A program for cost estimation of forest road construction using engineer's method

Ghajar, Ismael; Najafi, Arezu; Karimimajd, Amir Mohsen; Boston, Kevin; Torabi, S. Ali

doi:10.1080/21580103.2012.759163

Cited by 16 publications

(14 citation statements)

References 6 publications

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“…In order to evaluate each alternative form future landslides point of view, we extracted the values of LS for the all road alternatives from the LSI map. Furthermore, we applied a cost estimation model, initially developed by Ghajar et al (2013) for the Caspian forest, to economically evaluate the road alternatives. The model incorporates five main cost elements in forest roads including clearing operations, embankment, pavement, grading, drainage and stream-crossing structures to calculate the total construction cost calculation.…”

Section: Designing and Assessing Road Network Alternativesmentioning

confidence: 99%

Planning road networks in landslide-prone areas: A case study from the northern forests of Iran

et al. 2015

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Section: Designing and Assessing Road Network Alternativesmentioning

confidence: 99%

Planning road networks in landslide-prone areas: A case study from the northern forests of Iran

et al. 2015

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“…Studies concerning road construction (Ghajar et al 2013), maintenance (Coulter et al 2006) and environmental concerns affecting the placement of roads in forests (Grayson et al 1993;Rummer et al 1997;Forsyth et al 2006;Jordán and Martínez-Zavala 2008. ) show big variety.…”

Section: Introductionmentioning

confidence: 99%

Comparison of High and Low Density Airborne Lidar Data for Forest Road Quality Assessment

Kiss¹,

Malinen²,

Tokola³

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Good quality forest roads are important for forest management. Airborne laser scanning data can help create automatized road quality detection, thus avoiding field visits. Two different pulse density datasets have been used to assess road quality: high-density airborne laser scanning data from Kiihtelysvaara and low-density data from Tuusniemi, Finland. The field inventory mainly focused on the surface wear condition, structural condition, flatness, road side vegetation and drying of the road. Observations were divided into poor, satisfactory and good categories based on the current Finnish quality standards used for forest roads. Digital Elevation Models were derived from the laser point cloud, and indices were calculated to determine road quality. The calculated indices assessed the topographic differences on the road surface and road sides. The topographic position index works well in flat terrain only, while the standardized elevation index described the road surface better if the differences are bigger. Both indices require at least a 1 metre resolution. High-density data is necessary for analysis of the road surface, and the indices relate mostly to the surface wear and flatness. The classification was more precise (31-92%) than on low-density data (25-40%). However, ditch detection and classification can be carried out using the sparse dataset as well (with a success rate of 69%). The use of airborne laser scanning data can provide quality information on forest roads.

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“…However, large areas of forest are destroyed during road construction, which results in both economic losses and environmental changes (Caliskan 2013). For lowvolume forest roads, construction and maintenance of roads are the largest proportion of the total cost of producing timber (Ghajar et al 2013). Therefore, forest road construction must be designed and executed with consideration of economic, environmental, and social requirements (Ozturk and Inan 2010).…”

Section: Introductionmentioning

confidence: 99%

Using remote sensing data to predict road fill areas and areas affected by fill erosion with planned forest road construction: a case study in Kastamonu Regional Forest Directorate (Turkey)

Arıcak

2015

Environ Monit Assess

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Forest roads are essential for transport in managed forests, yet road construction causes environmental disturbance, both in the surface area the road covers and in erosion and downslope deposition of road fill material. The factors affecting the deposition distance of eroded road fill are the slope gradient and the density of plant cover. Thus, it is important to take these factors into consideration during road planning to minimize their disturbance. The aim of this study was to use remote sensing and field surveying to predict the locations that would be affected by downslope deposition of eroding road fill and to compile the data into a geographic information system (GIS) database. The construction of 99,500 m of forest roads is proposed for the Kastamonu Regional Forest Directorate in Turkey. Using GeoEye satellite images and a digital elevation model (DEM) for the region, the location and extent of downslope deposition of road fill were determined for the roads as planned. It was found that if the proposed roads were constructed by excavators, the fill material would cover 910,621 m(2) and the affected surface area would be 1,302,740 m(2). Application of the method used here can minimize the adverse effects of forest roads.

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A program for cost estimation of forest road construction using engineer's method

Cited by 16 publications

References 6 publications

Planning road networks in landslide-prone areas: A case study from the northern forests of Iran

Planning road networks in landslide-prone areas: A case study from the northern forests of Iran

Comparison of High and Low Density Airborne Lidar Data for Forest Road Quality Assessment

Using remote sensing data to predict road fill areas and areas affected by fill erosion with planned forest road construction: a case study in Kastamonu Regional Forest Directorate (Turkey)

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