Sensors 2016, 16(8), 1298; https://doi.org/10.3390/s16081298
A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques
1
Department of Civil Engineering, Florida International University, Miami, FL 33174, USA
2
Department of Earth and Environment, Florida International University, Miami, FL 33199, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Hans Tømmervik
Received: 12 May 2016 / Revised: 1 August 2016 / Accepted: 8 August 2016 / Published: 16 August 2016
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
Abstract
Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). View Full-Text
Graphical abstract
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MDPI and ACS Style
Gholizadeh, M.H.; Melesse, A.M.; Reddi, L. A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. Sensors 2016, 16, 1298.
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