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Special Issue "Remote Sensing of Water Quality"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 31 December 2017

Special Issue Editors

Guest Editor
Dr. Wesley J. Moses

U.S. Naval Research Laboratory, 4555 Overlook Ave SW, Washington, DC 20375, USA
Website | E-Mail
Interests: optical properties of water (open-ocean, coastal, and inland waters); sensor noise analysis; atmospheric correction; remote sensing of natural resources
Guest Editor
Dr. W. David Miller

U.S. Naval Research Laboratory, 4555 Overlook Ave SW, Washington, DC 20375, USA
E-Mail
Interests: airborne remote sensing; environmental forcing of phytoplankton dynamics; hyperspectral imaging; bio-optical modeling of optically complex waters

Special Issue Information

Dear Colleagues,

Recent advances in sensor technology and algorithm development enable the use of remote sensing to quantitatively study complex biophysical and biogeochemical processes in open-ocean, estuarine, coastal, and inland waters. However, realizing the operational potential of remote sensing for water quality monitoring has a number of challenges. A special issue on “Remote Sensing of Water Quality” has been dedicated in the journal Remote Sensing to address the current status, challenges, and future research priorities for remote sensing of water quality.

We are therefore inviting your new contribution in this exciting field to our Remote Sensing special issue on “Remote Sensing of Water Quality”.

Dr. Wesley J. Moses
Dr. W. David Miller
Guest Editors

Keywords

  • water quality
  • remote sensing
  • ocean color
  • bio-optical modeling
  • atmospheric correction
  • spatial variability
  • optical complexity
  • end-user engagement

Published Papers (1 paper)

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Research

Open AccessArticle Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China
Remote Sens. 2017, 9(6), 624; doi:10.3390/rs9060624
Received: 8 May 2017 / Revised: 26 May 2017 / Accepted: 15 June 2017 / Published: 17 June 2017
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Abstract
In situ measured values of particulate organic carbon (POC) in Taihu Lake and remote sensing reflectance observed by three satellite courses from 2014 to 2015 were used to develop an near infrared-red (NIR-Red) empirical algorithm of POC for the Moderate Resolution Imaging Spectroradiometer
[...] Read more.
In situ measured values of particulate organic carbon (POC) in Taihu Lake and remote sensing reflectance observed by three satellite courses from 2014 to 2015 were used to develop an near infrared-red (NIR-Red) empirical algorithm of POC for the Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) satellite image. The performance of the POC algorithm is highly consistent with the in situ measured POC, with root mean square error percentage (RMSPs) of 38.9% and 31.5% for two independent validations, respectively. The MODIS-derived POC also shows an acceptable result, with RMSPs of 53.6% and 61.0% for two periods of match-up data. POC from 2005 to 2007 is much higher than it is from 2002 to 2004 and 2008 to 2013, due to a large area of algal bloom. Riverine flux is an important source of POC in Taihu Lake, especially in the lake’s bank and bays. The influence of a terrigenous source of POC can reach the center lake during periods of heavy precipitation. Sediment resuspension is also a source of POC in the lake due to the area’s high dynamic ratio (25.4) and wind speed. The source of POC in an inland shallow lake is particularly complex, and additional research on POC is needed to more clearly reveal its variation in inland water. Full article
(This article belongs to the Special Issue Remote Sensing of Water Quality)
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