
Research Article


Effective Factors in Determination Optimal Density of Forest Road Network


Majid Lotfalian,
Yahya Kooch
and
Nosratollah Sarikhani


ABSTRACT

The aim of this research is to consider roads network quantity by reviewing the effective factors and finally determining the optimal road density. Sangdeh forests of Farim Wood Company were selected for this research that located at Savadkouh region of Mazandaran province (in Iran). In this research it is assumed that the effective factors in costs can be determined by using the mathematical model, as well as by the help of graphical model, less costs of skidding and road construction can be obtained; therefore, optimal road density can be evaluated. Harvesting methods, different types of roads, the ratio of each road to the whole network, stand per hectare, slope, geological conditions, presence of sand mine for constructing surface of roads, capital interest rate, wood exit costs, type of skidding or yarding machinery, slope and length correction coefficient, routes, type and number of load, allowable winching distance, brush and underbrush, condition of the roots, silvicultural methods (cutting form), regional soil, regional height, direction of the slope and morphology of the forest are factors which have been mentioned in this research as affecting determination of roads network density. For this, the model of evaluation and calculation of the time of skidder movement, which determines the skidding costs under the existing conditions in Sangdeh Forest, is as follows: Y = 25.05 + 1.20 X. For the forest region of Sangdeh with 353 cubic meters stand per hectare and skidding in contract method, the roads network density is 23 m in hectare and for skidding by the company, the roads network density is 19 meters in hectare; these numbers are the optimal ones. 




INTRODUCTION
Forestry plans are provided to assist the forest protection and
its life regeneration by forest management and essential marking of the
removable trees. In this direction, forest roads network as forest divisions
to the programming units (parcel) providing forestry plans, management,
logging and wood extraction, as well as forest protection play important
roles (Sarikhani and Majnounian, 1994; Mostafanejad, 1995, 2001; Sarikhani,
2001).
Quality and quantity of the forest roads network are important subjects
because if there is an error in this case, not only inflicts a lot of
losses to the production establishment but also causes some other damages
such as, soil erosion, ground sliding, unavailability to the forest and
etc. (Bazargan, 1998; Ejtehadi, 2000; Jourgholami, 2005). The goal of
this research is to consider roads network quantity by reviewing the effective
factors and finally determining the optimal road density for a sample
region. This subject is very important because of the todays need to the
forest management in country; more over since there no sufficient research
in this field, there is any identical operation (Lotfalian, 2000).
For this purpose, the research is assumed that the effective factors
in costs and can be determined by using the mathematical model, as well
as by the help of graphical model, less costs of skidding and road construction
can be obtained; therefore, optimal road density can be evaluated. In
Iran, there has been no related researches have been done; as follows:
Pilehvar (1994), Naghdi (1996), Ejtehadi (2000) and Lotfalian (2000) have
examined skidding time studies and evaluated related cost and mathematical
model.
Some studies have been done out of Iran. Some of them include: In Korea,
Kim (1996) have examined economic issues of the forest road according
to the forest growing and forest road density. In the research, the effects
of 54 forest roads network which were planned based on the forest stocking
conditions (such as the percent of planted forests, volume of removable
tree) skidding costs and road construction costs have been examined. Research
results show that, for 46, 60, 100, 150 and 200 m^{3} stands ha^{1},
7.7, 10, 16, 23 and 29 road densities ha^{1} are suitable, respectively.
Acar (1997) has done ground classification and planning the optimal forest
roads network and have discussed about production and costs in Kumbet
in Turkey. Also, network design models are well studied and results for
models have been reported by Arvidsson et al. (2002), Karlsson
et al. (2002), Karlsson (2002), Olsson and Lohmander (2005) and
Olsson (2005).
MATERIALS AND METHODS
Study Area
In 1968, development plan of the Caspian Sea forests at 27 km of East
Polsefid (Mazandaran province) in Sangdeh was provided by the cooperation
of FAO experts in five forest districts with 27000 hectare in area. The
region is located on north direction (side) of Alborz mountain chain (North
Iran) in 36° North latitude and 52° East longitudes. The maximum
and minimum height of this forest is 3100 and 750 m, respectively. Sangdeh
forestry plan is the second of these five forest district that has a humid
climate and cold winters. The annual average rainfall is 1200 mm, average
forest standing is 353 m^{3} ha^{1} and yearly growing
of this region is 6 m^{3} ha^{1}. Regional soil is podzolic
soil. This research was performed in the summer of 2005.
Data Collection
Pay attention to, the best rate of roads network density for each forest
is a condition which includes the least total costs of road construction
and skidding also other factors are constant in this region, for this
purpose, model to minimize total costs of the road construction and skidding
(Fig. 1) was used in this study.

Fig. 1: 
The minimize total costs model 
Total curve minimum shows a limitation of the roads network density which
has the least total costs of road construction and skidding as well as
shows the optimal road density (Fig. 1). Since winching
and unloading time are variables which are independent of roads network
density and their changes reduce the correlation between skidding route
length and skidding time, while calculating the skidding costs, these
variables to 151 samples are averaged and it is assumed that in each point
of the skidding route, this time will be averagely spent on winching and
unloading. In order to calculate the skidding costs, two methods, contract
and accounting, are used. In contract method, the costs inquiry as commission
and in accounting method, the time study of the connected times and calculating
of the machinery costs with the method offered by FAO have been used.
To obtain road construction costs, by referring to the company previous
years costs the region and adjusting them in order to be fitted to the
roads with standards included in 131 publication guide line of plan and
budget organization and updating them to the current year, some measurements
have been done.
RESULTS
Mathematical Model of Predicting the Time of Skidder Movement
After evaluating the number of the needed samples (51 samples were needed
in surface 5% and considering the selection of at least 3 samples, 54
samples were needed to obtain credit, by doing time studies, for 67 samples
and 151 samples were measured for winching and unloading) evaluating coefficients
in math. Model of predicting time of skidder movement, Minitab statistical
software was used, for this purpose with using the multiple regressions,
the best model for predicting the time of skidder movement was distinguished
as follows, in addition to the effective factors in skidding time which
included, distance, volume and etc. (Pilehvar, 1994), interactions of
these factors were also examined. For this, the product of both factors
as a new specification in regression equation had been reviewed and related
model, variance analysis results and its table were also determined as
follows:
Y = 121 + 1.19x_{1}  1.06x_{2}
+ 15.0x_{3} + 25.7x_{4} + 0.38x_{5}  9.08x_{6}
 1.15x_{7} 
(1) 
Where:
Y 
= 
Time of skidder movement per case (sec) 
X_{1} 
= 
Skidding distance (m) 
X_{2} 
= 
Slope of skidding route (%) 
X_{3} 
= 
No. of logs per case 
X_{4} 
= 
Volume of logs per case (m^{3}) 
X_{5} 
= 
Slope and volume interaction 
X_{6} 
= 
Volume and number of logs interaction 
X_{7} 
= 
No. of logs and slope of skidding route interaction 
In Table 1, considering pvalue, only the distance variable
is in the significant level. Table 2 shows the model
variance analysis, also.
Table 1: 
pvalue for model variables 

Table 2: 
Model analysis variance 

S = 100.4, R^{2} = 96.1%, R^{2} (adj.)
= 96.1% 
Calculated F shows that it is significance in the level a = 1%. It also
shows the significance of the selected regression and significant difference
of the regression variable coefficient from zero, as well as represents
the regression to 96.1% changes. Now, for determining the best model with
the Back Ward Stepwise Method, effective specifications have been determined
in the model. Here, it is distinguished that pvalue is significant just
for distance variable in 5% level, that is, time of skidder movement in
each case is only depended on distance. And form there, below model is
provided:
Where:
Y 
= 
Time of skidder movement in each case (sec) 
X 
= 
Skidding route length (m) 
To evaluate model credit, prediction of the time of skidder movement
calculated by recognized model was compared to the three samples of the
real time of skidder movement obtained from ground measurement (selected
randomly) and it was recognized that this model enjoys statistical credit
with the probability of 5%.
Final Calculation and Determination of the Optimal Road Network Density
To draw the diagram of the road construction cost of any cubic meter of
wood under operation, at first, roads construction and preservation in
each kilometer had been calculated, then, road construction cost in any
hectare for different roads network densities had been obtained. Considering
growing of 6 m^{3} in a hectare, it is assumed that averagely,
the same rate of the wood in surface unit can be remove in a year and
by dividing it to the road construction cost in any hectare, the related
diagram can be drawn.
To consider that different roads network densities are followed by various
lengths of the skidding routes, by doing the time study, regression between
different skidding routes lengths and time of skidding movement was obtained.
From there, the relation between network different densities and time
of skidder movement was obtained. Having the spent average time for winching
and unloading, as well as calculating of the skidding time cost, the relation
between network various densities and skidding time cost had been recognized.
Obtaining production rate in skidding hour in the time study, the relation
of the network different densities and skidding cost of any cubic meter
of wood had been gained, then skidding cost diagram had been drawn. Moreover,
skidding costs had been evaluated by two different methods, contract and
accounting and by calculating the total costs curve Fig.
2 was obtained.
Here, it would be seen that for different managements and selection of
the skidding kind, densities of 19.5 and 23 m ha^{1} have been
determined that total of these numbers shows a suitable and logic limitation
of the forest roads network density which guides the researcher to gain
the least cost for this study.

Fig. 2: 
The model to minimize total costs 
DISCUSSION
Among the effective factors in skidding, just distance factor, is
important in time of skidder movement factors such as load volume, number
of log, route slope and their interactions are not important in time of
skidder movement (with or without load). Pilehvar (1994), in his study
about the function of the timber jack skidder 450 c, found that the skidding
time was depend on variables such as, skidding distance, log volume in
each skidding and skidding rout slope. Naghdi (1996), during his study
about the timber jack skidder 450 c in downward slopes, concluded that
the skidding time was depended on variables such as skidding distance,
log volume in each time of skidding, skidding rout slope and the number
of logs per case. As seen, in mentioned studies, more variables had been
effective in the skidding time, while in the present research; only the
distance factor has taken into account.
Firstly, it must be mentioned that in above studies, the whole of the
skidding time have been examined; however, in the present research just
the time of skidder movement is considered. Therefore, we can conclude
that the elimination of winching and unloading stages can lead to the
elimination of some variables and this shows the accurate selection of
the research in elimination of these stages, because the purpose of this
research is the examination of the effective factors in determination
of the roads network density, while it was previously pointed out that
the spent time in winching and unloading stages was not depended on the
roads network density. As had been predicted in the hypothesis, the effective
factors in costs and their relation with costs can be determined by the
mathematical model. For this, the model of evaluation and calculation
of the time of skidder movement, which determines the skidding costs under
the existing conditions in Sangdeh Forest, is as follows:
Where:
Y 
= 
Time of skidder movement (sec) 
X 
= 
Skidding route length (m) 
Mostafanejad (1995, 2001) has stated that in Neka forest region, the
best distance of skidding route is 250 m and forest roads density (main
and secondary) is 25 m ha^{1} Ejtehadi (2000) has declared that,
in Vaz forest region (in North of Iran) the best length density of the
roads network is about 19.0 m ha^{1}. Kim (1996) in Korea shows
that for stands of 46, 60, 100, 150 and 200 m^{3} in hectare,
roads densities of 7.7, 10, 16, 23 and 29 m in hectare are suitable, respectively.
It is evident that, considering various and regional affects of the pointed
factors in this research, different results had been gained so it is suitable
for the same region. Therefore, the results of the present research like
predicted hypothesis can be evaluated by the graphical model (Fig.
2). For the forest region of Sangdeh with 353 m^{3} stand
per hectare and skidding in contract method, the roads network density
is 23 m ha^{1} and for skidding by the company, the roads network
density is 19 m ha^{1}; these numbers are the optimal ones.

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