TY - BOOK ID - 146317205 TI - Improving Flood Detection and Monitoring through Remote Sensing AU - Refice, Alberto AU - Capolongo, Domenico AU - Chini, Marco AU - D'Addabbo, Annarita PY - 2022 PB - Basel MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Technology: general issues KW - History of engineering & technology KW - Environmental science, engineering & technology KW - mobile mapping system KW - RRI model KW - high-water marks KW - inundation KW - Northern Kyushu floods KW - point clouds KW - flood mapping KW - temporary flooded vegetation (TFV) KW - Sentinel-1 KW - time series data KW - Synthetic Aperture Radar (SAR) KW - sentinel-1 KW - SAR KW - flood KW - image classification KW - clustering KW - monsoon KW - Philippines KW - LiDAR KW - geometric parameters KW - levee stability KW - overtopping KW - Pearl River Delta KW - CYGNSS KW - flood detection KW - Sistan and Baluchestan KW - GNSS-R KW - flood monitoring KW - ALOS 2 KW - multi-sensor integration KW - multi-temporal inundation analysis KW - Zambesi-Shire river basin KW - image processing KW - hydrology KW - synthetic aperture radar UR - https://www.unicat.be/uniCat?func=search&query=sysid:146317205 AB - 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. ER -