Geospatial analysis and modelling of riverine systems: realising the potential for satellite supplied data assimilation

该项目旨在分析创建供水资源管理人员和工程师使用的河流环境数字双胞胎的潜力和可行性。河流的高时空变化率使其难以进行现场监测，特别是在很长一段时间内。因此，卫星遥感已被确定为改进系统管理的关键工具。许多河流特征是从空间测量的，但在很大程度上，这些仅限于概念验证研究，缺乏将其转化为可操作和适用的产品的研究。因此，目前有一个研究领域可以找到，即创建一个以地球观测为动力的数字孪生虚拟环境，以解决现实世界的工程管理问题。首先，这将涉及检查哪些河流特征对不同类型的河流管理者或工程师最重要。这些将被组织成目前可以通过对地观测测量的那些，理论上可以测量但目前缺乏算法或方法实施的那些，以及需要现场传感器或更高分辨率图像的那些。前一类将被开发成一种新的仪表盘，类似于低级数字双胞胎，它将整理这些现有方法，并为管理人员提供最先进的决策依据。云计算软件，如谷歌地球引擎，将被依赖于提供框架，以组成这种同化所需的大数据，并提供使其可行使用的处理能力。使用此仪表板作为基础，需要执行三个工作流程。首先，对于非专业人士来说，类似的系统和API很难使用，与电脑游戏带来的巨大可视化飞跃相比，这些系统和API可能会被视为笨拙和缺乏吸引力。谷歌已经创建了一些概念性洪水地图，这些地图使用游戏引擎来真实地预测3D山谷中的洪水是什么样子，这个工作包旨在将其中一些改进纳入仪表盘。其次，提议开展一系列研究，比较已确定地区的卫星数据、航空遥感和无人机遥感的不同分辨率。将评估直接使用案例，以便勾勒出公司为增强其数字双胞胎而为专有卫星数据或现场方案付费的商业案例。这还将包括在示例情景中了解所需的结对率(虚拟环境需要多长时间更新一次)，以便更好地了解系统。最后，将汇编一个工作包，以调查可通过航空遥感或传感器系统测量目前无法通过卫星遥感测量的特征的可能方式。预计管理者的一些关键变量将不可用，因此数字孪生兄弟的使用将依赖于与模型无缝匹配的替代方法。因此，其中一些方法将在实地方案中用传感器或评估其可能的贡献和相互作用的较小规模的遥感方法进行测试。最终成果将是全面了解卫星对地观测的能力，以发挥其为河流管理和工程带来革命性变化的潜力。这将通过对数字双胞胎的建造和改进来促进，该数字双胞胎对所有这些现有数据和算法进行了整理。以及评估虚拟环境不同方面的可能改进和可行性的工作包，包括可视通信的能力、在特定情况下对更高质量数据的需求以及添加外部数据集的能力，以补偿卫星数据无法执行任务的情况

This project aims to analyse the potential and practicalities of creating a Digital Twin of a riverine environment for use by water managers and engineers. The high rate of spatial and temporal change in rivers make them difficult to monitor in-situ especially over an extended period of time. As a result, satellite remote sensing has been identified as a key tool to improve system management. Many riverine characteristics have been measured from space but for the most part, these are limited to proof-of-concept studies and a lack of research into conversion into actionable and applicable products. Thus, there is currently a research niche to be found in producing a Digital Twin virtual environment powered by Earth Observation to solve real world engineering management problems. First this would involve examining which river characteristics are most important for different types of river manager or engineer. These will be organised into those that can currently be measured through earth observation, those that theoretically can be measured but currently lack algorithms or methodology to be implemented and those that would require in-situ sensors or higher resolution imagery. The former category will be developed into a novel dashboard, analogous to a low-level Digital Twin, which will collate these existing methods and provide a state of the art for managers to rely on for decision making. Cloud computing software, such as Google Earth Engine, will be relied upon to provide the framework to compose the big data required for this assimilation and the processing power to make it feasible to use. Using this dashboard as a foundation there are three workflows to be undertaken. Firstly, similar systems and APIs are very difficult for a non-expert to use and when compared, to the vast visualisation leaps taken by computer games, these can be viewed as clunky and unappealing. Google has created some conceptual flood maps which use gaming engines to give a real idea of what predicted flood water would look like in a 3D valley and this work package will aim to incorporate some of these improvements into the dashboard. Secondly, it is proposed that a set of studies will be undertaken to compare different resolutions of satellite data, aerial and drone based remote sensing in the areas already identified. Direct use cases will be assessed, in order to outline an understanding of what the business cases are for companies to pay for proprietary satellite data or field programmes to enhance their Digital Twins. This would also include an appreciation of the required twinning rate (how often the virtual environment would need to be updated) during the example scenarios in order to better understand the system.Finally, a work package will be put together to investigate the possible ways in which characteristics, not currently measurable through satellite remote sensing, can be measured through aerial remote sensing or sensor systems. It is expected that some of the key variables for managers will not be available and therefore the use of a Digital Twin will be reliant on alternative methods fitting seamlessly into the model. Therefore, some of these methods will be tested in field programmes with sensors or smaller scale remote sensing methods assessing their possible contribution and interactions. The final product will be a comprehensive understanding of the ability for satellite Earth Observation to live up to its potential to revolutionise river management and engineering. This will be facilitated through the construction and improvements made to a Digital Twin collating all these available data and algorithms. Along with work packages assessing the possible improvements and viability of different aspects of this virtual environment including its ability to visually communicate, the need for higher quality data in specific cases and the ability to add external datasets to compensate where satellite data cannot carry out the task