{"title":"High-Definition Digital Elevation Model System Vision Paper","authors":"Andi Zang, Xin Chen, Goce Trajcevski","doi":"10.1145/3085504.3085533","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":431308,"journal":{"name":"Proceedings of the 29th International Conference on Scientific and Statistical Database Management","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 29th International Conference on Scientific and Statistical Database Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3085504.3085533","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
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.