SECTION 7
The sea covers two thirds of the earth's surface. To a large extent, man is dependent on it for food species which include fish, shellfish, marine mammals, turtles, aquatic plants and algae. To exploit these resources more effectively, fishermen must catch the most fish possible (within biological constraints) while, at the same time, minimizing costs and optimizing the scheduling of their operations. Reliable environmental information is required from the scientific community for these purposes. Remote observations of the sea surface can provide a significant part of the information needed to assess and improve the potential yield of the fishing grounds. In the past, remote sensing was used predominantly to assist in the efficient harvesting of natural resources. Today it is being used for resource management, conservation and exploitation.
Variations in environmental conditions affect the recruitment, distribution, abundance and availability of fishery resources. It is not possible to measure remotely the entire range of information needed to assess changes in the marine environment. Knowledge of particular conditions and processes affecting fish populations, however, may often be deduced using measurements made by remote sensors, e.g., concentration of dissolved and suspended matter, variations in primary production levels, distribution of surface isotherms, location of frontal boundaries, regions of upwelling, currents and water circulation patterns. The parameters providing information on these environmental factors may allow a forecast of fish distribution or more generally the definition of marine fish habitats. These are often easier to sense remotely than the presence of fish.
Remote sensing techniques can be utilized directly, indirectly or as general aids in the detection and assessment of fishery resources.
The most direct and simple method of remote sensing in fisheries is visual fish spotting. Fishing fleets which exploit major fisheries such as tuna and menhaden are dependant on visual fish spotting from aircraft to direct their fleets.
Aerial photography per se is of little importance to the majority of commercial fisheries. The location of mobile fish schools, for example, cannot be provided fast enough to the fishermen. Aerial photography, however, can be of assistance to a fisheries scientist as it provides information about the distribution and relative abundance of pelagic fish, particularly the schooling species. The pattern of distribution and the location may identify the species observed, and the surface area of a school, measured from an aerial photograph, has been shown to be correlated with the biomass of some species.
Echo-sounders and sonars have been in use as remote sensors for at least 50 years and are now widely used by the fishing fleets of the world. Sonars are useful for the detection of fish and biomass estimation.
In recent years, high powered laser systems operating in the blue- green portion of the visible spectrum (lidar) have shown promise for the evaluation of fishery resources. A lidar carried on aircraft flying at an approximate altitude of 1700 m can detect fish at depths to 16 m.
Estimation of a fishery resource can be assisted by the measurement of parameters which affect its distribution and abundance. Much of the research dealing with environmental effects related to fisheries are concerned with the correlation of a single parameter with the spatial and temporal distribution of fish. It is most likely, however, that fish respond to the sum total of environmental factors. Thus, it becomes necessary to correlate a large number of parameters, obtained by remote sensing techniques, with fish distribution.
The environmental parameters most commonly measured from airborne and spaceborne sensors are as follows: surface optical or bio-optical properties (diffuse attenuation coefficient, total suspended matter, yellow substance, chlorophyll pigments and macrophytes, commonly grouped under the general term of ocean colour); surface temperature; vertical and horizontal circulation features; salinity; oil pollution; and sea state.
The optical properties in the marine surface layer are determined by the presence of dissolved and suspended matter. Under normal conditions, visible light penetrates marine waters to a depth of tens of metres. As the concentration of the water constituents increases, i.e. the water becomes more turbid, the penetration of sunlight is reduced as a result of absorption and scattering processes. Depending on the specific characteristics of the materials present in the water, i.e. on their spectral signature, the absorption and scattering processes will vary with the wavelength of the incident radiation. Multispectral observations, therefore, can be employed to estimate the nature and concentration of the water constituents. Passive sensors working in the visible wavelengths (mainly CZCS but also MSS, TM, HRV) are commonly used to image water colour. Active sensors providing their own source of illumination, e.g., lidar, can also be used but only from aircraft and for sampling, rather than for imaging purposes. The main parameters which can be derived remotely from water emergent radiation, through the use of empirically constructed algorithms, are listed below.
The diffuse attenuation coefficient at a specific wavelength is an apparent optical property. Its magnitude depends on the light distribution as a result of spreading, scattering and absorption that exists at the in situ point of measurement. This parameter, when correlated with Secchi disk depth and Munsell colour hues, provides the means of physically categorizing water according to colour. Its value can be interpreted as a measure of water turbidity and it constitutes a valuable tool in fisheries studies. It has been shown, for example, that turbidity and menhaden sighting in the Mississippi Sound are highly correlated.
In addition to optical parameters, the total concentration of the absorbing and scattering agents can be used to classify surface waters by means of their colour. The utilization of this parameter may be most appropriate when classifying waters where inorganic and/or organic sediments make an important contribution to the optical properties of the surface layer. It may also be appropriate if sediment concentration has to be used as a natural tracer for the identification of water movement and frontal boundaries (refer to Figure 7.1).
The term yellow substance may be defined as the material derived from the degradation of land and marine organic matter. It is an important parameter to monitor in the context of polluted coastal waters, since it may be used to identify marine areas where the exploitation of filter feeders, e.g., shellfish, could be hazardous. In certain regions of the world, for example the North Sea, this parameter exhibits some correlation with the salinity of surface waters.
The concentration of chlorophyll pigments (the photosynthetic pigments of phytoplankton) is often considered as an index of biological productivity and, in an oceanic environment, it can be related to fish production. Chlorophyll concentrations above 0.2 mg/cu.m indicate the presence of sufficient planktonic life to sustain a viable commercial fishery (Gower, 1972). Chlorophyll pigments have a specific and distinctive spectral signature since they absorb blue (and red) light and reflect strongly the green, thus affecting ocean colour. Multispectral observations from airborne or spaceborne sensors, therefore, allow the deduction of phytoplankton concentration (refer to Figure 7.2).
In coastal areas it is common to find macrophytic vegetation (seaweed). Some species are of economic importance but all species play an important role in supporting marine life. Different kinds of seaweed have different light reflection properties, for example, reflect more green or red radiation. This distinction which allows the differentiation of some seaweed species can be detected from airborne or spaceborne passive visible sensors. Due to the low intensity of the light as it leaves the water, however, it is usually more effective to employ airborne sensors such as aerial cameras or radiometers (refer to Figure 7.3).
Since 1973, the US National Oceanic and Atmospheric Administration (NOAA) has been engaged in sea surface temperature (SST) determination from satellite derived data. The process of extracting SST information from IR radiometer data is well established (refer to Figure 7.4). Global sea surface temperature charts are produced on an operational basis. They are in the form of computer printouts or contour maps with spatially smooth and radiometrically corrected measurements. It has been possible with data derived from TIROS, NOAA and the METEOSAT satellites to produce SST charts with an accuracy of 0.5°–2°C and in near real time.
The heliosynchronous satellites of the NOAA series provide high resolution (1 km) pictures twice daily while the geostationary satellites (GOES, METEOSAT) provide pictures every 1/2 hour but with a resolution of only 5 km. The geostationary satellites are principally used for the near-equatorial area where the sensor's resolution is at its best. For latitudes higher than 40° the image distortion is generally too extreme for operational use.
The occurrence of cloud or haze contaminates data to a certain extent but a knowledge of day-to-day variations or trends enables corrections to be made by interpolation. The sea truth information provided by ships is of further assistance in deducing the precise temperature fields.
To date, SST maps are mainly used by the salmon and tuna fishing fleets. It is well known that some tuna species feed on the warm seaward side of thermal fronts while salmon feed on the cold landward side. The occurrence of some other species can also be correlated with SST. In addition, physical features such as gyres, eddies, inversions and upwelling which are of importance to fisheries can be detected using SST maps.
Figure 7.1 Susppended sediment concentrations in the Bay of Fundy, Canada, as derived from LANDSAT MSS data
Figure 7.2 Chlorophyll concentration off the West coast of France, derived from a CZCS image (July 1981). A dinoflagellate bloom is shown as a red region.
Figure 7.3 Colour infrared aerial photograph (1:10,000) of the Chausey Islands, France, taken on April 24, 1982, at low tide. Five species of seawood can be distinguished.
Figure 7.4 Sea surface temperature image of the Northwest Atlantic Ocean recorded by IR radiometer aboard NOAA-9.
Several remote sensing techniques can provide information regarding surface circulation features of importance in defining marine fish habitats. These include the location and evolution of frontal boundaries, upwelling areas, currents and circulation patterns in general. Optical and thermal characteristics of surface waters can be used as natural tracers of dynamic patterns. Hence, the previous discussion of sea surface colour and temperature should be considered again in light of this application. Microwave techniques, particularly the use of active sensors (radar altimeter), also have applications regarding large-scale circulation features. For example, remote measurements of water surface vertical displacements can provide information on the dynamic characteristics of a basin.
The measurement of salinity from remotely sensed data is not operational at the present time. Research, however, indicates the possibility of determining salinity with the use of microwave sensors to an accuracy of one part per thousand. The microwave properties of the sea surface are a function of its physical and chemical state. The emissivity of sea water is related to salinity. Changes in salinity cause significant changes in the emissive brightness temperature of water for frequencies less than 5 GHz. Hence the salinity of sea water can be determined remotely by measuring accurately the emissive brightness temperature. The precision afforded by this technique may be adequate for mapping the spread of fresh water at a river mouth or for studying estuaries and near shore waters.
The numerous methods used for oil detection at the sea surface include visual detection by eye, aerial camera, MSS and CZCS; microwave detection by SMMR and SAR; fluorescence detection by lidar; and thermal detection by IR scanner.
The visual method images the change in colour and brightness due to the presence of oil. Other visible-light phenomena used to detect oil slicks include EMR interference effects (colour banding) and the suppression of solar speckle by slicks. The microwave method, when passive techniques are used, is based on the difference of emissivity between the sea surface and the oil slick. Active radar sensors depend on small capillary wave backscatter to be dampened by the oil slick as a means of oil detection. Fluorescent properties of hydrocarbons may be detected and discriminated by appropriate lidars. These laser fluorosensors can also identify the basic types of oil (heavy, light, etc.) and provide a measurement of oil slick thickness. Thermal sensors identify oil by means of the difference in solar absorption and thermal emissivity between oil and water and they also provide a basic measurement of oil thickness.
It has been known for some time that rough sea conditions created by wind have an effect on the distribution of fish. SAR equipped aircraft or satellites can survey the sea state of fishing grounds in near-real time. This information can be relayed to fishermen via a ground control station.
The microwave sensors on board SEASAT were capable of measuring the following with a high degree of accuracy:
| i) | radar altimeter: wave height and the microtopography of the ocean surface; | |
| ii) | synthetic aperture radar SAR: wave length and direction (refer to Figure 7.5); | |
| iii) | radar scatterometer SASS: near surface wind speed over the oceans in all weather conditions. |
The ERS-1 satellite, scheduled to be launched in 1989, will carry a payload of sensors similar to that of SEASAT. These should be available for the same applications as noted above.
Although the effect of waves on the distribution of fish have been studied by several researchers, no attempt has been made so far to relate quantitatively the abundance of fish to any parameter of sea state.
Satellites can assist the fishing industry in many ways other than the locating of fish per se. Most of these aids are also of assistance to mariners other than fishermen. The types of assistance that satellites can offer include the following:
| i) | search and rescue operations: The satellite NOAA-8 carries a special sensor, SARSAT (Search and Rescue Satellite Tracking), which detects the distress signals emitted by vessels in difficulty. The recorded signal is used to locate the position of the vessel. Sensors carried on board the Russian satellite series COSPAS-1, 2 and 3, launched respectively in 1982, 1983 and 1984, fulfill a similar function to SARSAT; | |
| ii) | weather reports: Environmental satellites such as NOAA, GOES or METEOSAT can provide weather information over a wide area at a given time (refer to Figure 7.6). This may assist fishermen to plan their fishing operations. In higher latitudes, ice and icebergs are major hazards; environmental satellites can assist in identifying ice and spotting icebergs; | |
| iii) | bathymetry: Remote sensing using passive or active visible sensors may be used for bathymetric measurements. With the exception of acoustic methods (sonar), airborne sensors provide the most accurate bathymetric measurements. In addition, active sensors such as bathymetric lidar are more reliable than the passive devices. |
Figure 7.5 SEASAT image of the Strait of Juan de Fuca taken on August 13, 1978, at an altitude of 805 km. The image form L-band SAR has a resolution of 25 m. Gravity waves, internal waves and patches of amooth water may be observed.
Figure 7.6 Visible band image from GOES West taken at 18:00 on November 22, 1984.
