The application of route network analysis to commercial forestry transportation in the north coast of Kwazulu-Natal.

Abstract

Transportation costs of commercial forestry farms in South Africa are generally very high, causing great economic concern. The current roads of the majority of commercial farms, used to transport timber from the compartments to the market (mill), form part of a 'cob-web', high density network. In order to optimise transportation, it is beneficial to eradicate such a high density of road, achieved by adopting the most effective methods and technology. Such methods include that of Route Network Analysis (RNA) which designs a minimalist, yet cost-effective road pattern of a forestry farm. The aim of the study was to determine what data are required to optimise economic and timber transportation, based on the commercial forestry farm of Ntonjaneni, located in Zululand, KwaZulu-Natal. Route Network Analysis, which incorporates Geographical Information Systems (GIS) in addition to the current information pertaining to a network, was applied to the Ntonjaneni Farm. The existing data consisted of cadastral shapefile data containing relative attribute data, as well as Digital Elevation Models (DEMs), which were manipulated in order to create a realistic spatial representation of the farm's current transportation network. In addition, the development of project management guidelines to assist the efficient implementation and completion of the analysis was undertaken. The most ideal route from the plantations to the mill was created, avoiding the environmentally buffered rivers and those slopes which were too steep. As a result, the network was greatly improved. The irrelevant roads were removed, and replaced with a less dense route for timber transportation. The results of the RNA reveal that RNA, completed by the project management guidelines, is an effective and environmentally sound means of optimising commercial forestry transportation. However, data relating to the rivers and road slope need to be updated in order for RNA to be effectively performed during future studies.