Matthew Moy de Vitry

TL;DR: The findings show that data-driven UWM allows us to develop and apply novel methods, to optimize the efficiency of the current network-based approach, and to extend functionality of today's systems.

TL;DR: In this paper, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions.

TL;DR: Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments as discussed by the authors. But it is still a relatively new area.

TL;DR: In this article, the authors investigated the potential of using surveillance camera footage to measure surface flow velocity thanks to an LSPIV-based method called Surface Structure Image Velocimetry (SSIV) seven realscale experiments conducted in a specialized flood training facility were used to test the SSIV method under varied and challenging conditions.

TL;DR: This work proposes a new approach that exploits existing surveillance camera systems to provide qualitative flood level trend information at scale and uses a deep convolutional neural network to detect floodwater in surveillance footage and a novel qualitative flood index as a proxy for water level fluctuations visible from a surveillance camera's viewpoint.