Precision Fishing
Abstract
This major project involving several objectives and phases to meet the goal of development a satellite-based fishery forecasting system in the South China Sea is aimed at supporting the national aspirations of developing an efficient offshore fishery. More importantly, it is aimed at providing the basis for alternate ways towards meeting the sustainable harvest of fishery resources. To data, the first phase of the project is completed with the development of an efficient extraction algorithm of sea surface temperature of South China Sea, which includes automatic geocoding, cloud masking and land masking. A GIS model of historical fish catch and oceanographic database for satellite and ship-land masking. A GIS model of historical fish catch and oceanographic database for satellite and ship-based data is currently being developed. Preliminary results show a clear correlation f fish catch areas with the present of warm waterfronts of Malaysia continent. The study will now go into the second phase to produce a GIS-based system for predicting potential fishing zones by seasons.
Introduction
The use of remote sensing to provide synoptic measurements of the oceans is becoming increasingly important in fisheries research and fishing operations. Variations in ocean conditions play key roles in natural fluctuations of fish stocks and in their vulnerability to harvesting [1].
Information on the changing ocean is necessary to understand and to eventually predict the effects of the ocean on fish population. The evolving capabilities of satellite sensors and data processing technologies combined with conventional data collection techniques and GIS modeling provide a powerful tool towards fish forecasting and thus allowing sustainable management of living marine resources.
Techniques in the development of fishing grounds have used such oceanographic phenomena as upwelling areas, temperature fronts, ocean color and the presence of large amounts of chlorophyll in the water as indicators of areas of fish stock congregations and fish stocks migration. Sea surface temperature and salinity and other oceanographic conditions can further assist to develop these areas known as potential fishing zones for forecasting of natural fluctuations of stocks, their congregations and migrations.
With the advent of satellite oceanographic, these oceanographic features such as ocean color, sea surface temperature, chlorophyll-a-concentrations can be successfully mapped in near real time basis. This capability coupled with the knowledge oceanographic conditions affecting fishery population and historical catch data can lead towards forecasting of fish populations and their
Movements and thus afford the capacity to harvest the fishery resources effectively and equally important on a sustainable basis [2].
Material and Methods
The overall goal of the project is to develop an efficient system for fish forecasting in the South China Sea and make this information available to the fisherman and other stakeholders through a fishery information system. To achieve this goal, the project has to meet several defined objectives viz.
- To develop an efficient sea surface extraction algorithm for NOAA AVHR data.
- To produce potential fishing zone (PFZ) maps from oceanographic data using GIS techniques.
- To verify this PFZ maps with actual historical fish catch data.
- To develop an effective and efficient real time fish forecasting technique for the South China Sea.
- To develop a GIS -based decision support system for predicting fishing grounds.
- To disseminate the information through an IT based fishery information system.
The project involves three major phases as shown in Figure 1.
In phase 1 of the project which is now completed, the project developed automatic geocoding of the NOAA AVHRR data, operationalize five methods of cloud masking techniques and develop the algorithm for quick sea surface temperature extraction for the tropical areas [3]. Concurrently, oceanographic data obtained from SEAFDEC fishery/oceanographic surveys. The Royal Malaysian Navy, PETRONAS and other oceanographic expedition [4] are obtained and a GIS model enveloping these data are being developed.
Historical catch data of pelagic fish for the South Chine Sea for the three east coast states of historical Trengganu and Johore for the year 1992 to 1997 are being gathered and organized according to monsoon season. This will then be used to verify the initial forecast maps for the area.
Operational sea surface temperature
In the 10.0 to 12.5 atmospheric window, the atmospheric absorption and re-emissions is principally due to atmospheric water vapor. The Spatiotemporal Split Window Technique (SSWT) method takes advantages of the differential absorption in the window region to correct the atmospheric effects [6]
Sea surface temperature T
s was extracted from the following relation.
Ts = a0 + a1T4 + a2T5 (1)
Where, T
s is surface temperature, T4 and T5 are respectively the radiometric temperature in two adjacent AVHRR channel of 11 and 13 mm, a0, a1 and a2 are are coefficients which depend on the surface emissivities, atmospheric absorption coefficients and total vapor amount. These coefficients can be computed from
Where
where L
i=T
i/n and the value of n for NOAA-14 AVHRR channels 4 and 4 are4.51 and 4.13
respectively (for a temperature range of 290-310K).
The performance of AVHRR based multichannel sea surface temperature had been shown by [5] used in this work of comparison. The multichannel sea temperature algorithum has two parts. (i) dytime MCSST algorithm as equation (4); and ii) nighitime MCSST algorithm as equation (5).
Ts=1.0346 T4+2.5779 (T4-T5)-283.18 (4)
Ts=3.6139 T4-2.5789 T5-283.21 (5)
Where T
4T
5 are the brightness temperatures (in degree Kelvin) by the AVHRR on the NOAA operational spaceraft and T5 sea surface temperature in degrees Celsius. This algorithm was successfully implemented by [5]
