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Adjusting the Regular Network of Squares Resolution to the Digital Terrain Model Surface Shape

Bibliographic Data

ID22032096
AuthorsDariusz Gościewski (0000-0002-6663-3412, University of Warmia and Mazury in Olsztyn, corresponding author), Małgorzata Gerus-Gościewska (0000-0003-4725-7578, University of Warmia and Mazury in Olsztyn)
Year2020
Volume9
Issue12
Pages761
Publication date2020-12-20
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi9120761
OpenAlexW3114188252
LanguageEN
References cited39

A regular network of squares is formed by points uniformly distributed (mostly in the square corners) over the surface that is represented by the network. Each point (node) of the network has specified coordinates (X and Y) with a fixed constant distance between them. The third coordinate in a node (H) is determined by the application of interpolation based on the points distributed (usually dispersed as a point cloud e.g., from LiDAR) over the surface of the area surrounding the node. The regular network of squares formed in this manner allows the representation of a digital terrain model (DTM) to be performed in spatial information systems (SIP, GIS). The main problem that arises during the construction of such a network is the proper determination of its resolution (the base distance between the coordinates X and Y) depending on the topography. This article presents a method of the regular network of squares resolution determination depending on the morphological shape of the terrain surface. Following the application of the procedures being described, a differently shaped terrain is assigned various network densities. This enables the minimisation of inaccuracies of the surface model being formed. Consequently, a regular network of squares is formed with different base square sizes, which is adjusted with its resolution to the morphology of the surface it describes. Such operations allow the terrain model accuracy to be maintained over the entire area while reducing the number of points stored in the DTM database to the minimum

Acoustics · Algorithm · Cartography · Computer vision · Digital elevation model · Geography · Geometry · Least-squares function approximation · Mathematical analysis · Physics · Point cloud · Remote sensing · Terrain · Triangulated irregular network · 3D Modeling in Geospatial Applications · 3D Surveying and Cultural Heritage · Computer Science · Mathematics · Remote Sensing and LiDAR Applications

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