A genetic algorithm for tributary selection with consideration of different factors
ISBN 978-85-88783-11-9
Authors
1Zhang, L.; 2Guilbert, E.; 3Long, Y.
1NANJING NORMAL UNIVERSITY Email: lingzhang.sky@gmail.com
2LAVAL UNIVERSITY Email: eric.guilbert.1@ulaval.ca
3NANJING NORMAL UNIVERSITY
Abstract
In both GIS and terrain analysis, drainage systems are important components. Owing to local topography and subsurface geology, a drainage system achieves a particular drainage pattern based on the form and texture of its network of stream channels and tributaries. The drainage pattern can reflect the geographical characteristics of a river network to a certain extent, because it depends on the topography and geology of the land. Whether in cartography or GIS, hydrography is one of the most important feature classes to be generalized to produce representations at various levels of detail. Recently, many researchers have paid more attention on geospatial patterns in cartographic generalization. In order to preserve knowledge about the network, this arrangement, characterized by statistical parameters such as the average junction angle or tributary length, computed at the network level needs to be maintained. As these parameters are more or less relevant according to the pattern, this paper proposes a solution to deal with multiple factors at the same time in river tributary selection. The multi-objective optimization problem is solved through a genetic algorithm with consideration of the drainage pattern. According to the pattern characteristics of each drainage network, factors, such as the stream order and the tributary balance, are considered and translated into objective functions. In the multi-objective model, different weights are used to aggregate all objective functions into a fitness function. The method is applied on a case study to evaluate the importance of each factor for different types of drainage and results are compared with a manually generalized network.