Software for quantifying shallow landslide hazards to transportation infrastructure under changing climate and forest management

山体滑坡和泥石流可能会破坏高地地区的关键基础设施，管理和减轻对这些基础设施构成的风险是基础设施所有者面临的一项关键挑战。此外，滑坡和泥石流不尊重所有权边界，第三方土地所有者可能会发现自己对源自其土地的大规模流动负有责任，而基础设施所有者则必须管理其所持土地以外的危险。此外，运输业主和维修代理必须能够计划在正确的时间和地点交付工程。规划有效的支出面临一系列挑战，包括气候和土地利用的变化如何影响未来滑坡易感性的持续不确定性，以及有效利用高分辨率数字数据集(例如激光雷达调查)模拟滑坡情况的能力有限。该项目将开发软件，在区域尺度上制作包含最高分辨率地形和土地利用数据的滑坡危险地图。它建立在爱丁堡大学和英国地质调查局之前的危险研究基础上，并被构建为在多核、超级计算环境中工作--该软件可以处理非常高分辨率的激光雷达调查形式的大数据，提供亚米级的斜坡信息：质量运动和驱动它们运行的水文学的规模。此外，该软件将设计成提供情景模拟。特别是，滑坡灾害变化的主要驱动因素之一是改变运输走廊沿线不同植被格局的根部凝聚力。该项目将吸收森林研究公司的林业数据，以便我们能够调查将山体滑坡风险降至最低的种植和收获时间表，并确定运输走廊受到山体滑坡威胁最大的时间。该项目的最终目标是提供一个软件工具，供土地所有者、基础设施所有者和维护代理使用，以更好地规划缓解和支出战略。

Critical infrastructure in upland landscapes can be damaged by landslides and debris flows, and managing and mitigating the risks posed to this infrastructure is a key challenge for infrastructure owners. In addition, landslides and debris flows do not respect ownership boundaries, and third party landowners can find themselves liable for mass movements originating from their land, whereas infrastructure owners have to manage hazards from beyond their holdings. In addition, transport owners and maintaining agents must be able to plan on works to be delivered at the right time and in the right place. Planning efficient spending has a number of challenges, including persistent uncertainty in how changes in climate and land use affect future landslide susceptibility and limited capability to make effective use of high resolution digital datasets (e.g. LiDAR surveys) to model landslide scenarios.This project will develop software for producing landslide hazard maps at regional scales incorporating the highest resolution topographic and land use data. It builds on previous hazard research at the University of Edinburgh and the British Geological Survey, and is built to work in a mulitcore, supercomputing environment--the software can handle big data in the form of very high resolution LiDAR surveys that provide information on slopes at the sub-metre scale: the scale at which mass movements and the hydrology that drive them operate. In addition, the software will be designed to provide scenario modelling. In particular, one of the major drivers in changes in landslide hazard is changing root cohesion from different vegetation patterns along transport corridors. The project will assimilate forestry data from Forest Research so that we can investigate the planting and harvesting schedule that minimised landslide risk, and also determine the time at which transport corridors are most threatened by landsliding. The ultimate objective of the project is to provide a software tool that land owners, infrastructure owners and maintaining agents can use to better plan mitigation and spending strategies.