is an optimal path that can be found using Dijkstra's algorithm. In this study Dijkstra's algorithm that consisted of nodes and links was used to optimize the road path in a broadleaved forest. The lower the cost, the greater the chance that the link will get routed. The road construction cost depends on the length of links, longitudinal gradient of links, side slope of the terrain and unit cost of the link construction. In general, the construction cost of each link increased with increasing length of the link, side slope gradient and longitudinal gradient. The total length and mean construction cost of optimal path were 530 m and 18.18 USD.m-1, respectively. Based on the analysis, we found that Dijkstra's algorithm is feasible in selecting an optimal path according to the construction cost of forest road.

Keywords: selecting path; nodes; links; Nahar Khvoran forest

Published: June 30, 2016  Show citation

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Parsakhoo A, Jajouzadeh M. Determining an optimal path for forest road construction using Dijkstra's algorithm. J. For. Sci. 2016;62(6):264-268. doi: 10.17221/9/2016-JFS.
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References

  1. Ahuja R.K., Mehlhorn K.O., James B., Robert E. (1990): Faster algorithms for the shortest path problem. Journal of Association for Computing Machinery, 37: 213-223. Go to original source...
  2. Akbarimehr M., Naghdi R. (2012): Determination of most appropriate distance between water diversions on skid trails in the mountainous forest, north of Iran. Catena, 88: 68-72. Go to original source...
  3. Cheng M.Y., Chang G.L. (2001): Automating utility route design and planning through GIS. Automation in Construction, 10: 507-516. Go to original source...
  4. Contreras M., Chung W. (2007): A computer approach to finding an optimal log landing location and analyzing influencing factors for ground-based timber harvesting. Canadian Journal of Forest Research, 37: 276-292. Go to original source...
  5. Devlin G., McDonnell K., Ward S. (2008): Timber haulage routing in Ireland: An analysis using GIS and GPS. Journal of Transport Geography, 16: 63-72. Go to original source...
  6. Dijkstra E.W. (1959): A note on two problems in connation with graphs. Numerische Mathematic, 1: 269-271. Go to original source...
  7. Heralt L. (2002): Using the ROADENG system to design an optimum forest road variant aimed at the minimization of negative impacts on the natural environment. Journal of Forest Science, 48: 361-365. Go to original source...
  8. Ilayaraja K. (2013): Road network analysis in Neyveli Township, Cuddalore District by using Quantum GIS. Indian Journal of Computer Science and Engineering, 4: 56-61.
  9. Kaufman D.E., Smith R.L. (1993): Fastest paths in timedependent networks for intelligent vehicle-highway systems application. Journal of Intelligent Transportation Systems, 1: 1-11. Go to original source...
  10. Kooshki M., Hayati E., Rafatnia N., Taghi Ahmadi M. (2012): Using GIS to evaluate and design skid trails for forest products. Taiwan Journal of Forest Science, 27: 117-124.
  11. Möhring R.H., Schilling H., Schütz B., Wagner D., Willhalm T. (2006): Partitioning graphs to speedup Dijkstra's algorithm. ACM Journal of Experimental Algorithmics, 11: 2-8. Go to original source...
  12. Rees W.G. (2004): Least-cost paths in mountainous terrain. Computers & Geosciences, 30: 203-209. Go to original source...
  13. Rogers L.W. (2005): Automating contour-based route projection for preliminary forest road designs using GIS. [MSc Thesis.] Seattle, University of Washington: 78.
  14. Tavankar F. (2013): Effect of forest management on density and species diversity of natural regeneration in Hyrcanian lowland forests, north of Iran. International Journal of Agriculture and Crop Sciences, 5: 1941-1945.
  15. Wang Z., Crowcroft J. (1992): Analysis of shortest-path routing algorithms in a dynamic network environment. ACM Computer Communication Review, 22: 63-71. Go to original source...
  16. Wang Z., Zlatanova S., Moreno A., Oosterom P., Toro C. (2014): A data model for route planning in the case of forest fires. Computers & Geosciences, 68: 1-10. Go to original source...
  17. Xie F., Levinson D.M. (2006): Measuring the structure of road networks. Geographical Analysis, 39: 336-356. Go to original source...
  18. Zhan F., Benjamin N., Charles E. (1998): Shortest path algorithms: An evaluation using real road networks. Transportation Science, 32: 65-73. Go to original source...

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