High-Definition Digital Elevation Model System Vision Paper

Andi Zang, Xin Chen, Goce Trajcevski
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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.
高清数字高程模型系统远景论文
数字高程建模(DEM)已被广泛应用于众多应用领域,从气候和地质研究,到各种迁移模式的时间演变,再到广泛的地理信息系统(GIS)。然而,由于自动驾驶、车辆定位、无人机和动态发展的高清智慧城市建模的最新发展,现有的DEM方法和系统无法直接扩展以满足需求。新的挑战是对高精度、稀疏高程数据压缩、实时高效检索和源内数据集成的需求。在此激励下,我们朝着开发基于tile的多层高精度DEM系统迈出了第一步,该系统旨在无缝集成(和对齐)来自不同来源的DEM,并实现缩放级别的上下文驱动变化。此外,为了进一步提高构建DEM所需数据的集中检索效率,我们的愿景是异构数据源之间的协同压缩。
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