**3.4 Marine plastic and coastal litter**

With the increasing amount of marine plastic litter, its adverse chemical, biological, and ecological impacts on the marine ecosystem have raised the public concerns [81]. It is estimated that 4.8–12.7 million metric tons of plastic is dumped in the sea every year [82] due to increased use of plastic in industry and daily life [83, 84]. Although some surveys have been undertaken [85] to estimate the density and weight of floating plastic in the oceans globally, there is a lack of long-term and large-scale monitoring.

Some research has been conducted using remote sensing technology for the detection of floating marine plastic [86]. However, this research domain is still in its early stages. The reflectance from water captured by sensors is different from that of floating plastic objects. There are several reasons for this, (1) the physical properties of water are different from that of plastic, and they have significant distinct reflectance; (2) the transmitting ability of light through water is different


**Table 5.** 

*Active spaceborne sensors mostly used in oil spill detection.* 

**Figure 12.** 

*(a) ASAR wide-swath image of northwest coast of Spain, captured on 17 Nov 2002, at 10:45 UTC showing oil from the wrecked tanker approaching Spanish coast (source, ESA), (b) ASAR image of South Korea, captured on 11 Dec 2007, at 01:40 UTC, showing oil spill from 146,000 ton damaged crude oil tanker (source ESA).* 

 from that through plastic; (3) the absorption of light by water is different from plastic [87]. **Figure 13** shows different pathways of incident light after interacting with the surface (with and without marine plastic). Some studies have used hyperspectral remote sensing to study marine macroplastics [87] and microplastics [88]. Goddijn-Murphy et al. [87] considered the spectral signatures and geometric optics of plastic and seawater to develop a reflectance model for detecting macroplastics. The key is to determine the appropriate reflectance peak of plastic and consider its ratio with wavelength bands where water-leaving reflectance is low. Their model considers reflectivity of only one type of plastic litter in two dimensions. However, there are some constraints for detecting marine plastics in a real scenario since there have no standard shape, dimension, color, chemical composition, etc. Nevertheless, this study demonstrated the possibility of using remote sensing as a useful means for mapping and tracking of marine plastic.

#### **Figure 13.**

*Schematic of solar radiance interacting with (A) an open water body and (B) the same water body but with floating plastic. Ld is total downwelling radiance (solar beam + diffuse skylight), Lds is subsurface downwelling radiance, Lws is subsurface upwelling radiance, Lwr is radiance reflected directly off the water surface, Lwt is subsurface upwelling radiance transmitted through the water-air interface, Lpr is radiance reflected off the plastic, and Lpt is subsurface upwelling radiance transmitted through the plastic. Lw is total water-leaving radiance, Lwr + Lwt, and Lp is total plastic leaving radiance, Lpt + Lpr; subscript '0' indicates all the variables in the absence of plastic and FOV is a field of view [87].* 

*Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies DOI: http://dx.doi.org/10.5772/intechopen.81657* 

#### **Figure 14.**

*Distribution and density of marine litter along the coasts of the main Hawaiian Islands. Areas with 100 and more item densities are shown as hotspots of high marine litter [89].* 

 Detecting coastal litter near land surface is easier than in open ocean, as its reflectance and shape characteristics are not affected by its pitching and rolling on ocean waves. Moy et al. [89] used aerial imagery along with spatial analysis to categorize and map marine litter deposited along the coasts of the Hawaiian Islands. Very high-resolution aerial imagery allowed precise measurements of the quantity, location, type, and size of dumped litter (>0.05 m2 ) (**Figure 14**). In another study, Martin et al. [90] discussed the potential of combining images from unmanned aerial vehicles (UAV) and a machine learning approach, to detect and map marine litter. Machine learning algorithms are able to detect and classify objects when training samples with known training objects are provided. Their results showed that a UAV-based beach survey is 39 times faster than beach screening on foot and the large footprint of a UAV can cover entire coastlines and beaches including those in remote areas.

## **4. Conclusion**

 Increased levels of marine pollution due to anthropogenic activities are adversely affecting marine sustainability of marine ecosystems. Reviewed literature suggested that aerial and spaceborne sensors provide holistic information for monitoring many of the major marine pollutants. These include oil and chemical spills, sewage, high suspended solids, and algal blooms. Solid waste deposited in coastal areas can also be mapped using similar geospatial technology. However, there are some technical limitations in assessing detailed information about pollutants. These limitations stem from their dynamic nature, limited information of specific spectral response of pollutants, substrate response in optically shallow waters, and complex physics of light interaction through the water column. Despite these limitations, remote sensing is still capable of providing useful information about pollution events in sensitive marine areas.

Active and hyperspectral airborne sensors are often considered superior to spaceborne sensors for monitoring coastal and estuarine pollutants due to their real-time and detailed monitoring capability. Spaceborne sensors are more reliable for large-scale ocean, but with the recent development of sensor technology,

#### *Monitoring of Marine Pollution*

especially hyperspectral and active sensors with high temporal resolution, the applications of spaceborne sensors in coastal regions are also increasing. Presently, monitoring of marine waters is offered through numerous satellite sensors such as MODIS, VIIRS, AVHRR, OLCI, GOCI, Landsat, and Sentinel-2 with spectral and spatial resolutions able to measure marine pollutants and other marine parameters. Active satellite sensors such as SAR, altimeters, scanning radiometers, and microwave sounders, which are mostly used in physical oceanography, also possess the potential for detection of marine pollution under specific meteorological conditions and provide useful data to track and model the impact of these pollutants.

 Heavy metal pollution in coastal and estuarine region is another major concern of marine managers and researchers. Studies have attempted to use airborne hyperspectral data for this task, but satellite remote sensing is not yet able to detect these loads directly. However, the core factors causing these pollutants such as river plumes, sewerage, and industrial waste entering into these sensitive systems can be monitored using satellite remote sensing. If the point source of heavy metals is traced by remote sensing, policies and management practices can be applied according to the specific pollutants, and their mobilization and transfer of heavy metal to sensitive coastal environments can be avoided. Multiple approaches have proven reliable for this task.

In addition, recent developments in software and computation power have led to the increased use of data captured by remote sensing systems. Computer systems can now store and analyze large datasets. Therefore, marine protection agencies and government can utilize the full potential of remote sensing data in geographic information systems (GIS) and decision support systems (DSS) to manage marine resources and pollution. Collaboration between the research community and government is of utmost importance for using the full potential of this data in marine pollution management. Different applications of remote sensing such as detection of floating marine plastic litter and the use of active remote sensing for detecting algal blooms are still in the research. With the advancement of remote sensing sensors, sophisticated methods will be developed in the future for monitoring marine pollution.
