The sudden onset of natural hazards such as a flash flood events can be devastating to a country or region, often affecting numerous communities, and humanitarian supply chains play a major role in enabling the timely recovery of economic and social activities. However, the uncertainty and suddenness of natural disasters such as flash floods, as well as the potential for aftershocks, require humanitarian supply chains to be resilient during the relief process. This research first adopts the Delphi and literature review methods to identify the key indicators in the humanitarian supply chain to form an evaluation index system. Then, taking the 2021 mega-flash flood event which affected four cities in the mountainous region under the jurisdiction of the Zhengzhou municipal government, the ANP method is used to calculate the weights of each indicator and combines the weighted results with the Multi-styling and stereotyping method under Pythagorean fuzzy (PFs-VIKOR) to make an evaluation of the resilience of the humanitarian supply chain in the relief process. The findings suggest that policy makers and decision makers should pay close attention to the coordination of the parties involved in the humanitarian supply chain and improve the level of resilience of the entire supply chain by enhancing the resource scheduling capacity and responsiveness. At the same time, the VIKOR evaluation of the 4 cities highlighted the humanitarian supply chain in Dengfeng City to be most effective in this event due to the close cooperation and positive response of all parties involved in the humanitarian supply chain. The findings of this research provide some useful suggestions and guidance to the various practitioners involved in the humanitarian supply chain. Furthermore, the evaluation of the performance of the four cities in this mega-flash flood event provides some helpful indication of the importance of the various emergency measures which can help to inform policy recommendations for the Zhengzhou municipal government.

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new dynamic programming for seamlessly stitching UAV images using optical flow. Our solution consists of two steps: Firstly, an image-matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is develop based on the concept of a stereo dual-channel energy accumulation using optical flow. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for adjacent image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching. Beyond that, our solution is also direction-independent, which has more adaptability and robustness for UAV images.