182
Views
12
CrossRef citations to date
0
Altmetric
Original Articles

Morphological segmentation of physiographic features from DEM

, &
Pages 3379-3394 | Received 03 Jan 2005, Accepted 17 Nov 2005, Published online: 31 Jul 2007
 

Abstract

A terrain can be segmented into three predominant physiographic features; mountains, basins and piedmont slopes. The objective of this paper is to develop a mathematical morphological based algorithm to segment the terrain of a digital elevation model (DEM) into the three predominant physiographic features. Ultimate erosion is used to extract the peaks and pits of the DEM. Conditional dilation is performed on the peaks and pits of the DEM to extract the mountain and basin pixels, respectively. The unclassified pixels are assigned as piedmont slope pixels. The combination of the mountain, basin and piedmont slope regions form the physiographically segmented DEM. The effectiveness of the proposed physiographic segmentation algorithm is tested by implementing it on the Global Digital Elevation Model (GTOPO30) of the Great Basin, Nevada, USA.

Acknowledgment

The authors are grateful for, and this paper has benefited substantially from, the suggestions of an anonymous referee.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 689.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.