A localized contour tree method for deriving geometric and topological properties of complex surface depressions based on high-resolution topographical data

Qiusheng Wu, Hongxing Liu, Shujie Wang, Bailang Yu, Richard Beck, Kenneth Hinkel

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Surface depressions are abundant in topographically complex landscapes, and they exert significant influences on hydrological, ecological, and biogeochemical processes at local and regional scales. The increasing availability of high-resolution topographical data makes it possible to resolve small surface depressions. By analogy with the reasoning process of a human interpreter to visually recognize surface depressions from a topographic map, we developed a localized contour tree method that is able to fully exploit high-resolution topographical data for detecting, delineating, and characterizing surface depressions across scales with a multitude of geometric and topological properties. In this research, we introduce a new concept ‘pour contour’ and a graph theory-based contour tree representation for the first time to tackle the surface depression detection and delineation problem. Beyond the depression detection and filling addressed in the previous raster-based methods, our localized contour tree method derives the location, perimeter, surface area, depth, spill elevation, storage volume, shape index, and other geometric properties for all individual surface depressions, as well as the nested topological structures for complex surface depressions. The combination of various geometric properties and nested topological descriptions provides comprehensive and essential information about surface depressions across scales for various environmental applications, such as fine-scale ecohydrological modeling, limnological analyses, and wetland studies. Our application example demonstrated that our localized contour tree method is functionally effective and computationally efficient.

Original languageEnglish (US)
Pages (from-to)2041-2060
Number of pages20
JournalInternational Journal of Geographical Information Science
Volume29
Issue number12
DOIs
StatePublished - Dec 2 2015

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

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