630
Views
19
CrossRef citations to date
0
Altmetric
Original Articles

The new high-resolution LiDAR digital height model (‘Ny Nationell Höjdmodell’) and its application to Swedish Quaternary geomorphology

, &
Pages 145-151 | Received 11 Dec 2012, Accepted 12 Dec 2012, Published online: 22 May 2013
 

Abstract

This letter outlines the abilities and potential applications of the Swedish ‘Ny Nationell Höjdmodell’ (new national height model), with particular reference to the mapping of Quaternary landforms. The application of high-resolution, light-detection and ranging data allows the mapping of terrain in an unprecedented level of detail, even under dense forest cover that has previously hidden key features from view. The new data set can be applied in a variety of ways: from digital morphological analysis to the production of field reconnaissance maps when combined with geographical information systems (GIS) layers such as access routes and landownership. It is hoped that this will start a national effort of applying the new national height model across the geological sciences. Encouraging cooperation and collaboration across interested parties within Sweden is vital in order to get the most out of this rich new source of data.

Acknowledgements

The authors would like to thank Mark Johnson and Clas Hättestrand for comment and discussion related to the use of the NNH and cooperation within Sweden, and Karin Larsson for technical support.

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 110.00 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.