Reprint

Improving Flood Detection and Monitoring through Remote Sensing

Edited by
July 2022
158 pages
  • ISBN978-3-0365-3875-4 (Hardback)
  • ISBN978-3-0365-3876-1 (PDF)

This is a Reprint of the Special Issue Improving Flood Detection and Monitoring through Remote Sensing that was published in

Biology & Life Sciences
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Public Health & Healthcare
Summary

As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions.

Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms.

In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events.

The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data.

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
mobile mapping system; RRI model; high-water marks; inundation; Northern Kyushu floods; point clouds; flood mapping; temporary flooded vegetation (TFV); Sentinel-1; time series data; Synthetic Aperture Radar (SAR); sentinel-1; SAR; flood; image classification; clustering; monsoon; Philippines; LiDAR; geometric parameters; levee stability; overtopping; Pearl River Delta; CYGNSS; flood detection; Sistan and Baluchestan; flood mapping; GNSS-R; flood monitoring; ALOS 2; Sentinel-1; multi-sensor integration; multi-temporal inundation analysis; Zambesi-Shire river basin; image processing; hydrology; synthetic aperture radar; n/a

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