AI Article Synopsis

  • Floods are frequent and devastating natural hazards, with their occurrences increasing due to climate change, making flood management essential.
  • Advancements in flood monitoring have transitioned from ground-based sensors to sophisticated airborne and remote sensing technologies, enhancing disaster prevention efforts.
  • The integration of flood sensors with artificial intelligence is emerging, significantly improving local flood management and response efficiency.

Article Abstract

Floods are the most destructive, widespread, and frequent natural hazards. The extent of flood events is accelerating in the context of climate change, where flood management and disaster mitigation remain important long-term issues. Different studies have been utilizing data and images from various types of sensors for mapping, assessment, forecasting, early warning, rescue, and other disaster prevention and mitigation activities before, during, and after floods, including flash floods, coastal floods, and urban floods. These monitoring processes evolved from early ground-based observations relying on in situ sensors to high-precision, high-resolution, and high-coverage monitoring by airborne and remote sensing sensors. In this study, we have analyzed the different kinds of sensors from the literature review, case studies, and other methods to explore the development history of flood sensors and the driving role of floods in different countries. It is found that there is a trend towards the integration of flood sensors with artificial intelligence, and their state-of-the-art determines the effectiveness of local flood management to a large extent. This study helps to improve the efficiency of flood monitoring advancement and flood responses as it explores the different types of sensors and their effectiveness.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11548130PMC
http://dx.doi.org/10.3390/s24217090DOI Listing

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