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.
volume: 41, issue:
Planning of forest harvesting operations is one of the key elements of successful forest management. The integration of modern tools and traditional forestry procedures is something that must be done in contemporary forestry. This research investigated the use of multicriteria decision support (AHP) and GIS in choosing the optimal harvesting system for predominantly selection cutting forest management on the example of two Forest Management Units (FMU). Results showed that AHP could be easily integrated into GIS using the extAHP tool and its results could be of help, along with other input data, in choosing the optimal harvesting system. Spatial analysis of raster data in GIS gives a comprehensive insight into the stand and terrain characteristics and shows the relative share of the area proposed for each system. In FMU »Kozara–Mlječanica«, the harvesting system chainsaw-skidder had the highest relative share with 44% of the area, meaning that it is almost the only harvesting system in current use, followed by chainsaw-forwarder (36%), chainsaw-cable yarder (19%), and chainsaw-adapted agriculture tractor (AAT) (1%). The system harvester-forwarder was not used at all, which is understandable considering that FMU »Kozara–Mlječanica« has a higher average slope and higher diameter of trees to be cut than FMU »Prosara«, where harvester-forwarder system accounts for a significant 36% of the area. The dominant system in FMU »Prosara« was chainsaw-forwarder (42%), followed by chainsaw-cable yarder (17%), chainsaw-skidder (4%) and chainsaw-AAT (1%). It should be noted that the presence of chainsaw-skidder system is insignificant. It is replaced by the system chainsaw-forwarder. Traditional harvesting system chainsaw-skidder, which prevails in Bosnia and Herzegovina, should be upgraded with the new technologies and methods. Using tools like multicriteria decision support and GIS could be of great help in that process.
volume: 45, issue:
The aim of the study was to provide a comprehensive overview of global long-distance road transportation of industrial roundwood. The study focused on the maximum gross vehicle weight (GVW) limits allowed with different timber truck configurations, typical payloads in timber trucking, the road transportation share of the total industrial roundwood long-distance transportation volume, and the average long-distance transportation distances and costs of industrial roundwood. The study was carried out as a questionnaire survey. The questionnaire was sent to timber transportation logistics experts and research scientists in the 30 countries with the largest industrial roundwood removals in Europe, as well as selected major forestry countries in the world (Argentina, Australia, Brazil, Canada, Chile, China, Japan, New Zealand, South Africa, Türkiye, the United States of America and Uruguay) in February 2022, and closed in May 2022. A total of 31 countries took part in the survey. The survey illustrated that timber trucking was the main long-distance transportation method of industrial roundwood in almost every country surveyed. Road transportation averaged 89% of the total industrial roundwood long-distance transportation volume. Timber truck configurations of 4 to 9 axles with GVW limits of around 30 tonnes to over 70 tonnes were most commonly used. The results indicated that higher GVW limits allowed significantly higher payloads in timber trucking, with the lowest payloads at less than 25 tonnes, and the highest payloads more than 45 tonnes. The average road transportation distance with industrial roundwood was 128 km, and the average long-distance transportation cost in timber trucking was €11.1 per tonne of timber transported. In the entire survey material, there was a direct relationship between transportation distance and transportation costs and an inverse relationship between maximum GVW limits and transportation costs. Consequently, in order to reduce transportation costs, it is essential to maximise payloads (within legal limits) and minimise haul distances. Several measures to increase cost- and energy-efficiency, and to reduce greenhouse gas emissions in road transportation logistics, are discussed in the paper. On the basis of the survey, it is recommended that up-to-date statistical data and novel research studies on the long-distance transportation of industrial roundwood be conducted in some countries in the future.