Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Hafeez, Sidrah; Wong, Man Sing; Abbas, Sawaid; Kwok, Coco Yin Tung; Nichol, Janet Elizabeth; Lee, Kwon-Ho; Tang, Danling

doi:10.5772/intechopen.81657

Cited by 52 publications

(38 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stormwater plumes reflectance values are consistent with other studies where we see highest reflectance values in the blue to red ranges (Hafeez et al, 2018;Wang et al, 2019). The wastewater plumes reflect most strongly in the green wavelength which shows similar reflectance signatures as CDOM and chlorophyll.…”

Section: Discussionsupporting

confidence: 91%

“…High turbidity is often due to high concentrations of suspended particles from sediments, CDOM, or algae and has units of Formazine Nephelometric Units (FNU) or Nephelometric Turbidity Unit (NTU). The bands that can detect turbidity are red, red-edge, or near-infrared (NIR) since turbidity has the optical properties of scattering light in these bands (Dogliotti et al, 2015;Hafeez et al, 2018). Turbidity is computed using the following equation (Nechad et al, 2009):…”

Section: Derived Turbiditymentioning

confidence: 99%

See 1 more Smart Citation

Analysis and Classification of Stormwater and Wastewater Runoff From the Tijuana River Using Remote Sensing Imagery

Ayad

Holt

et al. 2020

Front. Environ. Sci.

View full text Add to dashboard Cite

Urban runoff represents the primary cause of marine pollution in the Southern California coastal oceans. This study focuses on water quality issues originating from the Tijuana River watershed, which spans the southwest border of the United States and Mexico. Frequent discharge events into the coastal ocean at this boundary include stormwater and wastewater. This study focuses on differences in spectral features, as assessed by RapidEye, Sentinel-2 A/B, and Landsat-8 satellite data, along with physical and biological in situ data, to characterize and classify plumes into four key categories: stormwater, wastewater, open ocean/no plume, and mixed (when both types of plumes are present). Key spectral differences in the visible to NIR bands showed that stormwater had elevated reflectance (0.02 to 0.09), followed by mixed (0 to 0.08), wastewater (0 to 0.05), and open ocean/no plume (0 to 0.03) events. We also examined biophysical parameters and found that stormwater events had the highest values in remote sensing based estimates of colored dissolved organic matter (CDOM) (0.98 to 2.1 m–1) and turbidity (12.4 to 45.7 FNU) and also had a large range for in situ variables of enterococcus bacteria and flow rates. This study also finds that the use of spectral features in a hierarchical cluster analysis can correctly classify stormwater from wastewater plumes when there is a dominant type. These results of this study will enable improved determination of the transport of both types of plumes and transboundary monitoring of coastal water quality across the Southern California/Baja California region.

show abstract

Section: Discussionsupporting

confidence: 91%

Section: Derived Turbiditymentioning

confidence: 99%

Analysis and Classification of Stormwater and Wastewater Runoff From the Tijuana River Using Remote Sensing Imagery

Ayad

Holt

et al. 2020

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…In contrast with clear water, which is characteristically efficient at absorbing near infrared (NIR) to shortwave infrared (SWIR) light, floating materials including macroalgae and macroplastics reflect in the NIR 16,18,20,21,23,24 . Leveraging these spectral properties makes aggregated materials floating on the ocean surface visible from space.…”

mentioning

confidence: 99%

Finding Plastic Patches in Coastal Waters using Optical Satellite Data

Biermann

Clewley

Martinez‐Vicente

et al. 2020

Sci Rep

171

154

View full text Add to dashboard Cite

Satellites collecting optical data offer a unique perspective from which to observe the problem of plastic litter in the marine environment, but few studies have successfully demonstrated their use for this purpose. For the first time, we show that patches of floating macroplastics are detectable in optical data acquired by the European Space Agency (ESA) Sentinel-2 satellites and, furthermore, are distinguishable from naturally occurring materials such as seaweed. We present case studies from four countries where suspected macroplastics were detected in Sentinel-2 Earth Observation data. Patches of materials on the ocean surface were highlighted using a novel Floating Debris Index (FDI) developed for the Sentinel-2 Multi-Spectral Instrument (MSI). In all cases, floating aggregations were detectable on sub-pixel scales, and appeared to be composed of a mix of seaweed, sea foam, and macroplastics. Building first steps toward a future monitoring system, we leveraged spectral shape to identify macroplastics, and a Naïve Bayes algorithm to classify mixed materials. Suspected plastics were successfully classified as plastics with an accuracy of 86%.

show abstract

“…Airborne sensors tend to retrieve data with greater accuracy and spatial resolution, suiting smaller waterbodies; however, in situations where monitoring a larger waterbody is required, spaceborne sensors provide broader observational feasibility [96]. The spatial coverage of most used spaceborne sensors ranges from tens to hundreds of kilometers [97].…”

Section: Consideration In Water Quality Monitoring Using Sensorsmentioning

confidence: 99%

Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

Park

Kim

Lee

2020

Water

View full text Add to dashboard Cite

Water quality control and management in water resources are important for providing clean and safe water to the public. Due to their large area, collection, analysis, and management of a large amount of water quality data are essential. Water quality data are collected mainly by manual field sampling, and recently real-time sensor monitoring has been increasingly applied for efficient data collection. However, real-time sensor monitoring still relies on only a few parameters, such as water level, velocity, temperature, conductivity, dissolved oxygen (DO), and pH. Although advanced sensing technologies, such as hyperspectral images (HSI), have been used for the areal monitoring of algal bloom, other water quality sensors for organic compounds, phosphorus (P), and nitrogen (N) still need to be further developed and improved for field applications. The utilization of information and communications technology (ICT) with sensor technology shows great potential for the monitoring, transmission, and management of field water-quality data and thus for developing effective water quality management. This paper presents a review of the recent advances in ICT and field applicable sensor technology for monitoring water quality, mainly focusing on water resources, such as rivers and lakes, and discusses the challenges and future directions.

show abstract

Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Cited by 52 publications

References 81 publications

Analysis and Classification of Stormwater and Wastewater Runoff From the Tijuana River Using Remote Sensing Imagery

Analysis and Classification of Stormwater and Wastewater Runoff From the Tijuana River Using Remote Sensing Imagery

Finding Plastic Patches in Coastal Waters using Optical Satellite Data

Recent Advances in Information and Communications Technology (ICT) and Sensor Technology for Monitoring Water Quality

Contact Info

Product

Resources

About