Application of Thermal Remote Sensing in Fish Harvesting

-


Introduction:

Using satellites in fish harvesting is due to the great advantages they provide such as the wide range capture of see surface “large coverage”, temporal resolution and data are independent from weather. So that remote sensing has real impact on uncovering the relationship between fish distribution and surrounding environment.

The main objective of using remote sensing is to reduce search time and increase catch rate.

There are two methods to apply remote sensing data:

  1. Indirect Method: measuring oceanographic and environmental factors that correlate with fish habitat, such as ocean colour, sea surface temperature (SST), wind stress, current data, and other environmental characteristic that affect fish habitat Also, known the fact that fish correlate with nutrient-rich waters.

  2. Direct method: by spotting fish appearance. 

Measuring the environmental factors is much easier than spotting the appearance of a fish. And the main source for fisheries management is thermal infrared and ocean colour.

Using remote sensing data require a previous knowledge about fish life pattern and ocean circulation, Behaviour of a given species at various temperature, Catch rate at a specific area and Biological quality of the water.

There is a lot applications of remote sensing used in fisheries, but here we are talking about the application of thermal data.

Sea Surface Temperature SST:

It is one of the indirect methods which is obtained directly from the remote sensing satellite measurement of the thermal band which is related to the object temperature. It has the longest historical and reliability.

As some fish species depend on the surrounding environment temperature, the SST can relate to their life cycle. Using this information some scantiest has identify the spawning grounds for some species. SST is used mainly for salmon and tuna.

SST is used to identify:

  • Temperature regime.

  • Upwelling zones and thermal fronts, which helps on charting the productive area.

  • Ocean circulation pattern (temperature pattern), which helps on understanding the transport of larvae and pelagic resources.

Despites the great advantages of thermal infrared, there are some problems with infrared data:

  • effect of cloud haze and moisture, which could be eliminate by comparing daily base photos due to the great temporal resolution of remote sensing satellites.

  • Also one of the problems is how relevant is the surface temperature measured by the satellite which can be validated by the measurement made by ships.

Measuring the infrared radiation provide more accurate thermal patterns which is needed for determining fish distribution and estimating stocks.

Sea Surface Temperature map.

Examples of satellites and sensors that provide Thermal Infrared data:

  1. Landsat satellite, it is originally for land use but it also can be used in near shore and different studies.

  2. GMS-1.

  3. MODIS / T sensor.

  4. TIRROS, NOAA, METEOSAT,GOES: accuracy of 0.5 to 2 c near real time.

  5. Sensors like Seasat Multifrequency Microwave Radiometer  (SMMR) and Advanced Very High Resolution Radiometer (AVHRR),  has been used along time to measure the sea surface temperature and additionally the Thermal infrared band.

References:

  1. Application of Satellite Remote Sensing to Fishery Studies in Japan, Ichiro Yamanaka, Far Seas Fisheries Research Laboratory, 1000 Orido, Shimizu 434, Japan.

  2. Fisheries Applications, WSE instruments.

  3. APPLICATION OF REMOTE SENSING TO MARINE FISHERIES: ALTERNATIVE APPROACHES, R. SUDARSHANANd others, Post Graduate Department uf Marine Biology, Karnatak University, Kodibag - 581 303, Karwar, India.

  4. Use of thermal infrared remote sensing data for fisheries, environmental monitoring, oil and gas exploration, and ship routing. , Roffer M. A. And others.

  5. APPLICATION OF REMOTE SENSING TO FISHERIES, Fisheries and Aquaculture Department.

Keywords

Comments

Post a Comment

Popular posts

Datum

-
Image
  it defines the relationship between a local and a global three dimensional coordinate system of the same type, and it is defined as a re-position of a reference ellipsoid to be more accurate in representing a specific area . it also called local datum or national datum or just a datum.   Because an ellipsoid may be a best fit globally and the difference between the geoid and ellipsoid (n) be very minimum (globally) but not necessary for a specific area (country for example) so that a datum is created.   As every country wish to have an ellipsoid that is much accurate and close to the real surface of its land, some modifications may be applied to the previously best fitting global ellipsoid (correction for the ellipsoid parameters: a, b or e and f) or global reference system. Photo source   And that by taking a point and consider it as a datum centre point (datum origin point, it’s fixed and all other points are calculated from it), by assuming that this specific point i
Read more

Published Paper-2022: A Comparison of The Impact of Edge Detection Operators on The Extraction of Corner Points

-
Image
  Abstract: Edge detection is an essential pre-processing procedure involved in most digital photogrammetry applications. Edge detection captures the object's physical boundaries, a crucial property of objects in the image. The amount of information provided by the edge detection operator is a crucial factor for the extraction of Corner points. Each edge map has a unique amount of information that differs depending on the used edge detection operator. Edge detection operators get optimized to solve a tremendous number of issues such as noise, edge structure, edge orientation, and computation time. Because of these issues and others, there is no single operator that fits all kinds of applications and purposes. So, it is a critical task to measure the impact of each edge detection operator on the extraction of corner points and choose the operator that yields a precise localization of corner points. This study evaluates the impact of the edge detection operator and measures its eff
Read more

Published Paper-2020: Automatic Extraction of Corner Points from Aerial Images Using Point-Feature Operators and Hough Transform

-
Image
Abstract: Low-level feature extraction such as lines and points (i.e. corners), forms a fundamental step in digital photogrammetry and other fields. They supply the inputs for the photogrammetric orientation procedures; and they serve as an intermediate inputs for other processes such object recognition. With the accumulation of knowledge, the research community is in a better position to develop new generations of smart algorithms and solutions that possess a new level of maturity and understanding for the underlying challenges of automation. To this end, this paper presents an innovative approach for corner point extraction that combines the outputs from classical point feature operators with Hough Transform to generate a better hypothesis for a corner point that can be used for applications in urban areas. In particular, extracted point features were used to guide line extraction in a local neighbourhood by Hough Transform. Then the corner points that will be obtained from lines i
Read more