Amélioration de la planification opérationnelle par une connaissance plus précise des stocks forestiers (produits spécifiques) et de leur localisation en forêt
|Advisor:||Lowell, Kim; Lebel, Luc|
|Abstract:||Presently forest products transformation centers must be able to quickly adapt their resource supply in order to satisfy market needs. In order to react quickly to mill demands, forest harvesting activities must be deployed directly in forest stands that contain standing timber with the characteristics necessary to meet processing requirements. An inability to do this engenders involves additional costs related to the installation of corrective measures. Such measures usually result in an increase in forest stocks cut and/or in additional displacements of forest harvesting equipment. A shortage of supply -- i.e. a lack of raw material at the processing plant -- or difficulty in satisfying market needs are other possible effects. An adequate knowledge of standing tree distributions by species and diameter classes for the principal forest strata being harvested thus seems to be a useful way of ensuring adequate product-specific supply. Such knowledge indeed would seem to be required to improve forest management across the entire supply chain, and would also provide for better environmental protection. However, because forests are intrinsically highly variable, it is difficult to predict in a precise manner species and diameter distributions for specific stands in a given forest. This inherent forest variability generates uncertainty when these distributions are estimated or predicted. This project evaluates the developmental feasibility of a spatial system that can enable an immediate response in harvesting operations to a request for a specific species and size of tree by a processing facility that is motivated by clients’ needs. To accomplish this, species-specific graphic functions of volumes based on tree diameter distributions for each forest stratum were developed and compiled. Regression equations based on tree diameter were applied to these functions in order to validate those that were significant. Subsequently a link was established between the diameter distribution functions and a map of forest strata in a GIS software tool to obtain the probability of finding a sufficient volume of the desired tree type. The functionality discussed has been successfully implemented in this project in order to create a tool for forest planners that takes into account the variability of timber stocks in forests. This project has demonstrated that it is possible to use existing forest inventory information to develop relations between the forest data and the error it generates. Moreover, it was possible to integrate this information to create a functional GIS-based tool that indicates the likelihood of finding a desired quantity of a specific product in the forest.|
|Document Type:||Mémoire de maîtrise|
|Open Access Date:||16 April 2018|
|Collection:||Thèses et mémoires|
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