Next Article in Journal
Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input
Previous Article in Journal
Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(9), 1402; doi:10.3390/s16091402

Combining Remote Temperature Sensing with in-Situ Sensing to Track Marine/Freshwater Mixing Dynamics

1
Insight Centre for Data Analytics, National Centre for Sensor Research, Dublin City University, Dublin 9, Ireland
2
Carlow Institute of Technology, Carlow, Ireland
3
National Centre for Geocomputation Ireland, Maynooth, Ireland
*
Author to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 5 July 2016 / Revised: 12 August 2016 / Accepted: 23 August 2016 / Published: 31 August 2016
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [7193 KB, uploaded 31 August 2016]   |  

Abstract

The ability to track the dynamics of processes in natural water bodies on a global scale, and at a resolution that enables highly localised behaviour to be visualized, is an ideal scenario for understanding how local events can influence the global environment. While advances in in-situ chem/bio-sensing continue to be reported, costs and reliability issues still inhibit the implementation of large-scale deployments. In contrast, physical parameters like surface temperature can be tracked on a global scale using satellite remote sensing, and locally at high resolution via flyovers and drones using multi-spectral imaging. In this study, we show how a much more complete picture of submarine and intertidal groundwater discharge patterns in Kinvara Bay, Galway can be achieved using a fusion of data collected from the Earth Observation satellite (Landsat 8), small aircraft and in-situ sensors. Over the course of the four-day field campaign, over 65,000 in-situ temperatures, salinity and nutrient measurements were collected in parallel with high-resolution thermal imaging from aircraft flyovers. The processed in-situ data show highly correlated patterns between temperature and salinity at the southern end of the bay where freshwater springs can be identified at low tide. Salinity values range from 1 to 2 ppt at the southern end of the bay to 30 ppt at the mouth of the bay, indicating the presence of a freshwater wedge. The data clearly show that temperature differences can be used to track the dynamics of freshwater and seawater mixing in the inner bay region. This outcome suggests that combining the tremendous spatial density and wide geographical reach of remote temperature sensing (using drones, flyovers and satellites) with ground-truthing via appropriately located in-situ sensors (temperature, salinity, chemical, and biological) can produce a much more complete and accurate picture of the water dynamics than each modality used in isolation. View Full-Text
Keywords: in-situ sensing; sea-surface temperature; remote sensing; groundwater; salinity; nutrients; sensor networks in-situ sensing; sea-surface temperature; remote sensing; groundwater; salinity; nutrients; sensor networks
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

McCaul, M.; Barland, J.; Cleary, J.; Cahalane, C.; McCarthy, T.; Diamond, D. Combining Remote Temperature Sensing with in-Situ Sensing to Track Marine/Freshwater Mixing Dynamics. Sensors 2016, 16, 1402.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top