FAO FISHERIES TECHNICAL PAPER 356 Geographical information systems Applications to marine fisheries |
by
Geoffery J. Meaden
Department of Geography
Canterbury Christ Church College
Canterbury, Kent, UK
and
Thang Do Chi
Marine Resources Service
FAO Fisheries Department
The designations employed and the presentation of material in this publication 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 authorities, or concerning the delimitation of its frontiers or boundaries.
M-43
ISBN 92-5-103829-5
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying or otherwise, without the prior permission of the copyright owner. Applications for such permission, with a statement of the purpose and extent of the reproduction, should be addressed to the Director, Publications Division, Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, 00100 Rome, Italy.
Food and Agriculture Organization of the United Nations Rome, 1996
© FAO 1996
Sustainability of marine fisheries sectors has yet to be achieved and improved planning, taking into account conflicting marine uses and scarce resources, is therefore required. Consideration here is given to the use of management approaches which take a spatial viewpoint on differentiation in access to resources, of their rate of exploitation and of bioeconomic interactions within the sector and between fisheries and other sectors.
In order to understand and plan for increasing rates of changes of ocean use, infrastructure and socio-economic spatial patterns, the FAO Marine Resources Service is promoting the use of Geographical Information Systems (GIS) to access and use the range of relevant information available, through a number of workshops and training courses.
The present report is aiming at disseminating technical material to a larger audience: marine fisheries services of those governments concerned with fisheries research and management/development planning, plus workers in environmental fields, remote sensing, universities, etc.
ACKNOWLEDGEMENTS
The authors would particularly like to acknowledge Dr. S. Garcia (Director, Fisheries Resources Division, FAO Fisheries Department) who initiated the project and provided guidance throughout its development. We also wish to acknowledge the support provided by Dr. J.F. Caddy (Chief, FAO Marine Resources Service) and Dr. James M. Kapetsky (FAO Inland Water Resources and Aquaculture Service) and by the staff in the Geography Department at Canterbury Christ Church College. Access to otherwise unobtainable published and unpublished data and information on fisheries GIS applications is gratefully acknowledge to the authors of case studies presented in Chapter 9.
Our final thanks are given to Ms. M. De San Juan, Ms. N. Kiwan and to Mr. F. Carocci for the preparation of the final version of the text and of the mapping material.
Distribution list
FAO Fisheries Department
FAO Regional Fishery Officers
FAO Fisheries Projects
Directors of Fisheries
Directors of Fisheries Research Institutes
Regional and International Fisheries Organizations
Authors
Meaden, G.J.; Do Chi, T. Geographical information systems: applications to machine fisheries. FAO Fisheries Technical Paper. No. 356. Rome, FAO. 1996. 335p. |
ABSTRACT |
The late 20th century has witnessed increasing crises in the world's marine fisheries. A causal analysis of these reveals that a common element are various manifestations of spatial inequity. This most frequently includes the inequity of access rights to the resource, but factors such as variations in resource depletion, spatio-temporal variations in stock recruitment, the imposition of regulatory zoning, destruction of marine ecosystems and the siting of mariculture facilities are other examples. To resolve some of these problems, management practices must be improved. As has been shown in other fields where spatially related problems occur, there is now a promising tool, Geographical Information Systems (GIS), which, combined with other analytical tools and models, could allow for improved spatial management. GIS are basically integrated computer based systems which allow for the input of digital geo-referenced data to produce maps plus other textual, graphical and tabular output. The essential usefulness of GIS however, lies in its ability to manipulate data in a large number of ways and to perform various analytical functions so as to produce output which makes for more efficient decision making. |
As with many computer based systems, the key to GIS success lies in the acquisition of suitable data. The various means by which both primary and secondary data can be located, gathered, accessed and stored are described. Data acquisition methods vary from simple surveys, questionnaires and counts through to the access of secondary digital databases via on-line networking capabilities. Once data has been acquired it is only useful to a GIS when it has been formatted, processed or structured in a way which the system will understand. The various ways of doing this are introduced. GIS's can function in an almost limitless variety of configurations of hard and software. The basic elements of these are described, as are examples of some of the software packages. Before a GIS is implemented into a fisheries management programme, then there are two major areas of consideration. The first of these concerns the potential that GIS might have as a management aid. Seven potential database areas for management are described in some detail. The second area considered is that of how best to implement a marine fisheries resource GIS, along with how to ensure that sufficient guidance and support can be obtained to assure its continued success. The paper concludes with an examination of some case studies covering a range of marine fisheries related topics. |
PREFACE
This Technical Paper materializes, as probably other Papers do, from the topicality of several convergent processes and needs. Thus, the authors recognise that a series of strands of human progressive processes have reached a current developmental point such that they can now be unified, with the purpose of bringing about positive gains in the field of fisheries management. We can briefly allude to these processes and needs.
(a) The world extraction of fish and other biota from marine sources now appears to have reached a plateau, with FAO data showing that marine fisheries catches have not risen over the past five years. With fishing effort increasing, including technological improvements and applications, then there must be some doubt as to whether present catch rates can be maintained.
(b) Following enhanced perceptions of a deterioration in the world's natural biodiversity, which has been particularly recognised over the past 25 years, a strong conservation ethos has become apparent at many societal levels. This has been particularly noticed since the Rio de Janeiro Summit of 1992, and with the subsequent promotion of its Agenda 21, which aims to promote environmental consciousness upwards from a local level.
(c) Arising from both (a) and (b) above, and from the fact that resource exploitation in all spheres is occurring at an accelerating rate, there has been an increasing recognition of the need for the management of natural (or “wild”) resources. This is to be seen in the setting up of a range of authorities, pressure groups and government organisations at all levels, which are directed towards the environment, conservation, enhancement and protection.
(d) The information technology era has spawned an explosion of computing functionality. One manifestation of this has been in the emergence of Geographical Information Systems (GIS), with their capability of offering a tool for the varied management of all problems having a spatial connotation. Their worth is now being amply demonstrated in a wide variety of fields. One of their main strengths lies in the recognition that spatial visualization is of major importance in the armoury of ways in which humans can best acquire information.
(e) The need for information as a means of expediting management has grown almost exponentially over the last few decades. This has resulted in the so-called “data explosion”, with its needs to invest in methods of collection, storing, processing and outputting of data and information. Digital technology has developed, and the world is accumulating, by various means, vast databases of potentially useful data. With this explosion has come dramatic data price reductions and processing efficiencies.
So we would argue that the substance of what is presented in this Paper is the result of the merging of these five strands of human progression. Since each of these strands is so broad, then potentially the Paper might have a very wide audience among conservationists, ecologists, managers, geographers, etc, and we would hope that this should be the case. Realistically however, the Paper is most likely to be of interest to a more specific audience. Now that GIS has been shown to be a success in a variety of fields, then there must be a range of personnel who work in various fisheries fields who might wish to find out about its functionality. They might be working in fisheries research, fisheries management or in fisheries education, and this Technical Paper is aimed mainly at this audience. We believe that the content should be understood by readers at a variety of educational levels, though generally it is pitched at undergraduate level.
We have been extremely conscious when assembling the contents, that the fields of both marine fisheries and GIS are varied and to an extent complex. This being the case, it would be impossible to put together in one volume a complete “Do-it-yourself Fisheries Management GIS”. What this volume does therefore is to set out, in as straight-forward a way as possible, all the fundamentals and the potential that GIS has to offer in the marine fisheries field, i.e. to point the prospective GIS user in the right direction. There are certain more peripheral areas of GIS which we have deliberately not pursued in detail, either because they are exceptionally complex or because they are areas which might apply to computing in a more general sense. Examples of these would include error propagation, national transfer formats, data standards, copyright law, data modelling and statistical analyses. We have usually indicated where information on these can be obtained. It is also worth pointing out that nearly everything discussed in this Paper could apply to fisheries management which might be necessary on larger inland lakes.
As a means of providing a complete overview of this Technical Paper, Figure 1.3 illustrates its progression using a systems approach. The Paper itself commences with a detailed examination of why the management of fisheries could best be looked at as a spatial problem. Basically this means that many of the problems which the industry faces are a result of some manifestation of spatial inequity, i.e. unequal access rights to the resource, variable resource distributions, management practices which vary spatially, unequal spatial fisheries efforts, etc. We then briefly discuss the emergence of GIS in terms of what it is, how it developed and how it could be useful. Chapter 2 is devoted completely to the fundamentally important task of primary data gathering. Without large quantities of accurate data the system simply cannot function. Since the range of data collecting methods is so vast, we can only describe a few of them briefly. The description covers a hierarchy of methods, starting from several manual methods which use no equipment and proceeding right through to complex methods using advanced electronic equipment. Our next chapter (No.3) sets out the variety of ways which avoid primary data collection, i.e. through the acquisition of secondary data. This data is held mostly in the form of printed maps, tabular data sets and various digital data sets or databases such as remotely sensed imagery. We also explore some of the concepts comcerned with computer networking as a data source. Before any of the collected data can be of any use in a GIS, it has to undergo various forms of preparation. The various methods are described in Chapter 4. This is the first chapter which may introduce many entirely new concepts to a fisheries audience, and consequently there are many areas from this point on where the reader may wish to pursue ideas and themes in more detail elsewhere. Since this is the case, suggested sources for further information are provided in the text.
A GIS is fundamentally made up of hardware, software, data and operative personnel. Chapter 5 describes the range of hardware and hardware configurations which could be used, and it gives a necessarilly brief coverage of some of the software which is available. We have tried to restrict our discussion here to only those items which are directly related to GIS. This applies especially to the software since it is possible to link all kinds of packages to a general GIS in order to gain added functionality. Having arrived at an assembled array of data, hardware and software, the GIS can be made operative. Chapter 6 is devoted to outlining in broad terms what the functions of GIS are. We describe the main pre-processing functions which are designed to change the data into some useful form, the manipulative and analytical functions which allow for a wide range of operations, processing and analyses to be performed, and finally the ways of displaying and outputting the information. It is also necessary to explore briefly the fundamental area of database management. Having seen what GIS's are capable of doing, in Chapter 7 we look at their potential uses in the field of fisheries resource management. We begin this chapter by outlining, in a cautionary way, some of the main problems to be overcome (or coped with) in the use of GIS in this management area. Bearing these limitations in mind, it is feasible to direct a fisheries GIS in a number of directions, or towards the solution of problems in a range of fisheries associated fields. Seven major database areas are defined and discussed, although of course it would soon be obvious that these main areas could be sub-divided or integrated in a limitless number of ways.
If the potential GIS user has decided to adopt the technology then this is certainly no straight-forward matter. In Chapter 8 we consider all the necessary stages which must be gone through if the adoption is to prove successful. These all form part of the implementation procedures. Advice is also given on how guidance and support can best be obtained in order that the GIS can continue to operate in a satisfactory way. The Technical Paper would not be complete without giving some ideas on how a variety of marine GIS's have been successfully adopted throughout the world. We have therefore selected and detailed, in Chapter 9, a range of case studies which should give a thorough overview of the potential which GIS has to offer at this early stage in its adoptive life. The Paper concludes with a look at the current direction in which the main trends in GIS are moving, and it offers a view of the place of GIS in future fisheries management.
Hyperlinks to non-FAO Internet sites do not imply any official endorsement of or responsibility for the opinions, ideas, data or products presented at these locations, or guarantee the validity of the information provided. The sole purpose of links to non-FAO sites is to indicate further information available on related topics.
Table 1.1 | Selected Published Examples Illustrating Spatially Related Fisheries Management Problems |
Table 1.2 | Selection of the Subject Matter of Some Papers Presented at the 1993 ICES Statutory Meeting Showing the Spatially Related Nature of the Themes |
Table 1.3 | Practical Questions Which GIS May Answer |
Table 1.4 | Reasons Why Marine Applications of GIS Have Been Slow to Materialise |
Table 2.1 | A Summary of Primary and Secondary Data Collection for a Marine Fisheries Resource GIS |
Table 2.2 | Essential Data Required for a GIS Which is Being Used for Monitoring Fish Yields |
Table 3.1 | Types of Marine Data and Data Sets |
Table 3.2 | Some International Organizations Responsible for Collecting Marine Data |
Table 3.3 | Some Potential Holders of Marine Oriented Tabular Data |
Table 3.4 | Examples of 1994 Prices for Some Remote Sensing Digital and Photographic Products |
Table 3.5 | Availability and Price (1995) of Selected Digital Data for Europe |
Table 4.1 | A Comparison of Raster and Vector Data Models |
Table 4.2 | Information Which Needs to be Stored in a Meta Database |
Table 4.3 | Some Image Enhancement Processes Which May be Applied to Raw Satellite Sensed Digital Data |
Table 5.1 | Characteristics of the GIS Eras |
Table 5.2 | A comparison of processor units |
Table 5.3 | The Advantages of Using Distributed Computer Capabilities for GIS Work |
Table 6.1 | A Classification of GIS Functions |
Table 6.2 | The Main Features Required of a Database Management System |
Table 7.1 | Fisheries Applications of Mapping Techniques as Identified by Caddy and Garcia (1986) |
Table 7.2 | Factors Determining the Way in Which a Marine Fisheries GIS Could be Subdivided into Database Areas |
Table 7.3 | Likely Data Sources on Marine Water Conditions and Habitats |
Table 7.4 | Likely Data Sources on the Density or Distributions of Natural Marine Resources |
Table 7.5 | Regional Fishery Bodies Covering the Atlantic Ocean and Adjacent Seas |
Table 7.6 | Examples of Marine Protection Areas |
Table 7.7 | Some Common Ways of Measuring Fishery Effort |
Table 7.8 | The Concentration of Marine Fish Catch (by percent of total tonnage) for the Top 20 States |
Table 7.9 | Production Criteria Controlling the Mariculture of Oysters |
Table 7.10 | Possible Environmental Impacts from Aquacultural Activities |
Table 7.11 | Critical Coastal Zone Systems Important to Fisheries |
Table 7.12 | Examples of Human Activities Which May Negatively Impact on the Coastal Zone |
Table 8.1 | Steps Which Might be Necessary for the Successful implementation of a GIS |
Table 8.2 | The Major Factors Which Should be Included in a GIS Implementation Plan |
Table 8.3 | The Main GIS Journals and Trade Magazines |
Table 8.4 | Introductory Books on GIS |
Table 8.5 | Types of Back-up Services Which Help to Support GIS |
Table 8.6 | The Main Learned Societies and Associations Covering GIS |
Table 8.7 | International GIS Conferences |
Table 9.1 | The Main Mapping Themes Contained in the United Kingdom Digital Marine Atlas |
Table 9.2 | The Processing Sequence and Scores Added for Each Production Parameter in Salmonid Aquaculture Site Selection in Scotland |
Table 9.3 | Criteria Used to Identify Opportunities for Aquaculture in the Gulf of Nicoya, Costa Rica |
Table 9.4 | A Brief Description of the Datasets Currently Held in the Torres Strait GIS |
Table 10.1 | Major Influencing Factors on the Progress of GIS |
Figure 1.1 | The Inception Periods for the Major Developments in Desk Top GIS |
Figure 1.2 | Recent Sectoral Growth in the European GIS Market |
Figure 1.3 | A Schematic Diagram to Show the Structure of this Technical Paper |
Figure 2.1 | The Transformation of Data Via Various Stages of the Total GIS Operation |
Figure 2.2 | Fishery Information Sought in a Frame Survey of Communities Along the Libyan Coastline |
Figure 2.3 | Examples of Standardised Data Collection Sheets Used on a Baitfish Project in Tonga |
Figure 2.4 | Example of a Data Collection Form Used for Trawl Surveys |
Figure 2.5 | Portable Pen Plotter for the Field Recording of Survey Data |
Figure 2.6 | The Functioning of a Global Positioning System |
Figure 2.7 | The Marine Areas of Northwest Europe Presently Covered by Differential GPS |
Figure 2.8 | Propagation of an Acoustic Wave Produced by Vibration of the Transducer |
Figure 2.9 | Basic Variations in Transducer Configurations |
Figure 2.10 | Different Acoustic Transducer Sensing Modes |
Figure 2.11 | Typical Bathymetric Output Achieved from an Acoustic Bottom Survey |
Figure 2.12 | 3-D Bathymetric Image Derived from Acoustic Data |
Figure 2.13 | The Main Components of a Sidescan SONAR System |
Figure 2.14 | Possible Transect Patterns for Use in Trawl Surveys |
Figure 2.15 | Transect Plan for an Acoustic Survey Off South Africa Using Quasi-Randomly Generated Track-Lines |
Figure 2.16 | Current and Planned Satellite Systems in Support of Marine Meteorology and Oceanography - 1990 to 2010 |
Figure 2.17 | Processed Satellite Imagery Showing Plankton Densities Off Peru (left) and West Africa (right) |
Figure 2.18 | Spectral Signatures of Various Natural Earth Features |
Figure 2.19 | Geostationary and Polar Orbiting Satellite Positioning |
Figure 2.20 | Basic Principles of Scanning and Push Broom Satellite Remote Sensing |
Figure 2.21 | The Configuration of Landsats 4 and 5 |
Figure 2.22 | Stereoscopic Viewing Capabilities of the SPOT Satellites |
Figure 2.23 | Orbital Sequence and Colour Coded Chart of Ocean Surface Wind Speeds Collected on 18th June, 1992 by the ERS-1 Satellite |
Figure 2.24 | Composite Wind Field Map of the Western Pacific Compiled from Wind Scatterometer Data Collected by the ERS-1 Satellite |
Figure 2.25 | Technical Characteristics of the ERS-1 Active Microwave Instrument Operating in (A) Image Mode and (B) Wave Mode |
Figure 2.26 | Cost Comparisons for Map Revision in Canada Using Three Different Data Sources |
Figure 2.27 | Image Overlap Sequence for Attaining Stereoscopic Aerial Photography |
Figure 2.28 | Some Sources of Error in Aerial Photography |
Figure 2.29 | The Main Components of a Videographic Image Collection System |
Figure 3.1 | Example of a Marine Thematic Map Showing the Distribution of Manatees and Their Habitat in Southern Florida, USA |
Figure 3.2 | Some of the Major Types of Thematic Mapping |
Figure 3.3 | Communications Between User and Database via a MODEM and Network |
Figure 3.4 | The Overall Infrastructure of the Atlantic Coastal Zone Information Management System |
Figure 3.5 | Schematic Representation of the DFO's Ocean Information System (DFONET) |
Figure 3.6 | Schematic Model of the Electronic Chart Distribution System (ECDIS) |
Figure 3.7 | Schematic Diagrams Showing data Flow (A) and Operational Configuration (B) of the Ice Data Integration and Analysis System (IDIAS) |
Figure 3.8 | Example of a Satellite Imagery Product Order Form for ERS-1 Output |
Figure 3.9 | Portion of the National Wetland Inventory Map in Florida, USA |
Figure 4.1 | Schematic Diagram Showing How the Real World is Transformed to Obtain GIS Output |
Figure 4.2 | Example of the National Zip Code System Used in the USA |
Figure 4.3 | Comparison Between the Vector Model (A) and the Raster Data Model (B) |
Figure 4.4 | Numerical Coding Allocated to Vector Graphical Data in Order to Identify Different Object Categories |
Figure 4.5 | A Model Showing the Layers Used to Construct a Basic Vector Coastal Zone Map |
Figure 4.6 | A Simple Vector Map Having a Point, Lines and a Polygon With Their Associated Topological Encoding |
Figure 4.7 | A Simple Raster Map Plus the Run-Length Encoding Structure Used for Data Storage |
Figure 4.8 | Three Stages in the Construction of a Quadtree Data Encoding Structure |
Figure 4.9 | Comparison of a Raster Map (A) With a Vector Map (B) (see text for details) |
Figure 4.10 | A Typical Triangulated Irregular Network (TIN) and the Type of Topological Storage Tables Required |
Figure 4.11 | An Ichthyoplankton Data recording Sheet (File) |
Figure 4.12 | The Structure of the Main File in the NANSIS Database |
Figure 4.13 | Simplified Diagram Showing the Principles of a Digitiser |
Figure 4.14 | Increasing Digital Simplification of the Coastline and Hydrology of Sardinia |
Figure 4.15 | Diagrammatic Representation of Flat-Bed Scanning (A) and Drum Scanning (B) |
Figure 4.16 | An A0 Size Continuous Feed Scanner |
Figure 4.17 | Integrated Spatial Information System Based on a Multi-Tasking Environment |
Figure 4.18 | Optimal and Sub-Optimal Habitat Conditions for Atlantic Salmon in the North West Atlantic Ocean |
Figure 5.1 | The Changing Importance of the Three Main Types of Computer Processing Units |
Figure 5.2 | Plotter Technology: Price Against Performance |
Figure 5.3 | Typical Drum Pen Plotter |
Figure 5.4 | Typical AO Thermal Plotter |
Figure 5.5 | A Comparison of Operating Costs Over Three Years for Inkjet v. Thermal Printing Technology |
Figure 5.6 | A Basic Stand Alone GIS Configuration |
Figure 5.7 | A Typical Centralised, Departmental GIS Configuration on a Local Area Network |
Figure 5.8 | A Wide Area Networked GIS Configuration |
Figure 5.9 | Example of ARC/INFO Output Showing Marine Sediments in Part of the Wadden Sea, Germany |
Figure 5.10 | Screen Image of ATLAS GIS for Windows Showing Some Main Features |
Figure 5.11 | High Resolution Raster Output From IDRISI as Used for Pattern Recognition Training |
Figure 5.12 | Typical Output from ERDAS Showing Monitoring Processes on the Coastline in Georgia, USA |
Figure 6.1 | Typical Errors Which Might be Made Whilst Digitising |
Figure 6.2 | Summary of Vector to Raster and Raster to Vector Structure Conversion |
Figure 6.3 | The Universal Transverse Mercator (UTM) Zones |
Figure 6.4 | Some Geometric Conversions Which a GIS May Perform |
Figure 6.5 | Illustration to Show How a Map Outline Can be Generalised |
Figure 6.6 | Illustration Showing How Overlaying Techniques Can Lead to Poor Integration |
Figure 6.7 | A Simple Example to Show Interpolated Isolines |
Figure 6.8 | Buffers Around a Point, Line and Polygon |
Figure 6.9 | Some Raster Based Analytical Techniques |
Figure 6.10 | Method of Compiling a Connectivity Matrix |
Figure 6.11 | Method of Compiling a Contiguity Matrix |
Figure 6.12 | The Possible Range of Spatial Autocorrelation |
Figure 6.13 | A Hierarchical Database Structure Based on a Simple Map |
Figure 6.14 | A Networked Database Structure Based on a Simple Map |
Figure 6.15 | The Use of a Relational Database for Integrating Fishing Vessels and Home Ports |
Figure 7.1 | A 3-D Hypothetical Cube of Oceanic Water With a Slice to Show Fish Biomass Variations |
Figure 7.2 | The Three Main Ways of Mapping Variable Quantities |
Figure 7.3 | A Possible Means of Dividing a Marine Area for Mapping by Using a Nested Hierarchy of Cells |
Figure 7.4 | Simulated GIS Output to Show the Incorporation of Variance Estimates Into a Fish Biomass Survey Map |
Figure 7.5 | Species Richness Maps Showing Absolute Richness of Vertebrates in Part of Southern Idaho (USA) at Five Sampling Unit Sizes |
Figure 7.6 | Typical Time and Space Scales Associated with Plants (P), Zooplankton (Z) and Pelagic Fish (F) |
Figure 7.7 | Horizontal Disposition of Particles at 30 Metre Depth on Georges Bank, N.W. Atlantic Ocean, Compared With the Main Currents at the Same Depth |
Figure 7.8 | Simulated Movements of Sockeye Salmon in the North Pacific According to Different Start Locations (A = June; B = July; C = August) |
Figure 7.9 | (A) Bottom Temperatures and (B) Bottom Oxygen Levels (Mg/1) in the Northern Gulf of St. Lawrence, Canada for August - September, 1991 |
Figure 7.10 | Inferred Nitrate Readings from Temperature Isotherms off the Southern California Coast, USA |
Figure 7.11 | Distribution of Cod in the Eastern English Channel - October, 1988 |
Figure 7.12 | Distribution of Blue Whiting to the West and North of the British Isles |
Figure 7.13 | Dot Map Showing Total Mackerel Egg Abundance in a 1990 Survey, and Choropleth Map Showing Daily Mackerel Egg Production in the Same Period - in the Southern Bay of Biscay |
Figure 7.14 | Distribution of the 1991 Year Class of Haddock in the Irish Sea for September, 1991 and 1992 |
Figure 7.15 | Mean Surface Temperatures and Distribution of Anchovy in the East China Sea During March |
Figure 7.16 | Water Qualitative Parameters (A) and the Abundance of Juvenile Squid (B) off the North Coast of Argentina in Summer, 1989 |
Figure 7.17 | Distribution of Macroplankton Biomass Compared With Fish Catches in the Summer of 1988 in the Sea of Okhotsk |
Figure 7.18 | Maps to Show Shrimp Biomass Contours of 5, 500, 1000 and 1500 kg/km² in the Gulf of St. Lawrence, Canada in 1988. (+ = sampling point < 1000 kg/km²; * = > 100 kg/km²; o = non-sampled areas) |
Figure 7.19 | 3-D Plot of Water Column Biomass Along a 3.5 km Track Using Data from an Acoustic Survey |
Figure 7.20 | Cell Diagram for a Transport Simulation of Anchovy Eggs in the Pacific Ocean off Southern California, USA |
Figure 7.21 | World Map of Large Marine Ecosystems |
Figure 7.22 | Example of Northwest Atlantic Fisheries Organization Divisions and Subdivisions |
Figure 7.23 | 200 Mile Exclusive Economic Zones in the South Western Pacific |
Figure 7.24 | Committee for East Central Atlantic Fisheries (CECAF) Divisions off the North West African Coast |
Figure 7.25 | Fishery Zones in Part of the East China Sea |
Figure 7.26 | Hypothetical GIS Output to Show Fishery Catches (or Effort) by Trawl Hauls for Specific Areas |
Figure 7.27 | UK Demersal Fish Landings by Ports for 1975 and 1986 |
Figure 7.28 | Spatial Distribution of Catch Per Unit of Effort for Bigeye Tuna in the eastern Pacific |
Figure 7.29 | Structure of a Coastal Zone Management GIS Giving Ideas of Database Areas |
Figure 7.30 | “Map” Showing the Suitability of Parts of North East Spain to be Designated as a Natural Park |
Figure 7.31 | Sample Layers used in the Sapelo Island Integrated Resource Database |
Figure 7.32 | Currents and Bathymetric Contours in Part of the German Wadden Sea Coastal Area |
Figure 8.1 | The Main Processes and Activators Involved in Implementing a Marine Fisheries GIS |
Figure 8.2 | Marble's Spiral Model for the Design of a GIS |
Figure 8.3 | An Evaluation Matrix for Selecting a Suitable GIS Software Package |
Figure 8.4 | GIS Courses Available in the UK |
Figure 8.5 | A Sample Page from the GIS Tutor Programme |
Figure 9.1 | A Typical Screen Display for the Norwegian MRDB, Showing the Distribution of Mackerel Eggs in the North Sea in June, 1990 |
Figure 9.2 | Example of Skagex Atlas Output Showing a Black and White Copyof a Colour Raster Image of Temperature Distributions at 5 Metres Depth on 27th May, 1990 |
Figure 9.3 | The Main Transects from which Data was Gathered for the Skagex Atlas |
Figure 9.4 | Examples of output from the United Kingdom Digital Marine Atlas |
Figure 9.5 | Coastal Zone Map of the Wadden Sea Area of Northern Germany |
Figure 9.6 | Wave Height and Sediment Distribution Over Tidal Flats Near Norderney, Northern Germany |
Figure 9.7 | Map Showing Coastal Intertidal and Shallow Water Zones for Part of the Lamon Bay Area of Luzon Island in the Philippines |
Figure 9.8 | The Hydrographic Symbols Displayed on the Pilot UK Digital Coastal Zone Map |
Figure 9.9 | A Displayed Portion of the Pilot Coastal Zone Map Overlaid with User Defined Vegetation Occurrences |
Figure 9.10 | Cells Which Should Prove to be Most Suited for Salmonid Aqua- culture in Camas Bruiach Ruiadhe Bay, Scotland |
Figure 9.11 | General Features of the Gulf of Nicoya, Costa Rica |
Figure 9.12 | Location and Surface Areas for the Development of Intertidal, Subtidal and Suspended Cultures in the Gulf of Nicoya, Costa Rica |
Figure 9.13 | Map Showing Individual Shellfish Leases in Eastern Prince Edward Island, Canada |
Figure 9.14 | Example of Tabular Output from the CARIS GIS on Shellfish Leases in Prince Edward Island, Canada |
Figure 9.15 | Map Showing the Greatest Conflicts Between Mapping Themes for an Area Near to La Ciotat, Southern France |
Figure 9.16 | Total Catch of Pelagic and Demersal Fishes for 1989 from all Shelf Areas of the Mediterranean |
Figure 9.17 | Seagrass Presence or Absence Data in Torres Strait from (a) the Historical Survey (1984/89) and (b) the 1993 Survey |
Figure 9.18 | Changes in Seagrass Distribution in Torres Strait Between 1984/89 and 1993 |
Figure 9.19 | Seagrass and Dugong Distribution in the Torres Strait Plus Location of the Dugong Sanctuary |
Figure 9.20 | Hardware Configuration of the Marine Geographic Information System at the University of Hawaii |
Figure 9.21 | Display of Contours in the Selected Deep Water Site Off the Island of Hawaii |
Figure 9.22 | Estimated Oil Trajectories from the Oil Spill Coming from the Irving Whale in the Gulf of St. Lawrence |
Figure 9.23 | The Origins of all Catches Landed on Iles de la Madeleine During 1991 |
Figure 9.24 | Example Output from the Irish Navy's Fishery Protection GIS Showing Fishing Rights of Neighbouring Countries |
Figure 9.25 | The Main Features of a Gulf of Carpentaria Marine Survey (see text for details) |
Figure 9.26 | Differences Between Surface and Bottom Water Temperatures in the Gulf of Carpentaria, Nov/Dec 1990 |
Figure 9.27 | Location Map of the Scotia Sea Area, Including the South Georgia Island Area in Detail |
Figure 9.28 | Krill Biomass Distribution in the South Georgia Area as Plotted by the British Antarctic Survey Y |
Figure 9.29 | Map of the Seagrass Sampling Area in Moreton Bay, Queensland Showing Distribution of Sampling Points |
Figure 9.30 | The Classification of Various Seagrass Strata in Part of Moreton Bay, Queensland |
Figure 9.31 | Series of Simulated GIS Output to Show the Possible Relationship Between Fish Distribution and Habitats in Senegalese Waters |
Figure 9.32 | Screen From an IFREMER Developmental GIS Showing Trawl Haul Locations in the Gulf of Lyons, France |
Figure 9.33 | Screen From an IFREMER Developmental GIS Showing Simulated Fishing Activity Zones in the Gulf of Lyons, France |
Figure 10.1 | Innovative Life Cycles in Various Facets of GIS |
Figure 10.2 | Summary of the Applied Fishery Research Needs as Seen by The World Bank |