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Analytic methods – Analitičke metode
Computation of mean extraction distance – Izračun srednje udaljenosti privlačenja drva
The most commonly used definitions of the mean extraction distance are those proposed by Dietz et al. (1984): theoretical mean extraction distance (SD0), shortest mean extraction distance (SDs) and real mean extraction distance (SDe), defining the total correction factor (kt) as the product between the extraction correction factor and the network correction factor.
In Romania, Amzica (1967; 1971) highlighted the importance of considering the most suitable harvesting systems for local conditions for determining the optimum forest road density. Bereziuc (1980; 1981) approached the issue of forest road network optimization in correlation with the reduction of the mean extraction distance. Olteanu (1985) focused on the characteristics of the structure indices of the forest road networks in hilly regions of Romania, while Ciubotaru (1996) addressed the topic of extraction distance at the harvesting plot level. The following formulas gathered from literature were used inthis study, assuming that timber is extracted at the landing areas located at the road side, which is the most commonly used practice in Romanian forests:
Ciubotaru (1996) and Pentek et al. (2005) used the method of centre of gravity for determining the real mean extraction distance (), as a weighted arithmetical mean of the extraction distances from each centre of gravity of the forest management units to the closest forest road (SDei) and the allowable cut of timber (Vi) from each unit. Ciubotaru (1996) showed the role of sinuosity and elongation of skid trails for the accurate determination of real mean extraction distance, proposing the following formulas:
where: SD0i – corrected extraction distance for management unit i, in m; SDo – theoretical extraction distance measured on map, in m; α – average side slope in the management unit, in degrees; kss – coefficient of skid trail sinuosity; kse – coefficient of skid trail path elongation; kt – total correction factor.
Correction factors – Faktori korekcije srednje udaljenosti privlačenja
The network correction factor (kn) reflects the adjustments owed to the geometry and unevenness of road layout, while the extraction correction factor (ks) refers to the sinuosity and slope variation of the skid trail network (Segebaden 1964).
The influence of the skid trails layout on the determination of mean extraction distance is given by ks, defined as the ratio between the real mean extraction distance and its orthogonal projection in the horizontal plane (Segebaden 1964; ks=1.25–1.55). Amzica (1971) recommended ks values of 1.30–1.75 for rough calculations depending on terrain topography.
The network correction factor (kn) increases with the unevenness of the distribution of the roads and in theoretical models varies strongly with the geometric design of the road network (Segebaden 1964): 1.00 for ideal case (parallel roads with no intersections); 1.33 for road networks layouts in the shape of regular polygons; and 2.0 for random layouts of road networks. Segebaden (1964) recommended kn values 1.60–1.70 for rough calculations, while Amzica (1971) reported values of kn between 1.05 and 1.65.
The total correction factor kt is given by the following formula (Lünzmann 1968):
According to FAO (1974a), this factor ranges between: 1.6 –2.0 in flat areas, 2.0–2.8 in hilly areas, 2.8–3.6 in mountainous areas and above 3.6 for very steep mountain areas. In addition, FAO (1974b) introduced the road efficiency factor as the relationship between road density index (RDI) and the real mean extraction distance:
where: a – road efficiency factor depending on terrain topography, with the following values: 4–5 for flat undulated terrain, 5–7 for hilly terrain, 7–9 for steep terrain and above 9 for very steep irregular terrain; SDe – real mean extraction distance, in km.
GIS based methods for computing the mean extraction distance – Metode izračuna srednje udaljenosti privlačenja utemeljene na GIS-u
For computing the real mean extraction distance (SDe) the raster method was defined. For determining the shortest mean extraction distance (SDs) the centres of gravity method, the grid point method and the buffer strips method were defined. These methods were automated using ESRI® ArcGIS Desktop 10 tools. Four traffic infrastructure scenarios were defined for the selected study area: scenario Zero, reflecting the current traffic infrastructure conditions; and scenarios