Advances in Mapping from Remote Sensor Imagery: Techniques and Applications
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Tests of crop classifications from imagery taken over the Dutch Flevoland agricultural test site indicate that new ways to classify the radar data with levels of accuracy of Workshop presentations, including lively poster session during which researchers were limited to two minutes to present a synopsis of their work and extend an invitation to speak at greater length, gave a glimpse at the diversity of research now underway in the SAR science community.
Among the highlights:. An evaluation the best SAR polarisation methods to use for detecting land mines, including modern plastic versions that are nearly invisible to conventional ground-penetrating radars. A complete analysis of the test results is currently underway, he added. Polarimetric SAR techniques could improve the detection and classification of oil slicks. Hugh Corr with the British Antarctic Survey presented details of how ground-based SARs and polarimetric techniques have been used to look through ice more than 2.
Remote Sensing & GIS Applications: Lesson 1 Introduction to Remote Sensing
Participants at the POLinSAR workshop heard details of upcoming satellite missions that will incorporate new advances in SAR technology, faster revisit times, and a more complete inventory of those spots on Earth of interest to the scientists and the public. Gordon Staples with Radarsat International detailed current planning for the Radarsat-2 follow-on to the existing orbiting Canadian Radarsat spacecraft. Planned for a launch, the spacecraft is being funded through a cooperative arrangement between the Canadian government and Radarsat International's parent company, MacDonald Dettwiler.
After an evaluation of 32 application areas for radar imagery, Staples said that the new satellite offers the best improvements in examining crop types, crop conditions and providing information about sea ice. Another unique feature of the spacecraft is the capability to split the antenna receiving the return radar signal into two separate channels to allow for the tracking of moving targets for measuring water currents and monitoring traffic over a large area.
With the first launch planned in , Cosmo-SkyMed will be coordinated with optical satellites, feature revisit times of a few hours and metre and sub-metre resolutions. Responding to questions concerning the availability of Envisat imagery, Laur said that all Envisat instruments are completely activated and operating, all ASAR products activated to be released, and data are being delivered to scientific users.
A new Envisat ground station, located in Svalbard at the northern edge of Norway, brings additional capability to the network for delivering Envisat data to users, the ESA official added. The ESA POLinSAR workshop clearly demonstrated the strides taken by the radar research community in the past few years in radar polarimetry techniques and applications, and that more work is needed to move from the lab to practical uses.
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The spatial coverage of these sensors ranges from tens to hundreds of kilometers, and the temporal frequency is from hourly to weekly monitoring. Table 2 shows the satellite sensors most used for the study of water quality parameters related to marine pollution. The major application areas of active spaceborne sensors include, but are not limited to, sea surface currents, oil spills, biogenic films algal blooms , and river plumes Table 5.
Most algal species are nontoxic and are always present in coastal and open oceans.
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Planktons are the base of the marine food chain [ 22 ]. But, algae do not have to produce toxins to be harmful to the environment. The accelerated growth of algae produces a large amount of biomass which blocks sunlight and produces an anoxic or hypoxic condition dissolved oxygen is depleted from the water column , which is hazardous to marine life.
Algal blooms also affect coastal operations such as movement of ships, coastal tourism, and coastal sports Figure 3. Algal blooms can persist from a few days to more than a month and spatially they may extend from a few meters to tens of kilometers.
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The impact of algal blooms on marine life depends largely on the algal species involved. In situ field data collected using vessels are important for determining the algal species and level of toxicity during the bloom. However, field data are always limited for estimating the spatial extent as well as the dispersion. Detection of algal bloom by estimating the Chl-a concentrations using satellite imagery has been well-researched, as remote sensing has been used to observe ocean primary productivity since the launch of CZCS in High spatial and temporal resolutions are the main requirements of remote sensing data to study the variability in ocean and coastal Chl-a.
Using Remote Sensing to Distinguish Areas of High Algal Growth
By comparing a time series of satellite images, researchers can evaluate the spatial and temporal variations in Chl-a concentration during the bloom. This can also help to understand the dynamics of blooms. However, there are still certain conditions for using optical remote sensing to detect Chl-a, including i no or low cloud cover, ii the bloom should be near to the surface, and iii the bloom must cause the coloration of the water. Optical remote sensing can observe the coloration of water due to algal pigments. In the open ocean, the color of water is mainly determined by phytoplankton; hence, it is relatively simple to develop algorithms using a bio-optical approach and remote sensing reflectance [ 22 ].
In the open ocean, Chl-a can be retrieved from the ratio of blue and green wavelengths as Chl-a absorption is sensitive to blue wavelength and reflectance peak occurs in the green wavelength region [ 22 ].
Researchers have demonstrated that waters with increased Chl-a concentrations show a lower spectral response at short wavelengths especially in the blue wavelength regions [ 41 ]. This is due to increased absorption of red and blue wavelengths during photosynthetic process. Figure 4 shows the reflectance of water with increasing Chl-a concentrations. Narrow spectral bandwidth is a necessity for accurate retrieval of Chl-a concentrations [ 7 ]. Many researchers have used broad wavelength data i.
Table 3 shows some studies and datasets used to study Chl-a in marine regions. They found that a simple two-band model achieved a higher accuracy than a complex three-band model. Methods used to retrieve Chl-a using remote sensing data in the river and marine waters. Chl-a concentration observed in the Pearl River Estuary and its connecting rivers on 31 December Recently, machine learning approaches taking advantages of reflectance in all bands have also been applied using Landsat [ 45 , 52 ] and GOCI data [ 28 ].
Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies
We have evaluated three machine learning models to estimate Chl-a in the coastal waters of Hong Kong, of which artificial neural networks ANN performed best resulting in higher R 0. Chlorophyll indices such as the cyanobacteria index [ 53 ], maximum chlorophyll Index [ 54 ], and maximum peak height algorithm [ 55 ] have been demonstrated the robustness for detecting algal blooms and surface scum in coastal waters.
Comparison of measured and predicted values from three machine learning models. Synthetic aperture radar SAR data can also be used to detect large algal blooms in cloudy weather as algal blooms may appear as an area of low backscatter compared to surrounding water surfaces [ 50 ]. Turbidity is an optical property of water and is highly influenced by concentrations of suspended and dissolved organic and inorganic materials in water, including Chl-a, SS, and CDOM.
SS is mainly responsible for the light scattering, whereas CDOM and Chl-a control the light absorption properties of water [ 58 ].
Turbidity and TSS are two important variables of marine systems studies because of their direct linkages with photosynthetically available radiation, which affects the growth of plankton and other algae [ 41 ]. Turbidity has also been used to measure fluvial SS concentrations in rivers and river plumes [ 59 ]. These fluvial SS loads are rich in nutrients and considered a cause of eutrophication.
So, it is vital to have time series records of suspended sediment concentrations for better understanding of land-ocean interactions. High SS loads negatively affect aquaculture [ 59 ] and are hazardous to benthic invertebrates [ 60 ].
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These parameters are also associated with the diffuse attenuation coefficient penetration of light, in the blue-green region of the spectrum, through water column and Secchi disk depth a measure of water transparency [ 41 ]. For all these reasons, turbidity and TSS concentrations are considered to be critical parameters in the study of marine systems. Ocean color remote sensing techniques are widely used to monitor spatiotemporal variations in SS concentration and for mapping of water turbidity.
Remote Sensing of Environment
Figure 7 shows the changes in ocean color due to high sediment loads in the Yangtze River Estuary [ 60 ] and the Pearl River Estuary [ 61 ]. It is suggested that an algorithm using single bands provides a good estimation of TSS concentrations if an appropriate band is used [ 62 ]. However, coastal water often consists of a complex mixture of substances and results in large variations in reflectance.
In this case, multiple spectral bands should be adopted for TSS retrieval [ 62 , 65 , 66 ]. The peak of the reflectance curve shifts from the green region to the red region with increasing concentration of dissolved and suspended matter; and water starts reflecting significantly in NIR region [ 21 ] Figure 8. The Sentinel-2 true color image, captured on 31 December , shows high sediment concentrations in the Pearl River Estuary right. High levels of suspended matter concentration were observed in the Pearl River Estuary and its connecting rivers on 31 December High levels of turbidity were observed in the Pearl River Estuary and its connecting rivers on 31 December Table 4 includes some studies and methods used to study TSS in rivers, bays, estuaries, and relatively open coastal waters.
Stormwater runoff is also a large source of marine pollution as runoffs and pollutants from the urban watershed enter into the coastal environment after rainstorms. Stormwater runoff and municipal wastewater plumes may sometimes be overlooked due to persistent cloud cover in optical imagery.
These types of runoff are often detectable via SAR as they deposit surfactants on the sea surface, smoothing the small gravity waves and thus producing an area of low backscatter in comparison to the surrounding sea surface [ 74 ].