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A Knowledge-based System for Selection of Trees for Urban Environments

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Author(s): J.O. Gwendo | L. Muchemi

Journal: Journal of Artificial Intelligence
ISSN 1994-5450

Volume: 5;
Issue: 1;
Start page: 37;
Date: 2012;
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Keywords: Jess | urban forestry | Knowledge-based system

ABSTRACT
Urban forestry is key in mitigating the environmental effects of urbanization however urban environments presents arboricultural challenges such as limited root and canopy space, poor soil quality, deficiency among others. This study presents findings of investigation into challenges caused by planting of inappropriate tree species and proposes a knowledge-based model. The model is validated through experiments based on a prototype that assists in the selection of the appropriate tree species for the diverse urban environments. Through the research it was evident that a better understanding of how urban ecosystems functions, how to take care of trees, where to strategically plant them and how to maintain them is the only way to maximize potential benefits of urban trees. The prototype was evaluated through selected test cases and the results were fairly accurate and promising when compared with the results of domain experts. Such a system would assist Governments, city-planners and conservationists to plan in advance for urbanizations threats to nature and thus shape the growth of cities through incorporation of successful urban forests initiatives.

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