Analysis of topographic maps for recreational purposes using decision trees

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Publication Type pre-print
School or College College of Engineering
Department Computing, School of
Creator Henderson, Thomas C.
Other Author Kirby, Richard
Title Analysis of topographic maps for recreational purposes using decision trees
Date 2013-01-01
Description In this paper we describe a method for predicting the subjective quality of a new mountain bike route for a particular subject based on routes previously ridden and ranked by the subject. GPS tracks of the previously ridden routes are over laid on rasterized topographic maps and topographic features are extracted in the vicinity of the routes using image processing techniques. The subject ranks each previously ridden route segment on four subjective qualities. The extracted topographic features and the subjective rankings are used as input vectors and target vectors to train a series of decision trees. The decision trees are then tested on a series of route segments not used in the decision tree training. The decision trees were able to exactly predict the subjective rankings with over 60% accuracy vs. 20% accuracy for random selection. When close matches are allowed in the prediction of subjective ranking (plus or minus one point vs. actual) the accuracy of the decision trees increased to 90% and above.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 1105
Last Page 1109
Language eng
Bibliographic Citation Kirby, R., & Henderson, T. C. (2013). Analysis of topographic maps for recreational purposes using decision trees. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 6628785, 1105-9.
Rights Management (c) 2013 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 323,787 bytes
Identifier uspace,18349
ARK ark:/87278/s6tx6qbq
Setname ir_uspace
Date Created 2014-02-20
Date Modified 2014-02-20
ID 711325
Reference URL
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