Improving Flood Detection and Monitoring through Remote Sensing

• Andere auteurs: Refice, Alberto (Redacteur), Capolongo, Domenico (Redacteur), Chini, Marco (Redacteur), D'Addabbo, Annarita (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Onderwerpen: Technology: general issues; History of engineering & technology; Environmental science, engineering & technology; 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; GNSS-R; flood monitoring; ALOS 2; multi-sensor integration; multi-temporal inundation analysis; Zambesi-Shire river basin; image processing; hydrology; synthetic aperture radar; n/a
• Online toegang: DOAB: download the publication; DOAB: description of the publication

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 temp...