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Sensors and Sensing in Water Quality Assessment and Monitoring
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Sensors and Sensing in Water Quality Assessment and Monitoring

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 September 2016) | Viewed by 76257

Special Issue Editors

Prof. Dr. Assefa M. Melesse

E-Mail Website
Guest Editor
Department of Earth and Environment, AHC-5-390, Florida International University, 11200 SW 8th Street, Miami, FL, USA
Interests: remote sensing; watershed modeling; climate change impact; sediment dynamics; river basin management
Special Issues, Collections and Topics in MDPI journals
Dr. Essayas Kaba Ayana

E-Mail Website
Guest Editor
Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, NY 10027, USA
Interests: remote sensing of water quality; hydrologic modeling; change detection; validation of remotely sensed hydrologic parameters
Dr. Gabriel Senay

E-Mail Website
Guest Editor
USGS EROS Center, North Central Climate Adaptation Science Center, Fort Collins, CO 80523, USA
Interests: remote sensing hydrology; evapotranspiration and soil moisture modeling; drought monitoring and food security; water use, quality, and availability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In this Special Issue, “Sensors and Sensing of Water Quality Assessment and Monitoring”, we invite contributions that demonstrate the use of sensors and remote sensing technologies to assess the physical, chemical and biological indicators of water quality. Contributions that highlight the use of optical and microwave remote sensing, sensors (handheld, air and space borne) and new applications on algorithm development, evaluation and validation are encouraged.

Prof. Dr. Assefa M. Melesse
Dr. Essayas K. Ayana
Dr. Gabriel Senay
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water quality
  • sensors
  • sensor design
  • suspended sediment
  • nutrients
  • sediment
  • eutrophication
  • fluxes
  • validation
  • statistical analysis
  • modeling
  • algorithms

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Published Papers (4 papers)

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Research

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3391 KiB  
Article
Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance
by Chen Zeng, Huiping Xu and Andrew M. Fischer
Sensors 2016, 16(12), 2075; https://doi.org/10.3390/s16122075 - 7 Dec 2016
Cited by 22 | Viewed by 6263
Abstract
Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust [...] Read more.
Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy. Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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8308 KiB  
Article
Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary
by Pei Shang and Fang Shen
Sensors 2016, 16(12), 1997; https://doi.org/10.3390/s16121997 - 25 Nov 2016
Cited by 25 | Viewed by 5563
Abstract
The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an [...] Read more.
The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an ideal means of monitoring spatial-temporal changes of Suspended Particulate Matter (SPM) in large estuaries like the Yangtze Estuary. However, a lack of proper atmospheric correction methods has limited its application in water quality assessment. We propose an atmospheric correction method based on a look up table coupled by the atmosphere radiative transfer model (6S) and the water semi-empirical radiative transfer (SERT) model for inversion of water-leaving reflectance from GF-1 top-of-atmosphere radiance, and then retrieving SPM concentration from water-leaving radiance reflectance of the Yangtze Estuary and its adjacent sea. Results are validated by the Landsat-8/OLI imagery together with autonomous fixed station data, and influences of human activities (e.g., waterway construction and shipping) on SPM distribution are analyzed. Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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1356 KiB  
Article
Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
by Tara Blakey, Assefa Melesse, Michael C. Sukop, Georgio Tachiev, Dean Whitman and Fernando Miralles-Wilhelm
Sensors 2016, 16(10), 1749; https://doi.org/10.3390/s16101749 - 20 Oct 2016
Cited by 7 | Viewed by 4591
Abstract
This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational [...] Read more.
This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning. Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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Review

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1078 KiB  
Review
A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques
by Mohammad Haji Gholizadeh, Assefa M. Melesse and Lakshmi Reddi
Sensors 2016, 16(8), 1298; https://doi.org/10.3390/s16081298 - 16 Aug 2016
Cited by 721 | Viewed by 58028
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 [...] Read more.
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). Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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