Developing resilience and strengthening capacity of urban disaster risk management using remote sensing.

利用遥感、公民参与和机器学习相结合的方法，评估城市在灾害风险时期的复原力。随着城市的扩张以容纳更多的人口，它们往往在没有适当规划的情况下这样做，特别是在低收入和中等收入国家。然而，这导致了空间不平等和更大的危险风险暴露。我的研究将以埃塞俄比亚为案例，并将寻求了解将人们置于危险之中的气候危害以及这些危害在城市中的位置，谁面临的风险最大，以及通过利益相关者和公民参与建立复原力是什么样子。创建健康、宜居、更具弹性的城市，同时将居住在其中的人包括在内，是这项研究的一个关键特征。

Assessing urban resilience in times of disaster risk, using a combination of remote sensing, citizen engagement and machine learning to do this. As cities expand to incorporate more people, they often do so without proper planning, particularly in low to middle income countries. However, this leads to spatial inequality and greater of exposure to risk of hazards. My research will use Ethiopia as a case study and will seek to understand the climate hazards that put people at risk and where these are located within the city, who is most at risk and what building resilience looks like through stakeholder and citizen engagement. Creating healthy, liveable and more resilient cities whilst including the people that live in them is a key feature of this research.