High-definition digital elevation model system

Andi Zang, Xin Chen, Goce Trajcevski

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Digital Elevation Modeling (DEM) has been a widely used methodology in plethora of application domains, ranging from climate and geological studies, through temporal evolution of various migration patterns, to Geographic Information Systems (GIS) broadly. However, the existing DEM methodologies and systems cannot quite straightforwardly be extended to catch up with the demands due to recent developments in autonomous driving, vehicle localization, drone and dynamically evolving high-definition smart city modeling. The new challenges are the demand of higher precision, sparse(r) elevation data compression, real-time efficient retrieval and intra-sources data integration. Motivated by this, we take a first step towards developing a tile based, multi-layer high precision DEM system, which aims at seamlessly integrating (and aligning) DEM from different sources, and enables context-driven variations in zoom levels. In addition, to further improve the efficiency of the focused-retrieval of the data necessary to construct the DEM with the desired quality assurance, our vision targets the collaborative compression among heterogeneous data sources.

Original languageEnglish (US)
Title of host publicationSSDBM 2017
Subtitle of host publication29th International Conference on Scientific and Statistical Database Management
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450352826
StatePublished - Jun 27 2017
Event29th International Conference on Scientific and Statistical Database Management, SSDBM 2017 - Chicago, United States
Duration: Jun 27 2017Jun 29 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128636


Other29th International Conference on Scientific and Statistical Database Management, SSDBM 2017
Country/TerritoryUnited States


  • Digital elevation model
  • Heterogeneous data
  • Spatial data compression

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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