The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Petter Pilesjö

Petter Pilesjö

Professor

Petter Pilesjö

A combined algorithm for automated drainage network extraction from digital elevation models

Author

  • Yanzi Yan
  • Jing Tang
  • Petter Pilesjö

Summary, in English

Drainage networks are the basis for segmentation of watersheds, an essential component in hydrological modelling, biogeochemical applications, and resource management plans. With the rapidly increasing availability of topographic information as digital elevation models (DEMs), there have been many studies on DEM-based drainage network extraction algorithms. Most of traditional drainage network extraction methods require preprocessing of the DEM in order to remove “spurious” sink, which can cause unrealistic results due to removal of real sinks as well. The least cost path (LCP) algorithm can deal with flow routing over sinks without altering data. However, the existing LCP implementations can only simulate either single flow direction or multiple flow direction over terrain surfaces. Nevertheless, terrain surfaces in the real world are usually very complicated including both convergent and divergent flow patterns. The triangular form-based multiple flow (TFM) algorithm, one of the traditional drainage network extraction methods, can estimate both single flow and multiple flow patterns. Thus, in this paper, it is proposed to combine the advantages of the LCP algorithm and the TFM algorithm in order to improve the accuracy of drainage network extraction from the DEM. The proposed algorithm is evaluated by implementing a data-independent assessment method based on four mathematical surfaces and validated against “true” stream networks from aerial photograph, respectively. The results show that when compared with other commonly used algorithms, the new algorithm provides better flow estimation and is able to estimate both convergent and divergent flow patterns well regarding the mathematical surfaces and the real-world DEM.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • Centre for Geographical Information Systems (GIS Centre)
  • Centre for Advanced Middle Eastern Studies
  • MECW: The Middle East in the Contemporary World
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2018-05-15

Language

English

Pages

1322-1333

Publication/Series

Hydrological Processes

Volume

32

Issue

10

Document type

Journal article

Publisher

John Wiley and Sons

Topic

  • Oceanography, Hydrology, Water Resources

Keywords

  • digital elevation models
  • drainage networks extraction
  • hydrology
  • multiple flow patterns
  • sink treatment
  • watershed

Status

Published

ISBN/ISSN/Other

  • ISSN: 0885-6087