Reprint
Remote Sensing of the Aquatic Environments
Edited by
August 2021
292 pages
- ISBN978-3-0365-1666-0 (Hardback)
- ISBN978-3-0365-1665-3 (PDF)
This book is a reprint of the Special Issue Remote Sensing of the Aquatic Environments that was published in
Engineering
Environmental & Earth Sciences
Summary
The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
polymer optical fibers; ammonia detection; optical fiber coating; aquaculture; French Alps; optical remote sensing; multitemporal; linear spectral unmixing; NDVI; drought; Rana temporaria; ecohydrology; mountain temporary pools; Lake Tana; water hyacinth; waterbody temperature; turbidity; lake level; Planetscope; remote sensing; sensors; ocean color; sediment; turbid water; chlorophyll; geostationary satellite; aquaculture ponds; extraction; inland lake; self-attention; Ulva; Sentinel-2; satellite; remote sensing; algal bloom; coral reefs; Pacific lagoons; HAB; multi-source remote sensing; MODIS; Landsat; sentinel; Chaohu Lake; ecological status class of lakes; European Union Water Framework Directive (2000/60/EC); water quality parameters; water level; Sentinel-3; Cryosat-2; shallow lakes; synergy; altimetry data; optical data; CDOM absorbance; spectroscopic indices; DOC; Arctic; shelf seas; estuarial and coastal areas; drone applications; surface water; groundwater; photogrammetry; optical sensing; thermal infrared; deep learning; convolutional neural network; chlorophyll-a; satellite; hydrodynamic model; empirical models; multiple regression; Paldang Reservoir; water quality parameters; SAR; Doppler Centroid Anomaly; inland waters; physical limnology; hydrodynamics