Computing watersheds on triangulated terrain models in a robust manner is a difficult task as it is sensitive to noise that appears in the elevation values of the input. This is amplified by the existence of many very small watersheds (corresponding to spurious minima) that obscure the overall hydrological structure of the terrain. In the present work we perform an experimental evaluation of various algorithms that may help alleviate these problems: We introduce and experimentally investigate algorithms for matching watersheds in different instances of a triangulated terrain that arise from adding noise to the elevations of the terrain model. These algorithms can be used to see which parts of a computed watershed map are reliable in the presence of noise. We compare two methods for merging small watersheds into larger ones. We use these methods in combination with the watershed matching algorithms to assess which merging method is most effective in facilitating successful matching of watersheds. We have evaluated the performance of the studied methods using a software package that we developed for computing watersheds on triangulated terrains. To our knowledge, this package is the first to use a robust flow model together with exact arithmetic.
|Title of host publication||Proceedings 19th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems (ACM-GIS 2011, Chicago IL, USA, November 1-4, 2011)|
|Place of Publication||New York NY|
|Publisher||Association for Computing Machinery, Inc|
|Publication status||Published - 2011|