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UBC Theses and Dissertations

Evolutionary automata for visual resource management planning and harvest design Chamberlain, Brent Charles

Abstract

Increasing pressure to harvest in scenic vistas as a result of increased timber demand has caused significant changes to many beautiful natural scenes. Visual Resource Management aims to reduce the impact of harvests and improve their scenic design while trying to minimize the effect on timber availability. This thesis focuses on two main outcomes. First, a program was created that is capable of automating aspects of the design process in Visual Resource Management. The program, or Model, uses a modified genetic algorithm in combination with a geographical information system to create a final harvest plan that minimizes negative visual impacts for any given timber extraction level. The Model was tested across an array of different landscape terrain, including mountains, hills and valleys, to show its ability to deal with complex situations. Second, the thesis was created to better understand the relationship between timber availability and visible alteration. Results suggest a capacity for increased levels of aesthetic design while also increasing timber availability when compared with previous studies. Thus, the end product is a program that is capable of being adapted to real world situations by aiding in the harvest design process and producing a plan that tries to maximize both timber availability and the aesthetic properties of a landscape. This decision support tools allows planners to manipulate "what if” scenarios to ascertain the effects of varying timber extraction levels and visible alteration percentages.

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