Article
Version 1
Preserved in Portico This version is not peer-reviewed
A New Simplified DSM-to-DTM Algorithm – dsm-to-dtm-step
Version 1
: Received: 29 June 2018 / Approved: 2 July 2018 / Online: 2 July 2018 (16:42:05 CEST)
How to cite: Krauß, T. A New Simplified DSM-to-DTM Algorithm – dsm-to-dtm-step. Preprints 2018, 2018070017. https://doi.org/10.20944/preprints201807.0017.v1 Krauß, T. A New Simplified DSM-to-DTM Algorithm – dsm-to-dtm-step. Preprints 2018, 2018070017. https://doi.org/10.20944/preprints201807.0017.v1
Abstract
In this paper we will present a simplified approach for extracting the ground level – a digital terrain model (DTM) – from the surface provided in a digital surface model (DSM). Most existing algorithms try to find the ground values in a digital surface model. Our approach works the opposite direction by detecting probable above ground areas. The main advantage of our approach is the possibility to use it with incomplete DSMs containing much no data values which can be e.g. occlusions in the calculated DSM. A smoothing or filling of such original derived DSMs will destroy much information which is very useful for deriving a ground surface from the DSM. Since the presented approach needs steep edges to detect potential high objects it will fail on smoothed and filled DSMs. After presenting the algorithm it will be applied to a test area in Salzburg and compared to a terrain model freely available from the Austrian government.
Keywords
Digital Surface Model, Digital Terrain Model, Steep edge detection
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
