hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.31298/sl.141.3-4.6

Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit

Erhan Çalişkan
Uzay Karahalil

Puni tekst: engleski, pdf (2 MB) str. 163-171 preuzimanja: 289* citiraj
APA 6th Edition
Çalişkan, E. i Karahalil, U. (2017). Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit. Šumarski list, 141 (3-4), 163-171. https://doi.org/10.31298/sl.141.3-4.6
MLA 8th Edition
Çalişkan, Erhan i Uzay Karahalil. "Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit." Šumarski list, vol. 141, br. 3-4, 2017, str. 163-171. https://doi.org/10.31298/sl.141.3-4.6. Citirano 18.07.2019.
Chicago 17th Edition
Çalişkan, Erhan i Uzay Karahalil. "Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit." Šumarski list 141, br. 3-4 (2017): 163-171. https://doi.org/10.31298/sl.141.3-4.6
Harvard
Çalişkan, E., i Karahalil, U. (2017). 'Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit', Šumarski list, 141(3-4), str. 163-171. doi: https://doi.org/10.31298/sl.141.3-4.6
Vancouver
Çalişkan E, Karahalil U. Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit. Šumarski list [Internet]. 2017 [pristupljeno 18.07.2019.];141(3-4):163-171. doi: https://doi.org/10.31298/sl.141.3-4.6
IEEE
E. Çalişkan i U. Karahalil, "Evaluation of forest road network and determining timber extraction system using GIS: a case study in Anbardağ planning unit", Šumarski list, vol.141, br. 3-4, str. 163-171, 2017. [Online]. doi: https://doi.org/10.31298/sl.141.3-4.6

Rad u XML formatu

Sažetak
Secondary forest road network planning and primary timber extraction systems play very important roles in sustainable forest management. The progression of forest areas in Turkey and the world towards mountains as well as the increase in working obligations have made timber extraction systems gain more importance. The forest areas found in mountainous lands with harsh slopes in Turkey makes timber extraction systems more problematic and more complex. The objective of this study is to develop a model for timber extraction systems using Geographic Information Systems (GIS) analysis considering terrain morphology and secondary forest road network. Additionally the forest road network in Anbardağ forest planning unit of Giresun province in Turkey was investigated considering forest road density and forest road spacing. According to obtained results, the forest road length was 226.34 km, forest road density was 11.74 m/ha, forest road spacing was 851.7 m and road coverage was 51% of the study area. Chainsaw–small size cable crane (36.76%) and chainsaw–medium size cable crane (27.94%) were selected as the most suitable timber extraction systems for the steep terrain study area according to our model. They were followed by chainsaw–forest tractor (23.52%), chainsaw–agriculture tractor (10.29%) and chainsaw–sledge yarder (1.49%). The results of this study showed that GIS saved a considerable amount of labor force, time and cost for the evaluation of forest road network as well as the development model for timber extraction system.

Ključne riječi
Secondary forest road network; timber extraction system; GIS; Turkey

Hrčak ID: 181413

URI
https://hrcak.srce.hr/181413

▼ Article Information



INTRODUCTION

UVOD

Turkey has 22.7 million ha of close to nature forest area covering nearly 27% of its total land. Approximately 46% of the total area is on steep terrain with ground slopes greater than 40%. Hence, harvesting in mountainous regions has always played a significant role. (GDF, 2013). Forestry operations in Turkey are carried out at different parts of the country under different conditions. Only the best forest road networks can provide conditions for working in wide, scattered and difficult mountainous areas. Approximately 18 million m³ logs are transported via forest roads in Turkey, each year (GDF, 2013). For­est road networks were developed via manual methods in previous studies, while computer software and hardware have been used extensively and effectively for solving com­plex problems in forest areas, especially in developed countries (Akay 2003; Rogers 2005; Demir 2007) in recent years. Nowadays, concepts such as digital map, GIS and land informa­tion systems have gained importance in the design of road networks (Akay, 2003; Aruga, 2005; Gümüş, 2008; Çalışkan, 2013).

Timber harvesting, as a succession of interrelated and interdependent operations in timber production, includes tree conversion (felling and processing) and timber transport. Timber transport consists of two mutually dependent sub-phases: off-road (timber extraction or primary transsport) and on-road (further transport or secondary forest road network) (Bayoğlu, 1962; Seçkin, 1978;Conway, 1982; FAO, 1982; Erdaş, 1986; Haarlaa and Jurvelius, 1987; Acar, 1994;Berg and Schiess, 1996; Dykstra and Heinrich, 1996; Heinimann, 1999; Karaman, 2001; Rummer, 2002; Heinimann and Stampfer, 2003; Pentek et al., 2008). In recent studies, Abbas et al., (2014) analyzed the different operational matters, conditions, equipment and transportation use reported by logging firms. The study provided technical forest product operations, information and methods for assessing the capacity of logging firms and markets looking to expand their businesses. Visser and Stampfer (2015) reviewed developments, the main engineering considerations of cable-assist workings, as well as the advances in integrating equipment into harvesting systems. They also analyzed the operating guidelines that are either in use or being developed to help implement the timber extraction systems. Duka et al., (2016) concluded that extending the operating range of skidder on steeper slopes with heavier loads has the potential to decrease harvesting costs and increase productivity.

There are four principal means of off-road transportation: ground vehicles on natural terrain, ground vehicles on skid roads, carriages on cable structures and airships in the air (Heinimann, 1999). The necessity of the timber raw material in Turkey has been increasing (GDF, 2013). Transportation stage involves a rather difficult, expensive and time consuming activity in timber production activities. In this process, transport of forest yield from forest to the landing has been practiced in various forms. In particular, transporting forest yield with minimum loss in quality and quantity and with minimum damage to the environment seems to be an important problem to be solved.

Timber transportation on ground surfaces in forest lands causes erosion on soil, damage on saplings and leads to loss of quality and quantity on stand trees (Lubello, 2008). This is especially a problem that we are faced with when losses of forest value, particularly in mountainous regions are taken into consideration. GIS for assessing soil trafficability was initially deployed for military off-road planning after which these applications were introduced to forest and agricultural applications (Lubello, 2008). In some cases, terrain evaluation has been carried out based on economic considerations in order to optimize road models regarding financial values. Lubello (2008) suggested a rule-based spatial decision support system for planning of forest operations using GIS techniques.

Suvinen (2006) used a GIS-based simulation model to evaluate the interaction of terrain trafficability, vehicle mobility and terrain tractability that takes place through the machine wheel’s surface. Mohtashami (2011) conducted a case study in Sweden putting forward that the use of digital planning of the improvement of strip roads in order to avoid vulnerable terrains made forwarding of timber more profitable.

Forest harvesting operations are usually pursued either by the General Directorate of Forestry or the private sector. However, there is no standard for specific terrain or forest road network conditions; therefore the selection of a specific harvesting operation has been limited to the availability of machiner­ies and worker force.

Thus, the first objective of this study was to investigate the secondary forest road network with regard to forest road density, forest road spacing and to implement developed planning approach using Geographic Information Systems (GIS) in Anbardağ planning unit of Giresun Forest Enterprise, Turkey. Another important objective was to develop a model for timber extraction systems via GIS analysis taking into consideration the terrain morphology and secondary forest road network.

MATERIAL AND METHODS

MATERIJAL I METODE

Study area- Promatrano područje

This study was carried out in the Anbardağ forest planning unit covering an area of approximately 5975.0 ha in the Giresun province in the northeastern Black Sea region of Turkey. The area was located between 400 42' 47" - 400 30' 13" North, and 380 01' 49" - 380 13' 16" East. The relief has a very irregular topography, and the elevation ranges from 700 to 3100 m. The mean annual precipitation is 1297 mm, with the lowest values being recorded in July and August. Dominant tree species used for production purposes are natural oriental spruce (Picea orientalis Link.) and oriental beech (Fagus orientalis Lipsky). Traditionally, cut-to-length harvesting method has been used in Turkish forestry. While skidding depends on the steep slope and presence of adequate road infrastructures, felling and delimbing operations were used to be carried out via chainsaws, . Debarking with axe and/or log wizard is mostly operated in stands and rarely on roadside (Eker and Acar, 2006). Agricultural and forest tractors are mostly represented as off-road machines and have been widely used. Aerial yarding is carried out by means of cable cranes based on sledge winch yarder and mobile tower yarder. Loading operations at the roadside or landing is carried out manually with grapple loaders or hydraulic cranes. Hauling through forest roads and main roads is executed by truck and tractor trailer from roadside to the main storage site.

Methods-Metode

Geographic data used in this study were acquired from on-screen digitized paper maps in an ArcGISenvironment. These maps consist of topographical maps containing elevation data (10 m contour interval), forest management plan information, forest road network, administrative boundaries, hydrology network and technical limitations for timber extraction systems. Topographic vector maps of 1:25000 scale were used in this study. These maps were produced by the General Command of Mapping of Turkey using Universal Transvers Mercator (UTM) projection and ED-50 datum. Therefore, the original projected coordinate system, UTM, European Datum 1950, Zone 37N, was selected for all maps.

An inventory of forest roads not existing in the digitized maps was conducted using GPS (Global Positioning System). Road routes were also collected with track mode of GPS. GPS data were converted into a GIS format using Pathfinder Office software. Field descriptions of continuous segments and discrete features were added to GPS location information to create a series of GIS coverages. A separate data layer (coverage) was made of each road feature mapped. The created layer was then used to calculate forest road density, road spacing and road coverage. Road density was obtained using the formula (1), road spacing was determined theoretically using the formula (2) and road coverage was calculated according to formula (3) as follows Backmund (1968):

RD=road length (m)/district area (ha) (1)

RS=10000/RD (2)

in which RD was Road Density and RS was Road Spacing.

Road coverage: (Accessible areas for logging)/ total areas*100 (3)

Timber extraction systems were determined on the basis of the following: ground slope, extraction direction, extraction distance, forest road network, elevation and boundaries. The Digital Elevation Model (DEM) of the study area was created with ArcGIS 10.0 software. Ground slope, aspect, and elevation maps were derived from the DEM.

Ground slope is one of the most important parameters determining the choice of an extraction system. Ground slope was calculated using the slope tool of the Spatial Analyst toolbox. Five main slope classes (in percentage) were defined according to Samset (1979) (Table 1).

Table 1. Ground slope classes and designation Tablica 1. Klase nagiba zemljišta i oznaka

Slope Class

Klasanagiba

Slope (%)

Nagib (%)

Designation

Oznaka

1 0-10

Level Terrain

Ravan teren

2 11-20

Gentle Terrain

Blagi teren

3 21-33

Moderate Terrain

Umjeren teren

4 34-50

Steep Terrain

Strm teren

5 >50

Very Steep Terrain

Jako strm teren

Aspect associated parameters such as exposure to sunlight; drying winds and rainfall are important factors in forest roads. Slope direction map of the study area was divided into 9 directions including flat, north, northeast, east, south, southeast, southwest, west and northwest.

The mean extraction distance (off-road transportation defined as the average distance between stem-site and the next forest road or storage place for further transportation, was grouped into five classes as follows: Class 1, <100 m; Class 2, 100–250 m; Class 3, 250–500 m; Class 4, 500–1000 m; Class 5, >1000 m. The extraction distance was generated via “Euclidean Distance Tool” using the roads shapefile (Tucek and Pacola 1999; Lubello, 2008). Although the maximum distance may be changed according to user, it was set up to 1000 m. as default.

Five main harvesting systems were selected for harvesting operations in the researched area considering timber extraction systems and felling method (Figure 1). Some factors such as working direction, ground slope limits, operation distance were found to be different according to the selected system. Therefore, to determine the timber extraction systems, studies previously conducted were used (Aykut et al. 1997; Acar 1997; Acar 1998; Çağlar 2002; Öztürk and Şentürk 2006; Şentürk et al. 2007) (Table 2).

Figure 1. Felling and timber extraction with selected harvesting operations Slika l. Sječa i privlačenje drva odabranim načinima pridobivanja drva
sumlist-141-163-g1.png

Table 2. Timber extraction systems and their technical limits Tablica 2. Sustavi privlačenja drva i tehnička ograničenja

Timber Extraction Systems

Sustavi privlačenja drva

Slope Downhill (%)

Nagibnizbrdice (%)

Slope Uphill (%)

Nagibuzbrdice(%)

Max.Distance(m)

Mak. udaljenost(m)

Agricultural Tractor

Poljoprivredni traktor

0-30 0-20 350

Forest Tractor

Šumski traktor

34-50 0-20 500

Small size mobile cable-crane

Mala pokretna lančana dizalica

>50 >50 300

Medium size mobile cable-crane

Srednja pokretna lančana dizalica

>50 >50 800

Sledge yarder

Žičara

>50 >50 >800

The “Euclidean Distance” and “Path Distance” commands were used in order to calculate the extraction distances and the relative limit of the terrain condition. The Path Distance tool is one of the available tools in ArcGIS 10.0, as part of Spatial Analyst, performing cost distance analysis, accounted for both horizontal and vertical cost factors as well as true surface distance. Vertical factors determine the difficulty of moving from one cell to another, while accounting for the vertical elements that may affect the movement (Pellegrini, 2012; ESRI, 2013). The vertical factor parameters in the model were set as values of terrain slope according to the relative limits to determine the timber extraction system. The Path distance analysis was performed for each extraction system. Each output map was then reclassified according to the feasibility of each system. The five output maps were then unified to create the final map representing the extraction system. The graphical representation of workflow was given in Figure 2 to show our methods for combining all the information.

Figure 2. Graphical representation of the workflow Slika 2. Grafički prikaz tijeka rada
sumlist-141-163-g2.png

RESULT AND DISCUSSION

REZULTATI I RASPRAVA

As mentioned above, topographic factors are very important for secondary forest roads. The research area generally has a steep topography. In figure 3 the Digital Terrain Model (DTM) of the study area is represented.

Given the mainly steep terrain slope classes 3, 4 and 5 (74.44%) predominated with the total area of 19269.74 ha, while the slope class 1 had the lowest cover according to the slope map of the study area (Table 3, Figure 4). When the roads are constructed in mountainous terrain, the excavated materials from the hillside are widely scattered downward the slope (Kim et al. 2004; Hosseini et al., 2012). Properly locating a road depends on the type of road, geology, land use, hydrological network and the side slope of the ground. Evaluating the needs of forest roads of an area is fundamental to evaluate together with the accessibility of the forest and also the possibility to perform the silvicultural operations (Pellegrini, 2012). The clearing limit of roads and skid trails will vary, depending on ground slope and the amount of cut and fill required (Kramer, 2001). Ground slope is the most significant parameter influencing the off-road transportation (timber extraction) and consequently the choice of the extraction system. Therefore, we considered technical limits as per table 2, to select the appropriate extraction systems generally limited by distance from the road.

Figure 3. Digital terrain model of research area Slika 3.Digitalni model terena istraživanoga područja
sumlist-141-163-g3.png

Table 3. Slope distribution for each class in the study area Tablica 3. Raspodjela nagiba za svaku klasu u promatranom području
Layer Name

Naziv sloja

Slope Class

Klasanagiba

Slope Value (%)

Vrijednost nagiba (%)

Area (ha)

Područje (ha)

Proportion (%)

Omjer (%)

Slope

Nagib

1 0-10 1644.01 8.53
2 11-20 3281.18 17.03
3 21-33 5180.00 26.88
4 34-50 4845.67 25.15
5 …> 50 4318.88 22.41
Total

Ukupno

19269.74 100.00

Figure 4. The slope map of the study area Slika 4.Karta nagiba promatranog područja
sumlist-141-163-g4.png

Aspect associated parameters such as exposure to sunlight; drying winds and rainfall are important factors in forest road and timber extraction systems. A road along the slope which gets the most sun will dry out faster after rainfall. Consequently, it will be subject to less damage from traffic thereby resulting in lower maintenance cost (Sessions 2007; Hosseini et al., 2012). Therefore, we prepared an aspect map and displayed that all aspects were presented in the study area (Figure 5). The largest areas of aspect are northwest, west and southwest directions, while the smallest areas are flat (Table 4).

Figure 5. Aspect map of the study area Slika 5.Karta orijentacije nagiba u promatranome području
sumlist-141-163-g5.png

Table 4. Aspect distribution for each class Tablica 4. Raspodjela orijentacije za svaku klasu nagiba

Layer Name

Naziv sloja

Aspect Class

Klasa orijentacije

Aspect Code

Kod orijentacije

Area (ha)

Područje (ha)

Proportion (%)

Omjer (%)

Aspect

Orijentacija

Flat

Ravno

0 315.99 1.64

North

Sjever

1 902.96 4.68

North East

Sjeveroistok

2 963.17 5.00

East

Istok

3 1099.44 5.71

South East

Jugoistok

4 2174.75 11.28

South

Jug

5 2809.19 14.58

South West

Jugozapad

6 3481.58 18.07

West

Zapad

7 3526.14 18.30

North West

Sjeverozapad

8 3996.51 20.74

Total

Ukupno

19269.74 100.00

Existing forest roads were digitized and a database was built using GIS as shown in Figure 6. One major challenge in secondary road network planning is to determine timber extraction systems under different terrain conditions. Ground slope and topography which affect the forest road network were considered as correction factors according to Segebaden (1964) and Lotfalian (2011). Heinimann (1998) reported that road spacing on slopes depends on the underlying off-road transportation technology. Considering the mentioned literature, road length, density, spacing and coverage were calculated as 226.34 km, 11,74 m/ha, 851,7 m, and 51% respectively for the entire study area. 184 km of the existing roads have a longitudinal slope greater than 10% and 42 km have a long slope greater than 12%. (Figure 7).

Figure 6. Map and attribute data base of the forest road network Slika 6.Karta i baza atributnih podataka o mreži šumskih cesta
sumlist-141-163-g6.png

Figure 7. Existing forest road network in Anbardağ Planning Unit Slika 7.Postojeća mreža šumskih cesta u Planskoj jedinici Anbardağ
sumlist-141-163-g7.png

Timber extraction systems were determined on the basis of ground slope, extraction direction, extraction distance, forest road network, elevation and boundaries. Spatial location of five selected systems as; chainsaw-agriculture tractor, chainsaw-forest tractor, chainsaw-small size cable crane, chainsaw-medium size cable crane and chainsaw- sledge yarder are shown in figure 8 according to our model considering above mentioned parameters and influencing factors such as technical limits of felling and timber extraction.

Figure 8. Spatial location of timber extraction systems in forest of the study area Slika 8.Prostorni smještaj sustava privlačenja drva u šumi promatranog područja
sumlist-141-163-g8.png

Outputs of the developed model displayed that, chainsaw–small size cable crane (36.76%) and chainsaw–medium size cable crane (27.94%) systems covered the largest forest area followed by chainsaw–forest tractor (23.52%), chainsaw–agriculture tractor (10.29%) and chainsaw–sledge yarder (1.49%). The model presented in the paper was developed as a tool for planning forest operations.

There is no recorded study in the literature about determining timber extraction system considering five different systems. There are some studies exist, however they generally focus on one system and basically analyses the cost or efficiency of the selected method or the system. Therefore, the outputs of the conducted study couldn’t compare with similar studies. On the other hand, a few studies conducted for the allocation of timber extraction systems but under different conditions. For instance, Pentek et al., (2008) developed a model for selecting a harvesting system for commercial forests of Northern Velebitis based on three influencing factors: terrain slope, extraction distance and breast height diameter of trees. Based on the model, a harvesting system is determined for each forest sub compartment. The results show that breast height tree diameter restricts mechanized felling and processing. They found that considering the fully mechanized nine harvesting systems, only over 7.27% of the researched area could be used.

CONCLUSIONS

ZAKLJUČCI

The results of this study put forth that GIS is one of the most valuable tools in locating and analyzing mountainous areas for forest road network planning and model for timber extraction system.

The maps of elevation, slope, aspect, forest road network and timber extraction were prepared and classified. In this study the total length of existing forest road network was 226,34 km, road density was 11,74 m/ha, road spacing was 851,7 m and road coverage was 51% . The GIS based timber extraction model, presented in this paper, has been developed for planning in harvesting operations. The timber extraction systems were determined on the basis of factors, such as slope, extraction direction extraction distance, existing forest road network, elevation and boundaries. While the forest road network allows access to the forest area, the system of timber extraction can be considered as the technical limit which defines the part of forest that can be managed with the present roads. The model selected timber extraction systems as; steep terrain chainsaw–small size cable crane (36.76%) and chainsaw–medium size cable crane (27.94%) for the study area.

In conclusion, options for more economically and environmentally friendly timber raw material production planning became more evident for the planners. The results showed that wecould provide an integrated harvesting operation solutions for a characteristic mountainous area in Turkey based on GIS techniques.

The methodology developed for this study can also easily be applied to the other planning units as long as the requirements are met such as digitized contours, existing roads and boundaries.

References

1 

Abbas D.; Handler R.; Hartsough B.; Dykstra D.; Lautala P.; Hembroff L. (2014). A Survey Analysis of Forest Harvesting and Transportation Operations in Michigan, Croatian Journal of Forest Engineering, 35(2), 179-192.

2 

Acar H. H. (1994). Developing Forest Transportation Plans in Mountainous Terrain, KTÜ Fen Bilimleri Enstitüsü, PhD Thesis, 150 p., Trabzon (In Turkish)

3 

Acar H. H. 1997). An investigation on the extraction from compartment by tractors at the mountainous region. Turkish Journal of Agriculture and Forestry, 21, 299-306.

4 

Acar H. H. (1998). An investigation on the logging machines from the economical and the technical point of view at Giresun forest district. Turkish Journal of Agriculture and Forestry, 22, 143-149.

5 

Akay A. E. (2003). Minimizing total cost of construction, maintenance, and transporta¬tion costs with computer-aided forest road design. PhD Thesis. 150 p., Oregon State University, Corvallis, Oregon . 229 p.

6 

Aruga K. (2005). Tabu search optimization of horizontal and vertical alignments of forest roads, Journal of Forest Research, 10: 275-284.

7 

Aykut T.; Acar H. H.; Şentürk N. (1997). An investigation on comparing of Koller K 300, Urus M III and Gantner forest skylines used timber extraction on Artvin region. Journal of İstanbul University Faculty of Forestry, Serial A, 47(2), 30-54.

8 

Bayoğlu S. (1962). Çangal Bölgesinde Orman Nakliyatı ve Yol Sistemi Üzerine Araştırmalar, Orman Genel Müdürlüğü Yayınları Sıra No: 334, Seri No: 19, Yenilik Basımevi, İstanbul , 142 s.

9 

Bayoğlu D. R.; Schiess P. (1996). Stand Level Setting Design – Biological Legacies in Clayoquot Sound, Clayoquot Sound Symposium, march 6-8 1996, Ahuosat, Flores Island, British Columbia, 74 p.

10 

Backmund F. (1968): Indices for the degree of accessibility of forest districts via roads . Zeitschr.F.Forstw, 119. 445-452.

11 

Conway S. (1982). Logging Practice, Oregon.

12 

Çağlar S. (2002). An investigation of the transport from compartment with cable cranes aspect of working productivity in Artvin region, Master Thesis, Kafkas University Artvin, Turkey.

13 

Çalışkan E. (2013). Planning of Forest Road Network and Analysis in Mountainous Area, Life Science Journal, 10(2), 2456-2465.

14 

Demir M. (2007). Impacts, management and functional planning criterion of forest road network system in Turkey. Transportation Research Part A, 41(1): 56-68.

15 

Gumus S.; Acar H.H.; Toksoy D. (2008). Functional forest road network planning by consideration of environmental im¬pact assessment for wood harvesting. Environmental Monitoring and Assessment, vol. 142 (1-3): 109-116.

16 

Dykstra D.P.; ve Heinrich R. (1996). FAO Model Code of Forest Harvesting Practice, FAO Publications, Rome, 85 s.

17 

Eker S.; Acar H.H. (2006). Operational Planning Method in Wood Harvesting (Odun Hammaddesi Üretiminde Operasyonel Planlama Yöntemi). Süleyman Demirel University Faculty of Forestry Journal, A(2): 128-140. (Abstract in English)

18 

Erdaş O. (1986). "Odun hammaddesi Üretimi, Bölmeden Çıkarma ve Taşıma Safhalarında Sistem Seçimi", Karadeniz Üniversitesi Orman Fakültesi Dergisi, Cilt 9, Sayı 1-2, s. 91-113, Trabzon.

19 

ESRI (2013). What is GIS, online, available at: [http://www.gis.com/content/what-gis], viewed 4 December 2013 ESRI Info, ESRI History online, available at: [www.esri.com/about-esri/about/history.html],viewed 5 December 2011.

20 

FAO (1982). Basic Technology in Forest Operations , FAO Forestry Paper No: 31, Rome

21 

GDF (2013). Activities of 2013 Year Report (2013 Yılı Faaliyet Raporu), General Directorate of Forestry, 100 p., Ankara

22 

Haarlaa R.; Jurvelius M. (1987). Choice of Appropriate Tools and Equipment For Mountain Forestry in Developing Countries, IUFRO Symposium on the Role of Forest Research in Solving Socio,economic Problems in the Himalayan Region 17-27.10.1987, Peshawar, Pakistan.

23 

Heinimann HR. (1998). A computer model to differentiate skidder and cable-yarder based road network concepts on steep slopes. Journal of Forest Research, 3: 1-9.

24 

Heinimann H. R. (1999). Ground-Based Harvesting Systems for Step Slopes, In Proceedings International Mountain Logging and 10th Pacific Northwets Skyline Symposium, Ed. by J. Sesssions and W. Chung Corvellis OR, March 28 – April 1, 1999. p. 1- 19. Oregon State University

25 

Heinimann H. R.; Stampfer K. (2003). Harvest Layout Plannıng for Hıgh-Altıtude Protectıon Forests, Austro2003: High Tech Forest Operations for Mountainous Terrain, October 5-9, Schlaegl – Austria

26 

Hosseini S.A.; Mazrae M.R.; Majid Lotfalian M.; Parsakhoo A. (2012). Designing an Optimal Forest Road Network by Consideration of Environmental Impacts in Gis. Journal of Environmental Engineering and Landscape Management, 20(1): 58-66.

27 

Karaman A. (2001). Wood raw material felling and transportation, Published Lecture, Publish No: 4 (p. 263). Artvin, Turkey: Kafkas University, Artvin Forest of Faculty

28 

Kim K.; Park H.; Lee S.; Woo I. (2004). Geographic Information System (GIS) based stability analysis of rock cut slopes. Geosciences Journal, 8(4): 391-400.

29 

Kramer B. W. (2001). Forest Road Contracting. Construction and Maintenance for Small Forest Woodland Owners , 35: 52-79. Oregon State University, College of Forestry.

30 

Lotfalian M.; Poorkia A.; Kooch Y.; Rafatnia N. (2011). Determination of Correction Coefficient of Skidding Distance According to Existing Road Network in Lalis Forest of Iran. Internatıonal Journal of Natural and Engineering Sciences, 5(3): 9-11.

31 

Lubello D. (2008). A rule-based SDSS for integrated forest harvesting planning. PhD Thesis. Padova: Universita Degli Studi di Padova.

32 

Mohtashami s. (2011). Planning forest routes for silvicultural activities using GIS based techniques: A case study of Selesjö in Östergötland, Sweden, Degree Project.

33 

Pentek T.; Porinsky T.; Sunjar M.; Stanki İ.; Nevecerel H.; Sporcic M. (2008). Environmentally Sound Harvesting Technologies in Commercial Forests in the Area of Northern Velebit Functional Terrain Classification. Periodicum Biologorum, 110, No 2: 127-135, 2008

34 

Pellegrini M. (2012). Support tools for planning and management of a forest road network, PhD Thesis. Padova: Universita Degli Studi di Padova.

35 

Rummer B. (2002). "TIMBR-3: Forest Operations Technology", USDA Southern Forest Resource Assessment Draft Report.

36 

Rogers L. W. (2005). Automating Contour- Based Route Projection for Preliminary Forest Road Designs using GIS, Ms.C. thesis.University of Washington. 87 p.

37 

Öztürk T.; Şentürk N. (2006). Extraction of spruce timber by Gantner cable crane from selective forests of Artvin region. Croatian Journal of Forest Engineering, 27(1): 59-66.

38 

Samset I. (1979). The Accessibility of Forest Resources, Proceedings of Symposium on Mountain Logging”, Ed. by W. Carson, J. Jorgensen, H. Lysons, IUFRO. 10-14 September, University of Washington.

39 

Segebaden GV. (1964). Studies of cross country transportation distances and net extension, Studia Forestalia Suecica, Nr.18.

40 

Sessions J. (2007). Forest Road Operations in the Tropics. Springer-Verlag, Berlin, Heidelberg, New York. ISBN-103-540-46392-5. 170 p.

41 

Seçkin Ö.B. (1978). Demirköy Karamanbayırı Devlet Orman işletmesi Çakmaktepe Bölgesi Yol Şebekesinin Planlama Tekniği Bakımından Araştırılması, OGM Yayınları No: 622/132, İstanbul.

42 

Suvinen A. (2006). A GIS-based Simulation Model for Terrain Tractability. Journal of Terramechanics. 43: 427-449.

43 

Şentürk N.; Öztürk T.; Demir M. (2007). Productivity and costs in the course of timber transportation with the Koller K300 cable system in Turkey. Building and Environment, 42: 2107-2113.

44 

Tucek J.; Pacola E. (1999). Algorithms for skidding distance modelling on a raster digital terrain model. Building and Environment, 10(1): 67-79.

45 

Visser R.; Stampfer K. (2015). Expanding Ground-Based Harvesting Onto Steep Terrain: A Review. Croatian Journal of Forest Engineering , 36(2): 321-331.


This display is generated from NISO JATS XML with jats-html.xsl. The XSLT engine is libxslt.

[hrvatski]

Posjeta: 474 *