HALOS: Mapping Linear Features on Modern Geospatial Reference Frameworks

这项建议是设计和开发复杂的方法，在瓦片地图和离散的全球网格上映射大量的线性特征。地理特征的表示（例如，道路、河流），区域的轮廓（例如，城市边界、湖岸）或移动对象轨迹（例如，人、车辆）在纸上或数字地图上的绘制通常使用几何图形来完成。这些几何体通常包括大量的顶点。为了便于在小尺度上处理、分析或映射这些几何图形，必须减少这些顶点的数量。传统的制图方法可以用来帮助消除顶点。然而，这些方法是半自动化的，并且涉及强烈的人工监督，在大规模生产中的适用性有限。地理空间网络和数字地球的最新发展为大量地理空间数据的建模和制图引入了新的框架。在线地图服务提供商，如Google Maps或OpenStreetMap，以标准化的瓦片格式提供内容，以满足通过网络高速传播大量数据的需求，而数字地球则采用离散全球网格系统（DGGS），通过提供分析就绪的信息网格来理解地球模型。这些参考框架的使用迅速增加（即，瓦片地图（tile maps）和DGGS）已经敦促开发新的方法来高效地、一致地和顺应地映射表示地理特征或轨迹的大规模非对称几何形状。这项研究计划旨在通过建立在以前获得的知识，对该领域，社会，经济和环境的多重利益，以满足这一需求。具体来说，这项研究旨在引入新的方法来解决线简化的基本问题（又名）。制图综合或数据简化）。这些方法将在现代地理空间参考框架上为大规模线性地理空间特征提供复杂的建模和可视化。行业和政府地图服务提供商，如谷歌地图、OpenStreetMap或加拿大自然资源部，将能够以更快、更准确的模式生成大量地图产品。一般终端用户和数据科学家将能够以更准确，可互操作和一致的方式可视化，处理和分析地理空间特征，对自然资源和工程领域的研究和实践产生宝贵的影响。HQP在这一新兴领域的教育在培养明天的领导者和保持加拿大在地理信息学方面的领先地位方面具有战略重要性。

This proposal is to design and develop sophisticated methods for mapping massive linear features on tile maps and discrete global grids. The representation of geographic features (e.g., roads, rivers), outlines of areas (e.g., municipal boundaries, lake banks) or moving objects trajectories (e.g., of humans, vehicles) on paper or digital maps is commonly accomplished using polyline geometries. These geometries usually comprise a massive number of vertices. To facilitate the processing, analysis, or mapping of these geometries at a small scale, the number of these vertices must be reduced. Traditional cartographic methods can be applied to assist the elimination of vertices. However, these methods are semi-automated and involve an intense human supervision with limited applicability in massive production. Recent developments in Geospatial Web and Digital Earth have introduced new frameworks to modelling and mapping voluminous geospatial data. Online map service providers, such as Google Maps or OpenStreetMap, deliver their content in a standardized tile format to meet the demand for high speed dissemination of voluminous data over the web, while Digital Earth has adopted the discrete global grid systems (DGGS) to understand the planet model by offering an analysis-ready-information-grid. The rapidly growing use of these reference frameworks (i.e., tile maps and DGGS) has urged the development of new approaches to an efficient, consistent, and compliant mapping of massive polyline geometries representing geographic features or trajectories. This research plan aims to address this need by building on previously acquired knowledge with multiple benefits to the field, society, the economy, and the environment. Specifically, this research aspires to introduce new approaches to the fundamental problem of line simplification (a.k.a. cartographic generalization or data reduction) in geospatial data handling. These approaches will offer a sophisticated modelling and visualization of massive linear geospatial features on modern geospatial reference frameworks. Industry and government map service providers like Google Maps, OpenStreetMap or Natural Resources Canada will be able to generate massive map products in a faster and more accurate mode. General end-users and data scientists will be able to visualize, process, and analyze geospatial features in a more accurate, interoperable, and consistent manner with a valuable impact in research and practice to diverse fields in Natural Resources and Engineering. The education of HQP in this emerging area is strategically important in preparing the leaders of tomorrow and in retaining Canada's leading position in Geomatics.