Image processing and machine learning applied to Earth Observation of the cryosphere

最近的一些研究已开始强调分析遥感图像以监测过去几十年来地球冰盖、冰帽和冰川发生的变化的潜力。一种常见的技术是使用光学图像绘制冰川锋面位置的变化，这表明在南极半岛等地有显著和广泛的退缩（Cook等人，2016），东南极洲的部分地区（Miles等人，2013年）以及格陵兰岛和北极冰川岛屿的部分地区（卡尔等人，2013年）。在南极洲西部，Christie等人（2016; 2018）使用Landsat和干涉合成孔径雷达相结合的方法，绘制了过去40年来接地线普遍后退的地图。这些研究只是为部署遥感数据和辅助信息的更广泛潜力打开了大门，其目标是将活动从人工绘制冰锋和接地线等特征升级到从机器学习继承的更自动化的技术。该项目的最终目标是制定一个框架，以便最好地利用现有的遥感和地球物理数据来绘制过去50年来极地冰盖周围的变化，并利用这些数据向我们提供有关过程的信息。该提案的目的是正式确定一个最好地利用现有遥感的框架（例如大地卫星、中分辨率成像光谱仪、高级星载热辐射仪、地球观测卫星）和地球物理数据（雷达探测），以捕捉极地冰块过去的变化。预计最初的重点将放在南极洲，但目标是制定一个适用于所有极地冰块的工作流程。本研究的方向有相当大的弹性，主要的研究问题如下：1。如何利用图像处理/分析和/或机器学习中开发的技术来优化绘制冰锋和接地线变化？2.在十年的时间尺度上，南极洲周围的冰锋变化是否适合作为地线变化的代理？3.冰锋的变化是否以冰流变化的光学可探测信号的形式被传送到内陆？4.这些技术恢复的冰川学观测结果的根本原因是什么？

A number of recent studies have begun to highlight the potential to analyse remote sensing imagery to monitor changes that have occurred to the Earth's ice sheets, ice caps and glaciers over the last few decades. A common technique has been to map changes to glacier frontal positions using optical imagery, which has shown significant and widespread retreat in locations such as the Antarctic Peninsula (Cook et al., 2016), parts of East Antarctica (Miles et al., 2013) and in parts of Greenland and glaciated Arctic islands (Carr et al., 2013). In West Antarctica, Christie et al. (2016; 2018) have mapped pervasive retreat of the grounding line over the last 40 years using a combination of Landsat and InSAR. These studies are just opening the door to the vastly wider potential for deploying remote sensing data and auxiliary information, where the ambition is to upscale activities from manual mapping of features such as ice fronts and grounding lines to more automated techniques inherited from machine learning. The ultimate goal of this project is to develop a framework for making best use of the existing remote sensing and geophysical data to map changes around the polar ice masses for the last 50 years, and to use these data to inform us on the processes responsible.The aim of the proposal is to formalise a framework for making best use of available remote sensing (e.g. Landsat, MODIS, ASTER, SPOT) and geophysical data (radar sounding) to capture past change to polar ice masses. It is anticipated that the initial focus will be on Antarctica, but the ambition is to develop a workflow applicable to all polar ice masses. There is considerable flexibility in the direction that the project may ultimately take.Key research questions are as follows:1. How can mapping ice front and grounding-line change be optimised taking advantage of techniques developed in image processing/analysis and/or machine learning?2. Over decadal timescales, are ice-front changes around Antarctica suitable proxies for grounding-line changes?3. Have changes at the ice front been transmitted inland in terms of optically-detectable signals of ice-flow change?4. What are the underlying causes of the glaciological observations recovered by these techniques?