Improving merge methods for grid-based digital elevation models

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 stud...

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Veröffentlicht in:Computers & geosciences 2016-03, Vol.88, p.115-131
Hauptverfasser: Leitao, J P, Prodanovic, D, Maksimovic, C
Format: Artikel
Sprache:eng
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Zusammenfassung: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. •A new merge method for raster data sets, called MBlend, is presented.•MBlend is tested in two areas in the UK, using four different elevation data sets.•MBlend is compared with conventional raster data sets merging methods.•MBlend produces smoother transitions between the raster data sets being merged.•MBlend retains the information of the most accurate and detailed raster data set.
ISSN:0098-3004
1873-7803
DOI:10.1016/j.cageo.2016.01.001