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In the context of climate change and urbanization, increasing flood disasters leads to severe losses and impacts on urban inhabitants. In order to enhance urban capacity to cope with floods and reduce losses, the comprehensive emergency-response capacity to flood disaster (CERCF) was studied in Zhengzhou City, which is seriously affected by floods. Firstly, the evaluation index system of flood emergency capacity was constructed from three aspects, including pre-disaster prevention capacity, during-disaster disposal capacity and post-disaster recovery capacity. Secondly, the weight of each index was calculated by the combination of the entropy weight method and the coefficient of variation method, and the evaluation model was established by the comprehensive index method. Thirdly, the CERCF of Zhengzhou City was classified into three grades by the Jenks natural-breakpoint classification method. Finally, the contribution model was used to reveal the contribution factors of flood emergency capacity in Zhengzhou city. The following beneficial conclusions were drawn: (1) The overall CERCF of Zhengzhou City was on a low level. The proportions of the study area at low, medium and high levels were 58.33%, 33.33% and 8.34%, respectively. Spatially, the CERCF was high in central regions and low in in the west and east parts of Zhengzhou City. (2) It was found that PDPC and PDRC made the greatest contribution, while DDDC has a relatively low contribution degree.

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<p style='text-indent:20px;'>With the increasing complexity of modern air warfare, an efficient and robust mission planning, which mainly includes task assignment and path planning, becomes the key issue to improve the combat efficiency. This paper reviews recent progress in UAV mission planning. First, basic concepts of UAVs and their mission planning problem are given. And several representative existing mission planning systems are briefly introduced. The constraints and objectives in the task assignment model are reviewed, and the pros and cons of algorithms commonly used are then summarized. After that, the algorithms for path planning are reviewed. Finally, we point out current problems and future research directions. The paper provides a comprehensive review of the field and enables a quick start for those who aim to do related research.</p>