Multi-scale multi-domain geospatial data modelling

多尺度多域地理空间数据建模

• 批准号: 2281589
• 金额: --
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2281589
• 关键词: Multi; scale; multi; domain; geospatial

This PhD is funded by the Engineering and Physical Sciences Research Council of Great Britain under EPSRC grant number EP/S023577/1, and Ordnance Survey of Great Britain. This topic aims to link different spatial domains of interest such as transport, water, environment, and society and thereby enable cross-domain and cross-scale analytics and simulation. The aim is to develop a geospatial data infrastructure and data model for a unified incident response system. In line with the United Nations Sustainable Development Goal 11 to make cities inclusive, safe, resilient, and sustainable, cities and the environment need to be equipped with the ability to better respond to and be prepared for unforeseen events. Using Internet of Things (IoT) and sensors deployed in a smart environment, this PhD will explore how to transform raw data into intelligence, support stakeholders in real-time response and improve resilience. A use case is developed including incident types from different domains, such as flooding, traffic incidents or utility failures that can cause a disruption across different systems, trigger an alarm, and require actions along the response chain involving different stakeholders. Therefore, this PhD aims to use cloud computing capabilities and spatial big data analytics to process the vast amounts of geospatial data collected by sensors, CCTV data feeds and social media transmitted as data feeds. By integrating knowledge from different stakeholders into a common ontology, this PhD will contribute to a better understanding of the requirements for future data models for incident response.

该博士学位由英国工程和物理科学研究理事会资助，EPSRC资助号为EP/S 023577/1，英国Orphanic Survey。本主题旨在将不同的感兴趣的空间领域（如交通，水，环境和社会）联系起来，从而实现跨领域和跨尺度的分析和模拟。目的是为统一的事件应对系统开发地理空间数据基础设施和数据模型。根据联合国可持续发展目标11，使城市具有包容性、安全性、韧性和可持续性，城市和环境需要具备更好地应对和准备应对意外事件的能力。利用物联网（IoT）和部署在智能环境中的传感器，该博士将探索如何将原始数据转化为智能，支持利益相关者实时响应并提高弹性。开发了一个用例，包括来自不同域的事件类型，例如洪水、交通事件或公用事业故障，这些事件可能导致不同系统之间的中断，触发警报，并需要沿着涉及不同利益相关者的响应链采取行动。 因此，该博士旨在使用云计算能力和空间大数据分析来处理传感器，CCTV数据源和社交媒体作为数据源传输的大量地理空间数据。通过将来自不同利益相关者的知识整合到一个共同的本体中，这个博士学位将有助于更好地理解未来事件响应数据模型的要求。