Machine productivity evaluation for harvesters and forwarders in thinning operations in Australia.
Mohammad Reza Ghaffariyan, Mauricio Acuña, Mark Brown
Abstract
Mohammad Reza Ghaffariyan, Mauricio Acuña, Mark Brown
Abstract
Investment in thinning as part of forest management is generally for one of three purposes: improved future stand growth and quality to produce higher value products for later final harvest, removal of fuels to reduce fire risk or to meet ecological goals such as increasing biodiversity. The focus of this paper is on the thinning operations in Australian pine and eucalypt plantations, which are almost exclusively conducted by harvester-processors and forwarders. The Australian Forest Operations Research Alliance (AFORA) has conducted research projects on assessing the productivity of harvester-processors and forwarders in pine and eucalypt plantations in different sates/regions. All-time study data collected in different case studies have been consolidated into a data base called ALPACA (Australian Logging Productivity and Cost Appraisal). The data were used to develop the general productivity predicting models for harvester and forwarder based on multiple regression modelling. Harvester productivity was mainly a function of tree volume. Forwarder productivity was primarily a function of extraction distance. Slope has been included in the models as a weighting factor based on three classes and namely <15%, from 15% to 25% and >25%.
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Investment in thinning as part of forest management is generally for one of three purposes: improved future stand growth and quality to produce higher value products for later final harvest, removal of fuels to reduce fire risk or to meet ecological goals such as increasing biodiversity. The focus of this paper is on the thinning operations in Australian pine and eucalypt plantations, which are almost exclusively conducted by harvester-processors and forwarders. The Australian Forest Operations Research Alliance (AFORA) has conducted research projects on assessing the productivity of harvester-processors and forwarders in pine and eucalypt plantations in different sates/regions. All-time study data collected in different case studies have been consolidated into a data base called ALPACA (Australian Logging Productivity and Cost Appraisal). The data were used to develop the general productivity predicting models for harvester and forwarder based on multiple regression modelling. Harvester productivity was mainly a function of tree volume. Forwarder productivity was primarily a function of extraction distance. Slope has been included in the models as a weighting factor based on three classes and namely <15%, from 15% to 25% and >25%.
Key concepts: Thinning, Productivity, Computer science, Economics, Geography, Forestry, Macroeconomics