Better prediction and monitoring of flood events are key factors contributing to the reduction
of their impact on local communities and infrastructure assets. Flood management involves …

The launch of large language models (LLMs) like ChatGPT in late 2022 and the anticipated
arrival of future GPT-x iterations have marked the beginning of the generative artificial …

This study proposes a vision-based method for flood depth estimation using flooded-vehicle
images with a ground-level view. The proposed method is comprised of three main …

Effective monitoring and forecasting of urban flooding are crucial for climate change
adaptation and resilience around the world. We proposed a novel and automatic system for …

It is important to have a real-time flash flood detection system to inform the public for them to
take appropriate action. The current method of authorities using mainstream media such as …

It is important that a sustainable community better prepare for and design mitigation
processes for major flooding events, particularly as the climate is non-stationary. In recent …

Collection of information from crowdsourced and traditional sensing techniques during a
disaster offers opportunities to exploit this new data source to enhance situational …

Abstract Information on the depth of floodwater is crucial for rapid mapping of areas affected
by floods. However, previous approaches for estimating floodwater depth, including field …

This work proposes a novel deep learning method to predict depth of floodwater on streets
based on side-view images of vehicles. Finding flood levels on roadways is useful for …

Flood damage accurate assessment, such as flood depth, is very helpful for disaster relief.
However, most of existing methods have some limitations, either the expensive data …