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The IQmulus high volume fusion and analysis platform for Geospatial Point Clouds, featuring a marine bathymetry use case

机译:适用于地理空间点云的IQmulus高容量融合和分析平台,具有海洋测深用例

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New data acquisition techniques are emerging and are providing a fast and efficient means for multidimensional spatial data collection. Single and multi-beam echo-sounders, airborne LIDAR, SAR satellites and mobile mapping systems are increasingly used for the digital reconstruction of the environment. All these systems provide point clouds, often enriched with other sensor data providing extremely high volumes of raw data. With these acquisition approaches, a great deal of data is collected, but it often requires harmonisation and integration before reaching its maximum use potential. Use cases include supporting numerical modelling on land such as simulations of flooding and drought, and for use in modelling waves and flow in seas and oceans. The IQmulus high volume fusion and analysis platform offers an architecture for processing such geospatial point clouds, through a set of pre-defined workflows, on a cloud infrastructure. Workflow elements include deconfliction of spatially overlapping data, spline interpolation to create high precision surfaces and the latest visualisation techniques for these datasets. Featured in the presentation is a workflow designed to process collections of surveys of water depth. Individual surveys vary both spatially and temporally and can overlap with many other similar surveys. Where measurements of water depth differ greatly between surveys a strategy needs to be employed to determine how to create an optimal bathymetric surface using all of the relevant, available data. As part of its SeaZone suite of data products, HR Wallingford employs the latest deconfliction techniques to produce such a ‘best’ surface. The workflow begins with a methodology for prioritising individual surveys, followed by spline interpolation of adjacent or overlapping datasets with a potentially parallel implementation which includes tiling and stitching to create the final completed surface. An example of how these datasets can support the immersive visualisation of civil engineering applications is shown through HR Wallingford's advanced Ship Simulation Centre.
机译:新的数据采集技术不断涌现,并为多维空间数据收集提供了一种快速有效的手段。单束和多束回声测深仪,机载LIDAR,SAR卫星和移动制图系统越来越多地用于环境的数字重建。所有这些系统都提供点云,通常会添加其他传感器数据,从而提供大量原始数据。通过这些获取方法,可以收集大量数据,但是在达到最大使用潜力之前,通常需要对其进行协调和集成。用例包括支持陆地上的数值建模,例如洪水和干旱模拟,以及用于对海浪和海流进行建模。 IQmulus高容量融合和分析平台提供了一种架构,该架构可通过一组预定义的工作流程在云基础架构上处理此类地理空间点云。工作流元素包括空间重叠数据的冲突,样条插值以创建高精度曲面以及这些数据集的最新可视化技术。演示中介绍的是一个工作流,旨在处理水深调查的集合。各个调查在空间和时间上都不同,并且可以与许多其他类似的调查重叠。如果两次调查之间水深的测量差异很大,则需要采用一种策略来确定如何使用所有相关的可用数据来创建最佳的测深表面。作为其SeaZone数据产品套件的一部分,HR Wallingford运用最新的去冲突技术来产生这种“最佳”表面。该工作流程始于一种方法,该方法用于确定各个测量的优先级,然后使用潜在的并行实现对相邻或重叠数据集进行样条插值,包括平铺和缝合以创建最终完成的表面。 HR Wallingford的高级船舶仿真中心展示了这些数据集如何支持土木工程应用的沉浸式可视化的示例。

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