Improving merge methods for grid-based digital elevation models
File(s)
Author(s)
Leitao, JP
Prodanovic, D
Maksimovic, C
Type
Journal Article
Abstract
Digital Elevation Models (DEMs) are used to represent the terrain in applications such as, for example, overland flow modelling or viewshed analysis. DEMs generated from digitising contour lines or obtained by LiDAR or satellite data are now widely available. However, in some cases, the area of study is covered by more than one of the available elevation data sets. In these cases the relevant DEMs may need to be merged. The merged DEM must retain the most accurate elevation information available while generating consistent slopes and aspects. In this paper we present a thorough analysis of three conventional grid-based DEM merging methods that are available in commercial GIS software. These methods are evaluated for their applicability in merging DEMs and, based on evaluation results, a method for improving the merging of grid-based DEMs is proposed. DEMs generated by the proposed method, called MBlend, showed significant improvements when compared to DEMs produced by the three conventional methods in terms of elevation, slope and aspect accuracy, ensuring also smooth elevation transitions between the original DEMs. The results produced by the improved method are highly relevant different applications in terrain analysis, e.g., visibility, or spotting irregularities in landforms and for modelling terrain phenomena, such as overland flow.
Date Issued
2016-01-06
Date Acceptance
2016-01-05
Citation
Computers and Geosciences, 2016, 88, pp.115-131
ISSN
0098-3004
Publisher
Elsevier
Start Page
115
End Page
131
Journal / Book Title
Computers and Geosciences
Volume
88
Copyright Statement
© 2016 Elsevier Ltd. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000370456200010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Physical Sciences
Computer Science, Interdisciplinary Applications
Geosciences, Multidisciplinary
Computer Science
Geology
Data merging
Digital elevation models
Grid-based rasters
Terrain analysis
DEM
Geochemistry & Geophysics
Earth Sciences
Information And Computing Sciences
Engineering
Publication Status
Published