Forest road network planning, management and construction

Planning Forest Road Network in Natural Forest Areas: a Case Study in Northern Bosnia and Herzegovina

volume: 39, issue: 1

Natural forests are one of the three types of forest management in terms of origin. These forests
are of seed origin and they regenerate naturally. Therefore, natural forests are the most important
forest category from the point of view of timber production, as well as its quality and
biodiversity. The natural forests accessibility and overall forest accessibility are insufficient
for sustainable forest management. This is the reason for dealing with planning of forest roads,
actually planning of forest accessibility and designing of forest roads in this forest category.
This task requires quantity and quality analysis of the current forest road network, determination
of optimal density of forest roads, determination of suitability of forest area for the construction
of forest roads and designing of forest roads in the end. Planning of forest roads is
carried out at strategic level. Analytic Hierarchy Process (AHP) allows the selection and
evaluation of influential factors related to planning of forest roads. The tools of Geographic
Information System (GIS) allow a complete spatial and statistical analysis and management
of data collected from the forest management plans or data surveyed in the field and obtained
by means of »Digital Terrain Model« (DTM) and AHP method. Planning of forest roads will
be done in the Management Unit (MU) »Prosara«, located in the northern part of Bosnia and
Herzegovina (BIH). The current density of forest roads is 7.3 m/ha in natural forests of this
management unit. The optimal density of forest roads should be 17 m/ha. The length of new
forest roads designed in the MU »Prosara« is 21 km, and forest accessibility has increased to
13.5 m/ha.

Study of Forest Road Effect on Tree Community and Stand Structure in Three Italian and Iranian Temperate Forests

volume: 39, issue: 1

Roads are built in forests for two main reasons, but always in function of management of forest
ecosystems, and these reasons are to provide access to the forest area for transportation
mobility and wood extraction. This creates a relatively even network in the forest. This topic
has received much attention in recent years due to its function and effect on forested rural
landscapes and the related environment. Forest road network is important for various types
of functional use, such as the interface between forested lands and roads. The aim of this study
is to assess the effects of road existence and use on the occurrence of tree dieback and on the
composition of the tree community in three forest areas (two in Italy and one in Iran). The
effort to determine the dynamics of the effects caused by road use was done by examining the
changes in stand structure and abundance of species. As demonstrated by the results, the
edges (20 m) of the forest road network are a fine mosaic composed of different trees (qualitative
and quantitative), coupled with the moderate presence of dead trees. In the three areas, from
the road edges to the interior forest, a similar taxonomic composition of forest community was
found. The first main difference was related to the abundance of less shadow tolerant species
along the road. The second main difference was related to the tree biodiversity indices that are
higher along the road. The main similarities are in the structure of live and dead trees.

Pavement Deterioration Modeling for Forest Roads Based on Logistic Regression and Artificial Neural Networks

volume: 39, issue: 2

The accurate prediction of forest road pavement performance is important for efficient management
of surface transportation infrastructure and achieves significant savings through timely
intervention and accurate planning. The aim of this paper was to introduce a methodology
for developing accurate pavement deterioration models to be used primarily for the management
of the forest road infrastructure. For this purpose, 19 explanatory and three corresponding
response variables were measured in 185 segments of 50 km forest roads. Logistic regression
(LR) and artificial neural networks (ANNs) were used to predict forest road pavement
deterioration, Pothole, rutting and protrusion, as a function of pavement condition, environmental
factors, traffic and road qualify. The results showed ANNs and LR models could classify
from 82% to 89% of the current pavement condition correctly. According to the results,
LR model and ANNs predicted rutting, pothole and protrusion with 83.5%, 83.00% and
81.75%, 88.65% and 85.20%, 80.00% accuracy. Equivalent single axle load (ESAL), date of
repair, thickness of pavement and slope were identified as most significant explanatory variables.
Receiver Operating Characteristic Curve (ROC) showed that the results obtained by
ANNs and logistic regression are close to each other.


Web of Science Impact factor (2017): 1.714
Five-years impact factor: 1.775
Next issue: January 2019

Subject area

Agricultural and Biological Sciences