Detecting Population and Built Environment Change from Space and their Impacts on Buried Utility Assets

从太空检测人口和建筑环境变化及其对埋藏公用事业资产的影响

基本信息

批准号：
2752728
负责人：
金额：
--
依托单位：
University of Liverpool
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2752728
关键词：
Detecting Population Built Environment Change

项目摘要

Advances in Satellite and Earth observation technology are creating new ways in which we can study the interrelationships between populations and those places within which they live. This is creating great opportunities for the study of human dynamics through the lens of changes to the built environment; and provides a new set of reference points for those companies focused on delivery of services at this intersection. MGISS are based within Liverpool City Region and have a vision to be a global leader in the use of Geospatial technology, location intelligence and advanced analytics to improve the long-term resilience of critical infrastructure such as buried utilities (water, gas, electricity, telco) and also major transportation networks. The core of this project will involve the application of machine learning and AI (e.g. Classification / spectral mixture models) to satellite data to extract information on changes in human activity, and will additionally benefit from the close coupling of insight from MGISS, available asset owner data, environmental data and other ancillary sources such as planning application and approvals. Substantively this project will likely explore various observable changes such as infrastructure development (planned and in progress) and potential for identification of past, imminent, and future potential supply interruption impacts.

卫星和地球观测技术的进步正在创造新的方法，使我们能够研究人口及其居住地之间的相互关系。这为通过建筑环境变化的视角来研究人类动力学创造了绝佳的机会；并为那些专注于在这个交叉点提供服务的公司提供了一组新的参考点。 MGISS 总部位于利物浦市地区，愿景是成为利用地理空间技术、位置智能和高级分析的全球领导者，以提高埋地公用设施（水、煤气、电力、电信等）等关键基础设施的长期弹性。）以及主要交通网络。该项目的核心将涉及将机器学习和人工智能（例如分类/光谱混合模型）应用于卫星数据，以提取有关人类活动变化的信息，并将额外受益于可用资产所有者 MGISS 的洞察力的紧密结合数据、环境数据和其他辅助来源，例如规划申请和批准。从本质上讲，该项目可能会探索各种可观察到的变化，例如基础设施开发（计划中和正在进行中）以及识别过去、即将发生和未来潜在供应中断影响的潜力。