DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS

Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much...

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Main Authors: E. Fissore, F. Pirotti
Format: Article
Language:English
Published: Copernicus Publications 2019-06-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.pdf
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author E. Fissore
E. Fissore
F. Pirotti
F. Pirotti
author_facet E. Fissore
E. Fissore
F. Pirotti
F. Pirotti
author_sort E. Fissore
collection DOAJ
description Using multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much they can contribute to improve a CityGML model. The minimal information required to represents a 3 dimensional space in an urban environment is the combination of a DTM, the footprints of buildings and their heights; in this way a representation of urban environment to define LOD1 CityGML is guaranteed. In this paper we discuss the following research questions: can DTMs and DSMs provide significant information for modelling buildings at higher LODs? What characteristics can be extracted depending on the ground sampling distance (GSD) of the DTM/DSM? Results show that the used DTM/DSM at 1 m GSD provides potential significant information for higher LODs and that the conversion of the unstructured point cloud to a regular grid helps in defining single buildings using connected component analysis. Regularization of the original point cloud does loose accuracy of the source information due to smoothing or interpolation, but has the advantage of providing a predictable distance between points, thus allowing to join points belonging to the same building and provide initial primitives for further modelling.
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spelling doaj.art-ef072e8ce64444ac862779a0a6e60e6f2022-12-22T01:13:11ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-06-01XLII-2-W131539154410.5194/isprs-archives-XLII-2-W13-1539-2019DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONSE. Fissore0E. Fissore1F. Pirotti2F. Pirotti3CIRGEO - Interdepartmental Research Center of Geomatics, University of Padova, Viale dell’Università 16, Legnaro (PD), ItalyTESAF Department, University of Padova, Viale dell’Università 16, Legnaro (PD), ItalyCIRGEO - Interdepartmental Research Center of Geomatics, University of Padova, Viale dell’Università 16, Legnaro (PD), ItalyTESAF Department, University of Padova, Viale dell’Università 16, Legnaro (PD), ItalyUsing multiple sources of 3D information over buildings to go from building footprints (LOD0) to higher LODs in CityGML models is a widely investigated topic. In this investigation we propose to use a very common 2.5D product, i.e. digital terrain and surface models (DTMs and DSMs), to test how much they can contribute to improve a CityGML model. The minimal information required to represents a 3 dimensional space in an urban environment is the combination of a DTM, the footprints of buildings and their heights; in this way a representation of urban environment to define LOD1 CityGML is guaranteed. In this paper we discuss the following research questions: can DTMs and DSMs provide significant information for modelling buildings at higher LODs? What characteristics can be extracted depending on the ground sampling distance (GSD) of the DTM/DSM? Results show that the used DTM/DSM at 1 m GSD provides potential significant information for higher LODs and that the conversion of the unstructured point cloud to a regular grid helps in defining single buildings using connected component analysis. Regularization of the original point cloud does loose accuracy of the source information due to smoothing or interpolation, but has the advantage of providing a predictable distance between points, thus allowing to join points belonging to the same building and provide initial primitives for further modelling.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.pdf
spellingShingle E. Fissore
E. Fissore
F. Pirotti
F. Pirotti
DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
title_full DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
title_fullStr DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
title_full_unstemmed DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
title_short DSM AND DTM FOR EXTRACTING 3D BUILDING MODELS: ADVANTAGES AND LIMITATIONS
title_sort dsm and dtm for extracting 3d building models advantages and limitations
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1539/2019/isprs-archives-XLII-2-W13-1539-2019.pdf
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