Uncertainty models of reference surfaces derived from multi-platform geodetic observations

多平台大地观测得出的参考面不确定性模型

• 批准号: RGPIN-2014-06111
• 负责人: Fotopoulos, Georgia
• 金额: $ 1.46万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=651021
• 关键词: Uncertainty; models; reference; surfaces; derived

Practitioners of geodesy today, must be able to integrate geospatial/gravity data from numerous sources and platforms in order to provide a homogeneous description of the Earth's surface. The fundamental link between the gravity field and physically meaningful heights is well established. The importance of reference surfaces and the vertical has surged due to the paradigm shift in geodesy that occurred with the launch of three dedicated gravity field satellite missions providing unprecedented spatial and temporal coverage of the Earth's gravity field. This revolution has impacted applications in global science, engineering, surveying and mapping. In addition, the advancement of digital elevation model information and coverage from interferometric synthetic aperture radar, airborne laser scanning and terrestrial light detection and ranging systems has skyrocketed. Today, researchers in engineering and Earth Science are faced with the digital reality in which more technical data have been collected in the year 2012 than in all previous years, with the quantity of data expected to double every year. While the importance and difficulty of gathering and storing vast amounts of data must not be underestimated, if the data cannot be transformed into useable information, it is useless. The need for the development, implementation and validation of algorithms, tools, and techniques for uncertainty in geodetic data is immense. This research program is dedicated to training highly qualified personnel with a focus on the vertical component of "position" information which can take on many roles depending on the application and spatial extent of the problem. Understanding data quality and how to model and disseminate that information will become increasingly crucial as (i) applications demand higher geospatial accuracy and (ii) policy makers increasingly rely on qualified information (also demanded by the public). Another catalyst for this research includes the immense public safety concerns associated with environmental hazards (anthropogenic or natural in source) and the need to make informed decisions in near real-time. The provision of uncertainty estimates along with reference surfaces (ie., in the form of a map) will allow for improved interpretations that can save both resources and infrastructure. Canada is in fact at the forefront of many geoscience and geomatics related activities and a conscious effort to provide technically sound and high level uncertainty information for the vertical component is necessary in order to ensure that we remain on top.

今天的大地测量从业者必须能够整合来自众多来源和平台的地理空间/重力数据，以便提供地球表面的均匀描述。重力场和物理意义上的高度之间的基本联系已经很好地建立起来。由于发射了三颗专门的重力场卫星飞行任务，提供了前所未有的地球重力场时空覆盖范围，大地测量学范式发生了转变，因此参考面和垂线的重要性急剧上升。这场革命影响了全球科学、工程、测量和绘图方面的应用。此外，数字高程模型信息的进步以及干涉合成孔径雷达、机载激光扫描和地面光探测和测距系统的覆盖范围也突飞猛进。如今，工程和地球科学领域的研究人员面临着数字现实，2012年收集的技术数据比往年都多，预计数据量每年都会翻一番。虽然绝不能低估收集和存储大量数据的重要性和难度，但如果数据不能转化为可用信息，它就毫无用处。需要开发，实施和验证的算法，工具和技术的不确定性在大地测量数据是巨大的。该研究计划致力于培养高素质的人才，重点是“位置”信息的垂直分量，它可以根据问题的应用和空间范围承担许多角色。了解数据质量以及如何建模和传播这些信息将变得越来越重要，因为㈠应用程序要求更高的地理空间准确性，㈡决策者越来越依赖合格的信息（公众也需要）。这项研究的另一个催化剂包括与环境危害（人为或自然来源）相关的巨大公共安全问题，以及近实时做出明智决策的需求。提供不确定性估计沿着参考表面（即，以地图的形式）将有助于改进解释，从而节省资源和基础设施。事实上，加拿大在许多与地球科学和地理信息学有关的活动中处于领先地位，有必要有意识地努力提供技术上可靠和高度不确定的垂直部分信息，以确保我们保持领先地位。