HALOS: Mapping Linear Features on Modern Geospatial Reference Frameworks

这项提议是设计和开发复杂的方法，在平铺地图和离散的全球格网上绘制海量线状要素。在纸质或数字地图上，地理特征(例如道路、河流)、区域轮廓(例如市政边界、湖岸)或移动对象轨迹(例如人、车辆)的表示通常使用折线几何来完成。这些几何图形通常包含大量的顶点。为了便于在小范围内处理、分析或映射这些几何图形，必须减少这些顶点的数量。可以应用传统的制图方法来辅助消除顶点。然而，这些方法是半自动的，涉及密集的人工监督，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海量地理空间数据的建模和测绘引入了新的框架。在线地图服务提供商，如谷歌地图或OpenStreetMap，以标准化的瓦片格式提供内容，以满足在Web上高速传播海量数据的需求，而数字地球则采用离散全球网格系统(DGGS)，通过提供可供分析的信息网格来理解地球模型。这些参考框架(即瓷砖地图和DGGS)的快速使用促使开发新的方法来高效、一致和合规地绘制表示地理特征或轨迹的海量折线几何图形。这项研究计划旨在通过建立在以前获得的知识的基础上，为领域、社会、经济和环境带来多重好处来满足这一需求。具体地说，这项研究渴望引入新的方法来解决线条简化这一基本问题(又名：地图概化或数据简化)在地理空间数据处理中。这些方法将在现代地理空间参考框架上提供海量线性地理空间要素的复杂建模和可视化。谷歌地图、OpenStreetMap或加拿大自然资源公司等行业和政府地图服务提供商将能够以更快、更准确的模式生成海量地图产品。普通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要素，对自然资源和工程的不同领域的研究和实践产生宝贵影响。HQP在这一新兴领域的教育对于培养未来的领导者和保持加拿大在地球信息学领域的领先地位具有重要的战略意义。

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.