Posted May 2000
Updated July 2002
Adapted from the FAO Remote Sensing for Decision-makers Series, No. 19, "Inventory and monitoring of shrimp farms by radar satellite data". For a full list of issues available in the Series, see FAO Publications on Remote Sensing
Introduction | Aquaculture | Forest management | Rangeland assessment | Groundwater exploration | Forest fire management | Forest decline assessment | Crop information systems | Inventory and monitoring of shrimp farms | Assessment of priority areas for trypanosomiasis control actions by satellite data and fuzzy logic | Preparation of a land cover database through remote sensing and GIS
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 Industrial and artisanal shrimp farms in northwestern Sri Lanka mapped from ERS-SAR data acquired 18 April 1996 (above) | |
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Shrimp and prawn farming have grown rapidly in recent years in many tropical and subtropical countries, but there have been setbacks resulting from diseases and the growing awareness of the environmental and social impacts of shrimp farming. Inventory and monitoring of shrimp farms are essential tools for decision-making on aquaculture development, including regulatory laws, environmental protection and revenue collection. In the context of government aquaculture development policy, much attention has to be focused on the identification and monitoring of the expansion of shrimp farms, often located in remote areas.
The operational availability of high-resolution satellite imagery from Landsat Thematic Mapper, SPOT, Soyouz, ERS-SAR, RADARSAT and others opens up new possibilities for investigating and monitoring natural resources. Compared with information acquired by traditional methods, these data offer a number of advantages:
Synthetic aperture radar data from the ERS-SAR satellite were used in this study, not only for the inherent all-weather capabilities, but mainly because the backscatter from surrounding dykes allows for the recognition and separation of shrimp ponds from all other water-covered surfaces. The methodological approach indicated in the figure and described in an FAO technical paper ["Inventory and monitoring of shrimp farms in Sri Lanka" (Environment and Natural Resources Working Paper No. 1, 1999)], after field testing in northwestern Sri Lanka and refining of the interpretation keys, provides a mapping accuracy of over 90 percent.
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There are several advantages to employing SAR data for shrimp farm inventory and monitoring. apart from the all-weather capabilities mentioned above, speed is very important because of the rapid growth of this industry. Furthermore, interpreted data can be easily incorporated into existing GIS and the shrimp pond locations can then be evaluated in terms of site suitability and prior uses of the land. In this way the development of shrimp farming can be planned and regulated in a more rational way than is possible without such information.
Shrimp farms identified from interpretation of ERS-SAR data acquired in 1996, 1998 and 1999 were reported in seven maps at 1:50 000 scale with UTM grid. For immediate use of the results by the FAO project TCP/SRL/67, 12 maps have been converted to IDRISI files and additional information has been added, such as roads, railways and other reference points.
A total of 8 846.05 ha covered by shrimp farms has been mapped from 1999 SAR data, with an increase of 2 706.27 ha from 1996 data, showing the rapid expansion of the shrimp farm industry in northwestern Sri Lanka, which has increased its area coverage by 44.08 percent in less than three years.
 Shrimp farms map of the Seguwantiyu test site |
Cost and time for SAR mapping of shrimp farms
| Cost (US$/km2) | Time (months) | |
| Acquisition of satellite data | 0.15 | 1.0 |
| Image processing and interpretation | 2.00 | 2.0 |
| Ground survey | 0.10 | 0.2 |
| Map preparation | 0.10 | 0.2 |
| Total | 2.35 | 3.4 |
Cost and time for SAR monitoring of shrimp farms
| Cost (US$/km2) | Time (months) | |
| Acquisition of satellite data | 0.15 | 1.0 |
| Image processing and interpretation | 0.50 | 0.5 |
| Ground survey | 0.05 | 0.1 |
| Map preparation | 0.10 | 0.2 |
| Total | 0.80 | 1.8 |
| Note: The image processing and interpretation times described in the tables above have been obtained by a trained remote sensing professional with experience in radar image analysis. | ||
Once the first SAR inventory of shrimp farms in a given area is completed, its update on a routine annual basis is an easy task. SAR provides both speed and flexibility because of its independence from weather conditions. Thus, in theory, an update can be obtained by ordering the acquisition of an image at a month's notice.
The most expensive and time-consuming task, the calibration and validation of the methodology, is performed once and for all in the inventory phase. Ground checking can thus be reduced to a bare minimum, and only changes in land use should be assessed and quantified. It should be noted that since this was a pilot study, the greatest part of the time was dedicated to the development of appropriate methodologies and to testing the relevant image-processing techniques. This will be considerably shortened in subsequent applications.
The methodology developed in support of TCP/SRL/6712 and field-tested in Sri Lanka has proved to be reliable and extremely accurate. It is also economically viable, as the value of shrimps more than justifies an acccurate inventory and monitoring of the development of the farms. It may be operationally applied to similar environments in other countries facing a rapid growth of this industry.
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Study conducted by the FAO Environment and Natural Resources Service in the framework of the European Space Agency Third Announcement of Opportunity and in cooperation with FAO project TCP/SRL/6712.
The designations employed and the presentation of material in this brochure do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations concerning the legal status of any country, territory, city or area or of its authority, or concerning the delimitation of its frontiers or boundaries.
Remote sensing Introduction | Aquaculture | Forest management | Rangeland assessment | Groundwater exploration | Forest fire management | Forest decline assessment | Crop information systems | Inventory and monitoring of shrimp farms
