J. For. Sci., 2016, 62(7):337-344 | DOI: 10.17221/110/2015-JFS

Predicting the earthwork width and determining the annual growth loss due to forest road construction using artificial neural network and ArcGISOriginal Paper

S. Peyrov1, A. Najafi1, A.R. Nourodini2
1 Department of Forestry, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Tehran, Iran
2 Department of Forestry, Faculty of Natural Resources, University of Guilan, Rasht, Iran

The area of forest destruction as well as the annual growth loss due to road construction before constructing a road was predicted. To do this, road cross sections of 88 points along the 10 km proposed road were predicted using Multilayer Perceptron Neural Network with two input parameters of hillside slope and rock share within MATLAB software. Then according to the predicted width, the area of road earthwork as well as the area of roadside with a 10 m width was calculated in ArcGIS software. Finally, by overlaying the inventory network layer on the road map and by knowing the annual growth (m3) for each plot the growth loss of the area of road earthwork was calculated and one-third of the annual growth increment was considered to calculate the growth loss of the roadside. According to the results, for the construction of a 10 km long road in the region, 12.98 ha of forest area is destructed due to road construction, of which 5.36 ha is destructed resulting from earthwork operations and 7.61 ha occurs in the roadside and its growth is influenced by road construction. With the construction of the road, in total, 32.606 m3 of growth will be lost annually, of which 22.221 m3 is due to road earthwork that is completely removed from the forest annual growth cycle and 10.384 m3 of the growth loss belongs to the roadside which is decreased resulting from road construction.

Keywords: area of road earthwork; hillside slope; roadside; rock share

Published: July 31, 2016  Show citation

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Peyrov S, Najafi A, Nourodini AR. Predicting the earthwork width and determining the annual growth loss due to forest road construction using artificial neural network and ArcGIS. J. For. Sci.. 2016;62(7):337-344. doi: 10.17221/110/2015-JFS.
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