Mustafa AKGÜL, Tolga ÖZTÜRK, Necmettin ŞENTÜRK, Anıl Orhan AKAY, Abdullah İlker ESİN, Murat DEMİR

Evaluation of occupational accidents in forestry in Europe and Turkey by k-means clustering analysis

The incidence rate of occupational accidents is an important indicator of occupational safety performance. The aim of this study was to classify the similarities and differences among 23 European Union (EU) countries along with Turkey in terms of various occupational accident evaluation criteria. This was achieved using the k-means clustering method on data from the forestry and logging sector between 2008 and 2017. The occupational accident assessment criteria used in the study include the nonfatal male accident incidence rate, the nonfatal female accident incidence rate, the total (male + female) nonfatal accident incidence rate, and the total (male + female) fatal accident incidence rate. According to the clustering analysis, three clusters were obtained, and Turkey was included in Cluster 2. By evaluating the final cluster center values and the descriptive statistical values in the clusters, it was found that the occupational accident incidence values of the countries in Cluster 2 were in all four categories below the averages of the other two other clusters as well as the 23 EU countries and Turkey considered together. Cluster 1 was above all of the other clusters as well as all the countries considered together in the total nonfatal occupational accident category, and Cluster 3 in the fatal occupational accident category. Studies similar to this one but on an intercontinental basis would provide a good foundation for improving work health and safety legislation in forestry and logging on a global scale.

PDF

___

Acar H, Senturk N (1999). Artvin yöresindeki orman işçilerinde işçi sağlığı üzerine bir araştırma. İstanbul Üniversitesi Orman Fakültesi Dergisi 49 (1): 25-40.
Aggarwal CC, Reddy CK (2014). Data Clustering Algorithms and Applications. Boca Raton, FL, USA: CRC Press.
Albizu PM, Tolosana-Esteban E, Roman-Jordan E (2013). Safety and health in forest harvesting operations. Diagnosis and preventive actions. A review. Forest Systems 22 (3): 392-400. doi: 10.5424/fs/2013223-02714
Alguwaizani A, Hansen P, Mladenović N, Ngai E (2011). Variable neighborhood search for harmonic means clustering. Applied Mathematical Modelling 35 (6): 2688-2694. doi: 10.1016/j. apm.2010.11.032
Ambrosio Y, Tolosana ES Vignote M (2001). Análisis de la seguridad y salud laboral en los aprovechamientos forestales de cortas de claras en España.
Revista Chapingo Serie Ciencias Forestales y del Ambiente 7 (1): 55- 65 (in Spanish).
Bentley TA, Parker RJ, Ashby L (2005). Understanding felling safety in the New Zealand forest industry. Applied Ergonomics 36 (2): 165-175. doi: 10.1016/j.apergo.2004.10.009
Berg S, Fischbach J, Brüchert F, Poissonnet M, Pizzirani S et al. (2012). Towards assessing the sustainability of European logging operations. European Journal of Forest Research 131 (1): 81-94. doi: 10.1007/s10342-011-0561-x
Bernik R, Jeroncic R (2011). The comparison of number of deaths in accidents with the agriculture and forestry tractors among European countries. Acta Agriculturae Slovenica 97 (3): 213. doi: 10.2478/v10014-011-0015-7
Dalton L, Ballarin V, Brun M (2009). Clustering algorithms: on learning, validation, performance, and applications to genomics. Current Genomics 10 (6): 430-445. doi: 10.2174/138920209789177601
Dhillon IS, Modha DS (2001). Concept decompositions for large sparse text data using clustering. Machine Learning 42 (1): 143-175. doi: 10.1023/A:1007612920971
Enez K, Topbas M, Acar HH (2014). An evaluation of the occupational accidents among logging workers within the boundaries of Trabzon Forestry Directorate, Turkey. International Journal of Industrial Ergonomics 44 (5): 621-628. doi: 10.1016/j. ergon.2014.07.002
Engsaas J (1993). Accidents in small-scale forestry. Department of Operational Efficiency, Swedish University of Agricultural Sciences, Research Note 251. Uppsala, Sweden: Swedish University of Agricultural Sciences.
Eurostat (2013). European statistics on accidents at work (ESAW) Summary methodology. 2013 ed. Luxembourg: Eurostat European Commission.
FAO (2018). Accident reporting and analysis in forestry guidance on increasing the safety of forest work. Rome, Italy: Food and Agriculture Organization of the United Nations.
Gellerstedt S, Dahlin B (1999). Cut-to-length: the next decade. Journal of Forest Engineering 10 (2): 17-24.
Grzywiński W, Skonieczna J, Jelonek T, Tomczak A (2020). The influence of the privatization process on accident rates in the forestry sector in Poland. International Journal of Environmental Research and Public Health 17 (9): 3055. doi: 10.3390/ijerph17093055
Gumus S, Okan SU, Hatay TY (2019). Analysis of work accidents in wood harvesting: a case study of the East Black Sea region. Forestist 70 (1): 1-7. doi: 10.5152/forestist.2020.19008
Hartigan JA, Wong MA (1979). Algorithm AS 136: A k-means clustering algorithm. Journal of the Royal Statistical Society Series C (Applied Statistics) 28 (1): 100-108.
Jain AK (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters 31 (8): 651-666. doi: 10.1016/j. patrec.2009.09.011
Jankovský M, Merganič J, Allman M, Ferenčík M, Messingerová V (2018). The cumulative effects of work-related factors increase the heart rate of cabin field machine operators. International Journal of Industrial Ergonomics 65: 173-178. doi: 10.1016/j. ergon.2017.08.003
Javadi S, Hashemy SM, Mohammadi K, Howard KWF, Neshat A (2017). Classification of aquifer vulnerability using K-means cluster analysis. Journal of Hydrology 549: 27-37. doi: 10.1016/j. jhydrol.2017.03.060
Kijewska A, Bluszcz, A (2016). Research of varying levels of greenhouse gas emissions in European countries using the k-means method. Atmospheric Pollution Research 7 (5): 935-944. doi: 10.1016/j. apr.2016.05.010
Klun J, Medved M (2007). Fatal accidents in forestry in some European countries. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering 28 (1): 55-62.
Krishna K, Murty MN (1999). Genetic K-means algorithm. IEEE Transactions on Systems, Man, and Cybernetics 29 (3): 433- 439.
Li C, Sun L, Jia J, Cai Y, Wang X (2016). Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China. Science of the Total Environment 557-558: 307-316. doi: 10.1016/j.scitotenv.2016.03.069
Li B, Fan ZT, Zhang XL, Huang DS (2019). Robust dimensionality reduction via feature space to feature space distance metric learning. Neural Networks 112: 1-14. doi: 10.1016/j. neunet.2019.01.001
Lilley R, Feyer AM, Kirk P, Gander P (2002). A survey of forest workers in New Zealand: Do hours of work, rest, and recovery play a role in accidents and injury? Journal of Safety Research 33 (1): 53-71. doi: 10.1016/S0022-4375(02)00003-8
Lindroos O, Burström L (2010). Accident rates and types among self-employed private forest owners. Accident Analysis & Prevention 42 (6): 1729-1735. doi: 10.1016/j.aap.2010.04.013
MacQueen J (1967). Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Oakland, CA, USA. pp. 281-297.
Marola KV, Kbnt J, Bibly JM (1979). Multivariate analysis. AcadeInic Press, Londres.
Mauro R., De Luca, M, Dell’Acqua G (2013). Using a k-means clustering algorithm to examine patterns of vehicle crashes in before-after analysis. Modern Applied Science 7 (10): 11. doi: 10.5539/mas.v7n10p11
Mitchell R, Driscoll T, Healey S, Mandryk J, Hendrie L et al. (2001). Fatal injuries in forestry and logging work in Australia, 1989 to 1992. Journal of Occupational Health and Safety-Australia and New Zealand 17 (6): 567-577.
Montorselli NB, Lombardini C, Magagnotti N, Marchi E, Neri F et al. (2010). Relating safety, productivity and company type for motor-manual logging operations in the Italian Alps. Accident Analysis & Prevention 42 (6): 2013-2017. doi: 10.1016/j. aap.2010.06.011
Nikooya M, Naghdi R, Nouroozıa Z (2012). Analysis of forest logging work accident case study, west forest of Guilan province. Journal of Forest and Wood Products (Jfwp) (Iranıan Journal of Natural Resources) 64 (4): 475-486.
Ovaskainen H, Heikkilä M (2007). Visuospatial cognitive abilities in cut-to-length single-grip timber harvester work. International Journal of Industrial Ergonomics 37 (9-10): 771-780. doi: 10.1016/j.ergon.2007.06.004
Ozcan M (2008). Avrupa Birliği ormancılık politikaları ve Türkiye ormancılığının bu politikalara uyumu. MSc, Süleyman Demirel University, Isparta, Turkey (in Turkish).
Pandit YP, Badhe YP, Sharma BK, Tambe SS, Kulkarni BD (2011). Classification of Indian power coals using K-means clustering and self organizing map neural network. Fuel 90 (1): 339-347. doi: 10.1016/j.fuel.2010.09.012
Potočnik I, Pentek T, Poje A (2009). Severity analysis of accidents in forest operations. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering 30 (2): 171-184.
Sangita O, Dhanamma J (2011). An improved k-means clustering approach for teaching evaluation. In: Unnikrishnan S, Surve S, Bhoir D (editors). Advances in Computing, Communication and Control. ICAC3 2011. Communications in Computer and Information Science, Vol. 125. Berlin, Germany: Springer, pp. 108-115. doi: 10.1007/978-3-642-18440-6_13
Shakeel PM, Baskar S, Dhulipala VS, Jaber MM (2018). Cloud based framework for diagnosis of diabetes mellitus using K-means clustering. Health Information Science and Systems 6 (1): 1-7. doi: 10.1007/s13755-018-0054-0
Shi BQ, Liang, J, Liu Q (2011). Adaptive simplification of point cloud using k-means clustering. Computer-Aided Design 43 (8): 910- 922. doi: 10.1016/j.cad.2011.04.001
Spinelli R, Magagnotti N, Facchinetti D (2013). Logging companies in the European mountains: an example from the Italian Alps. International Journal of Forest Engineering 24 (2): 109-120. doi: 10.1080/14942119.2013.838376
Suchomel J, Belanová K, Vlčková M (2013). Analysis of work accidents in selected activities in Slovakia, Czech Republic and Austria. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering 34 (2): 311-320.
Thelin A (2002). Fatal accidents in Swedish farming and forestry, 1988–1997. Safety Science 40 (6): 501-517. doi: 10.1016/S0925- 7535(01)00017-0
Tsioras PA, Rottensteiner C, Stampfer K (2011). Analysis of accidents during cable yarding operations in Austria 1998–2008. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering 32 (2): 549-560.
Tsioras PA, Rottensteiner C, Stampfer K (2014). Wood harvesting accidents in the Austrian state forest enterprise 2000–2009. Safety Science 62: 400-408. doi: 10.1016/j.ssci.2013.09.016
Ward Jr JH (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58 (301): 236-244.
Wei L, Villemey A, Hulin F, Bilger I, Yann D et al. (2015). Plant diversity on skid trails in oak high forests: A matter of disturbance, micro-environmental conditions or forest age? Forest Ecology and Management 338: 20-31. doi: 10.1016/j.foreco.2014.11.018
Wilhelmson E, Wästerlund DS, Burström L, Bylund PO (2005). Public health effects of accidents in self-employed forestry work. Small-Scale Forest Economics, Management and Policy 4 (4): 427-435. doi: 10.1007/s11842-005-0026-5
Wu X, Wu B, Sun J, Qiu S, Li X (2015). A hybrid fuzzy K-harmonic means clustering algorithm Applied Mathematical Modelling 39 (12): 3398-3409. doi: 10.1016/j.apm.2014.11.041
Yock AD, Kim GY (2017). Using k-means clustering to determine the number and position of isocenters in MLC-based multiple target intracranial radiosurgery. Journal of Applied Clinical Medical Physics 18 (5): 351-357. doi: 10.1002/acm2.12139