Development of a wood damage monitoring system for mechanized harvesting
DOI:
https://doi.org/10.15287/afr.2018.1084Keywords:
forwarder, image processing, quality monitoring, single-grip harvester, tree damage, sustainable wood supplyAbstract
Cut-to-length harvesting is a cost-efficient method of the wood supply chain. However, it risks causing stem damage in the mechanized process of thinning forest stands, thereby reducing the growth and technical quality of the remaining trees, which would then be exposed on the increased vulnerability to fungal diseases. For these reasons, it is critical to support quality monitoring of harvesting machines. One way to support quality monitoring is through the application of machine vision solutions. In this study, the damaged stems were photographed systematically from a strip road. The success of the stem-damage detection was analyzed to determine the relationships between successful detection, stand condition, and the image-processing technique. Statistically meaningful relationships were identified via logistic regression analysis, which can be used in selection of tailored image processing technique. The study indicated that the quality-monitoring system of mechanized harvesting could be improved by an increased focus on developing the multi-view photogrammetry of stem damages according to different stand conditions. Further, refining the machine learning system would support the need to determine accurate image-processing thresholds of the texture of stem damages. Then, the overall proportion of successful stem-damage detections will be 89%. These improvements of the quality monitoring system will provide the efficient thinning process in the sustainable wood supply from forests to forest industry. The implementation of such a system could be much broader, initially under Nordic conditions and then in other countries as well, given that its development takes into considerations the significant calibration factors of local conditions.References
Acuna M., 2017. Automated volumetric measurement of truckloads through multi-view photogrammetry and 3D image processing software. In: FORMEC 2017: 50th anniversary of the International Symposium on Forestry Mechanization, September 25-29, 2017, Braşov, Romania, pp. 1–4.
Adekunle V.A.J., Olagoke A.O., 2010. The impacts of timber harvesting on residual trees and seedlings in a tropical rainforest ecosystem, south-western Nigeria. International Journal of Biodiversity Science, Ecosystem Services & Management 6(3-4): 131–138.
Anonymous 2015. National Forest Strategy 2025. Publications of the Ministry of Agriculture and Forestry 6b/2015. http://mmm.fi/en/nfs. Accessed 02 January 2018.
Anonymous 2017a. Official Statistics of Finland (OSF): Wood Consumption & Cutting areas [e-publications]. Helsinki: Natural Resources Institute Finland.
Anonymous 2017b. Statistical information about the quality of harvesting for the years 2011–2015. Finnish Forest Centre. http://www.metsakeskus.fi/sites/default/files/. Accessed 02 January 2018
Anonymous 2017c. Finnish Forest Centre. Field audit manual. Web: http://www.metsakeskus.fi/sites/default/files/smk-maastotarkastusohje-2016.pdf. Accessed: 02 January 2018
Apafaian A., Boghian V., Bratu A., 2015. A Literature Review Related to the Modern Harvesting - Forwarding Equipment and the Main Topics Concern of the Research Community. Horticulture and Forestry - Review articles 72(1): 1–16.
Athanassadis D., 1997. Residual stand damage following cut-to-length harvesting operations with a farm tractor in two conifer stands. Silva Fennica 31(4): 461–467. DOI: 10.14214/sf.a8541
Behjou FK., Mollabashi OG., 2012. Selective logging and damage to unharvested trees in a Hyrcanian forest of Iran. BioResources 7(4): 4867–4874. DOI: 10.15376/biores.7.4.4867-4874
Borz SA., Acuna M., Heinimann HR., Palander T., Spinelli R., 2017. Innovating the competitive edge: from research to impact in the forest value chain”: the half-century of FORMEC. Annals of Forest Research 60(2): 199–201. DOI: 10.15287/afr.2017.914
Camp A., 2002. Damage to residual trees by four mechanized harvest systems operating in small-diameter, mixed-conifer forests on steep slopes in North-eastern Washington: a case study. Western Journal of Applied Forestry 17(1): 14–22.
Cox DR., 1958. The regression analysis of binary sequences (with discussion). Journal of the Royal Statistical Society 20: 215–242.
Egan AF., 1999. Residual stand damage after shovel logging and conventional ground skidding in an Appalachian hardwood stand. Forest Products Journal 49(6): 88–92.
Eroǧlu H., Öztürk UÖ., Sönmez T., Tilki F., Akkuzu E., 2009. The impacts of timber harvesting techniques on residual trees, seedlings, and timber products in natural oriental spruce forests. African Journal of Agricultural Research 4(3): 220–224.
Forsman M., Börlin N., Holmgren J., 2016. Estimation of tree stem attributes using terrestrial photogrammetry with a camera rig. Forests 7(3): 61. DOI: 10.3390/f7030061
Granhus A., Fjeld D., 2001. Spatial distribution of injuries to Norway spruce advance growth after selection harvesting. Canadian Journal of Forest Research 31(11): 1903–1913. DOI: 10.1139/x01-103
Han H-S., Kellogg LD., 2000a. Damage characteristics in young Douglas-fir stands from commercial thinning with four timber harvesting systems. Western Journal of Applied Forestry 15(1): 27–33.
Han H-S., Kellogg LD., 2000b. A comparison of sampling methods and a proposed quick survey for measuring residual stand damage from commercial thinning. Journal of Forest Engineering 11(1): 63–69.
Harstela P., 1997. Decision support systems in wood procurement. A review. Silva Fennica 31(2): 215–223. DOI: 10.14214/sf.a8520
Hassler CC., Grushecky ST., Fajvan MA., 1999. An assessment of stand damage following timber harvests in West Virginia. Northern Journal of Applied Forestry 16(4): 191–196.
Heitzman E., Grell A.G. 2002. Residual tree damage along forwarder trails from cut-to-length thinning in Maine spruce stands. Northern Journal of Applied Forestry 19(4): 161–167.
Hosmer D.W., Lemeshow S., 2000. Applied logistic regression. John Wiley & Sons, New York. ISBN: 0-471-35632-8. DOI: 10.1002/0471722146
Huang T., Li B., Shen D., Cao J., Mao B., 2017. Analysis of the grain loss in harvest based on logistic regression. Information Technology and Quantitative Management. Procedia Computer Science 122: 698–705. DOI: 10.1016/j.procs.2017.11.426
Hyyppä J., Virtanen J-P., Jaakkola A., Yu X., Hyyppä H., Liang X., 2018. Feasibility of Google Tango and Kinect for crowdsourcing forestry information. Forests 9(6): 6.
Košir B., 2008. Modelling stand damages and comparison of two harvesting methods. Croatian Journal of Forest Engineering 29(1): 5–14.
Laukkanen S., Palander T., Kangas J., 2004. Applying voting theory in participatory decision support for sustainable timber harvesting. Canadian Journal of Forest Research 34(7): 1511–1524. DOI: 10.1139/x04-044
Luo L., Tang Y., Zou X., Wang C., Zhang P., Feng W., 2016. Robust grape cluster detection in a vineyard by combining the AdaBoost framework and multiple color components. Sensors 16(12): 2098. DOI: 10.3390/s16122098
Mäkinen H., Hallaksela A-M., Isomäki A., 2007. Increment and decay in Norway spruce and Scots pine after artificial logging damage. Canadian Journal of Forest Research 37(11): 2130–2141. DOI: 10.1139/X07-087
Modig E., Magnusson B., Valinger E., Cedergren J., Lundqvist L., 2012. Damage to residual stand caused by mechanized selection harvest in uneven-aged Picea abies dominated stands. Silva Fennica 46(2): 267–274. DOI: 10.14214/sf.442
Naghdi R., Bagheri I., Taheri K., Akef M., 2009. Residual stand damage during cut-to-length harvesting method in Shafaroud forest of Guilan province. Journal of Environmental Sciences 60: 931–947.
Nakou A., Sauter UH., Kohnle U., 2016. Improved models of harvest-induced bark damage. Annals of Forest Science 73(2): 233–246. DOI: 10.1007/s13595-015-0530-5
Nevalainen P., Salmivaara A., Ala-Ilomäki J., Launiainen S., Hiedanpää J., Finér L., Pahikkala P., Heikkonen J., 2017. Estimating the Rut Depth by UAV Photogrammetry. Remote Sensing 9(12): 1279. DOI: 10.3390/rs9121279
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
Palander T., 1999. A hierarchical participatory methodology for tactical decision-making based on a decision-analytic model for balancing timber stock. Scandinavian Journal of Forest Research 14(6): 567–580. DOI: 10.1080/02827589908540822
Picchio R., Neri F., Maesano M., Savelli S., Sirna A., Blasi S., Baldini S., Marchi E., 2011. Growth effects of thinning damage in a Corsican pine (Pinus laricio Poiret) stand in central Italy. Forest Ecology and Management 262(2): 237–243. DOI: 10.1016/j.foreco.2011.03.028
Pryor MG., Toombs L., Anderson D., White JC., 2010. What management and quality theories are best for small businesses? Journal of Management and Marketing Research 3: 20–32.
Rodríguez-García C., Montes F., Ruiz F., Canellas I., Pita P., 2014. Stem mapping and estimating standing volume from stereoscopic hemispherical images. European Journal of Forest Research 133(5): 895–904. DOI: 10.1007/s10342-014-0806-6
Rose J.C., Paulus S., Kuhlmann H., 2015. Accuracy analysis of a multi-view stereo approach for phenotyping of tomato plants at the organ level. Sensors 15(5): 9651–9665. DOI: 10.3390/s150509651
Rosenfeld A., 2015. Picture processing by computer. Academic Press, New York.
Sonka, M., Hlavac, V., Boyle, R., 2015. Image processing, analysis and machine vision. Fourth edition. ISBN 1-133-59360-7.
Spinelli R., Lombardini C., Magagnotti N., 2014. The effect of mechanization level and harvesting system on the thinning cost of Mediterranean softwood plantations. Silva Fennica 48(1): 1–15. DOI: 10.14214/sf.1003
Surakka H., Sirén M., Heikkinen J., Valkonen S., 2011. Damage to saplings in mechanized selection cutting in uneven-aged Norway spruce stands. Scandinavian Journal of Forest Research 26(3): 232–244. DOI: 10.1080/02827581.2011.552518
Tavankar F., Majnounian B., Bonyad A.E., 2013. Felling and skidding damage to residual trees following selection cutting in Caspian forests of Iran. Journal of Forestry 59(5): 196–203.
Tsioras, P.A., Liamas, D.K., 2015. Residual tree damage along skidding trails in beech stands in Greece. Journal of Forestry Research 26, 523–531. DOI: 10.1007/s11676-015-0056-6
Vasiliauskas R., 2001. Damage to trees due to forestry operations and its pathological significance in temperate forests: a literature review. Forestry 74(4): 319–336. DOI: 10.1093/forestry/74.4.319
Waters I., Kembel S.W., Gingras J.F., Shay J.M., 2004. Short-term effects of cut-to-length versus full-tree harvesting on conifer regeneration in jack pine, mixed wood, and black spruce forests in Manitoba. Canadian Journal of Forest Research 34(9): 1938–1945. DOI: 10.1139/x04-064
Published
Issue
Section
License
All the papers published in Annals of Forest Research are available under an open access policy (Gratis Gold Open Access Licence), which guaranty the free (of taxes) and unlimited access, for anyone, to entire content of the all published articles. The users are free to “read, copy, distribute, print, search or refers to the full text of these articles”, as long they mention the source.
The other materials (texts, images, graphical elements presented on the Website) are protected by copyright.
The journal exerts a permanent quality check, based on an established protocol for publishing the manuscripts. The potential article to be published are evaluated (peer-review) by members of the Editorial Board or other collaborators with competences on the paper topics. The publishing of manuscript is free of charge, all the costs being supported by Forest Research and Management Institute.
More details about Open Access:
Wikipedia: http://en.wikipedia.org/wiki/Open_access
