Instructors Manual
Train-Sea-Coast Benguela Programme
Marine Pollution Control
Module 4: using geographic Information Systems for Managing Marine Pollution
DETAILED MODULE PLAN.
This module will run for one day in the marine pollution course. In this module the trainees will be
introduced to the scope of using a Geographical Information System GIS in assessing the risks
attached to a marine pollution event and help develop a contingency plan. This module first
examines the well-known Exxon Valdez oil spill of 1989 and its impact on Prince William Sound
and Copper River. The reason to use this case study is that an immense amount of GIS
information was collected in the aftermath of the tragedy and this information is freely available.
Once an understanding of the nature of the oil spill is discussed a more detailed lecture on GIS
will be presented. The third section of this course will examine how a trainee will use the South
African Coastal Information Centre online maps for evaluating an oil spill in the mouth of
Saldanha Bay. The reasoning for this is that CSIR has done a modelling exercise in the bay
which can be used as a simulation for a real life oil spill. The mastery test will be undertaken
using a multiple-choice question that is self marked and undertaken by the trainees.
Objectives
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To understand what information can be obtained from maps, orthophotographs and aerial
photographs and how it can be usefully applied.
Familiarize yourself with computer-based techniques to mapping and define what a
Geographical Information System (GIS) is and how it can be used for zonation of activities
and identification of potential problems relating to the coastal environment using St Helena
and Saldanha Bays on the West Coast as case studies.
Be able to define the differences between a vector and a raster-based GIS and know where
the strength and weakness of each system is.
Discuss how GIS can be used as a management tool and be developed for modeling and
prediction.
Discuss how a GIS can be implemented on an Internet.
This course will provide four PowerPoint lecture material with annotated notes.
Time Frame
09h00 – 09h30 Power Point 1 and Discussion
09h30 – 10h00 Power Point 2
10h00 – 10h30 First assessment (Mastery Test)
10h30 – 10h45 Tea break
10h45 – 12h30 Power Point 3 and Discussion
12h30 – 13h30 Lunch
13h30 – 15h00 Power Point 4 and Discussion
15h00 – 15h15 Tea break
15h15 – 16h30 Second Assessment (Mastery Test)
Materials and equipment needed
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FOR THE INSTRUCTOR
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A computer running PowerPoint connected to a data projector
Above computer connected to the Internet (When CSIR re-licenses its Pollution Model)
A whiteboard and pens
Trainee Manual
Instructors Manual
FOR THE PARTICIPANT
1. Pens
2. Trainee Manual
3. Word document Template to fill in electronically M4_Mastery_test_answersheet_1 & 2
4. Computers with Microsoft Word
Reference Material
Web Reference
The Exxon Valdez Oil Spill
http://response.restoration.noaa.gov/spotlight/spotlight.html
Books for an Introduction to GIS
Clarke, Keith C. 2001. Getting Started with Geographic Information Systems, 3rd ed., Prentice
Hall Series in Geographic Information Science, Prentice-Hall Inc., Upper Saddle River, New
Jersey.
Delaney, Julie. 1999. Geographical Information Systems, An Introduction, Oxford University
Press, New York.
DeMers, Michael N. 2003. Fundamentals of Geographic Information Systems, 2nd. ed. (update
edition), John Wiley and Sons, Toronto.
Longley, Paul A., Goodchild, Michael F., Maguire, David J., and David W. Rhind. 2001.
Geographic Information Systems and Science, John Wiley and Sons, Toronto
Books on South African Coast Sensitivity
Jackson and Lipschitz 1984 “Coastal Sensitivity Atlas of southern Africa”, Published by the
Government Printer
Report on Saldanha Bay
Taljaard, S and Monteiro, P.M.S. (2002) Saldanha Bay marine water quality management plan.
Phase I:Situation Assessment. Report to the Saldanha Bay Water Quality Forum Trust. CSIR
Report ENV-S-C, Stellenbosch.
MODULE CONTENT
Main Points of Module 4
The formal lectures will consist of four PowerPoint presentations entitled
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PowerPoint one Exxon Valdez oil spill 1989 in impact on Prince William Sound and Copper River.
(27 slides - no annotation is necessary and is self explanatory)
Lecture1_Exxon_Valdez_Impacts.ppt
Time required 30 minutes
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Summarised content
Title Page
Map showing the state of Alaska and the site of the Exxon Valdez oil spill
Detailed map site of the Exxon Valdez oil spill using an enhanced and
processed satellite image
Photo of the Valdez oil terminal showing the loading peers where the oil is
transferred from mainland to tankers
Photo showing the Exxon Valdez stranded on Bligh Reef
Photo showing transferrance of oil from the Exxon Valdez on two another
tanker
Photo showing a boom being deployed to contain any further leakage from the
Exxon Valdez
Photo showing spilt oil on the surface of the sea. Despite the measures taken
about 1/5 of the Exxon Valdez cargo was spilt
Photo showing sensitive sites that were being protected from the oil spill using
booms such as around this salmon hatchery
Photo showing oil washed up on the pebble Beach as a result of the storm that
followed the grounding of the Exxon Valdez
Photo showing oil impacting on a rock pool
Photo showing the use of the boom by barge and this skimmer to collect
surface oil
Photo showing the use of two boats and the boom and skimmer to concentrate
the surface oil
Photo showing NOAA scientists at work at the spill response command centre
pool
Photo showing the combined action of times and currents and the impact of
the oil on the intertidal zone
Photo showing how many of the beaches were heavily oil during the spill
Photo showing captured oil wildlife being moved to a rehabilitation centre for
cleansing
slide discussing methods of cleaning oil on the shoreline
Photo showing the use of high-pressure hot water washing of the rocky shore
Photo use of the boom to prevent oil that is being cleaned from refloating into
the ocean
Photo showing how sediment and some oil gets refloated into the ocean during
the cleanup
Photo showing case study of pre-high-pressure hot water washing at Block
Island
Photo showing the cleansing operation at Block Island
Photo showing an assessment of how deep the oil penetration has gone in to
the beaches surface
Photo showing the changing method to determine oil penetration
Photo showing debris that was collected and has been backed during the oil
spill. This will be deposited in a landfill site
Photo credits and reference material used
PowerPoint 2 Exxon Valdez oil spill 1989 showing file GIS is the use in the contingency plan.
Lecture2_Exxon_Valdez_GIS.ppt (9 slides-annotation is provided in the PowerPoint presentation)
Time required 30 minutes
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Summarised Content
Title Page – GIS coverages used for evaluating the Exxon Valdez 1989 Oil
spill
A brief list of coverages useful for assessing the impact of the Exxon Valdez
Impact divided into Satellite Images, Digital Elevation Models and actual
coverages
A map showing the trajectory of the oils spill (animated GIF)
A map showing the impacts of the oil spill categorised into high, medium, light
and very light.
A map showing the impact of the oil spill on recreational sites
A map showing the impact of the oil spill on marine bird colonies
A map showing the impact of the oil spill on Eagle nest sites
A map showing the ranking of the sites based on integrating the previously
shown coverages
References
PowerPoint 3 Basics of GIS
Lecture3_GIS_principles.ppt (25 slides-annotation is provided in the PowerPoint presentation)
Time required 105 minutes
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Summarised Content
Definitions of GIS
Types of data that can be included in a GIS
History of GIS
How does GIS vary from other Graphics Programs ?
Difference between a GIS and Maps/Atlases
GIS Maps are Customizable
GIS Maps are Searchable
GIS Maps are Updatable
What Computers would you need to run a GIS?
Where can you get GIS data?
Getting Maps and Data into a GIS
Who produces Digital Maps?
Obtaining New Data
Types of GIS
Raster GIS - Gridded Data
Vector GIS - Points, Lines and Polygons
Using a GIS for an Environmental Sensitivity Atlas
Thematic Mapping for Sensitivity-NOAA
List of sensitive Marine Environment-NOAAs
Sensitive Biological Features-NOAA
Symbolization of Sensitive Biological Features-NOAA
Sensitive Human Resources - General description-NOAA
Sensitive Human Resources - General description continued
Symbolization of Sensitive Human Resources - NOAA
Final Sensitivity Atlas-NOAA
PowerPoint 4 case study is simulated oil spill in Saldanha Bay South Africa.
Lecture4_Contingency_Plan.ppt (21 slides-annotation is provided in the PowerPoint presentation)
Time required 90 minutes
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Title Page
Why Saldanha Bay is Ecologically is sensitive?
A Sensitivity Atlas for Saldanha Bay
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Details of the simulation model and the URL from where it came from. This
site is currently down, however, you can preview previous simulations that had
been run and investigate the variables that we used to run the simulation.
Variables used for this study which is used to determine the impact of the oil
spill at the entrance to the Harbour and assess whether Malgas Island will
need a evacuation of its breeding Gannet population.
Start of the simulation showing the first hours of the trajectory of the oil spill.
A map showing how the oil spill is approaching Malgas Island
A map showing the progress of the oil spill trajectory
A map showing further progress of the oil spill trajectory
A map showing the oil spill almost on Malgas Island
A map showing how the oil spill virtually leaves Malgas Island unaffected.
A map confirming that the oil spill did not have a major predicted impact on
Malgas Island.
A map showing the area of interest that needs to be assessed in order to
develop a contingency plan
Use of the results of the simulation within a coastal sensitivity GIS
A screenshot showing the old South African coastal information Centre
interactive web-based GIS
A screenshot showing the above site with the satellite image selected and
zoomed in on Saldanha Bay.
A screenshot showing all coastal sensitivity layers being selected and the
various menus for operation.
A screenshot showing how the area of interested drawn as a line and has
been defined on the Web-based GIS
A screenshot showing an alternative way of defining an area of interest using a
box
A generic report that is generated based on 1:250 000 map sheets.
A screen shot showing how a user can define various reports for each 1:250
000 map sheets
JOB AID
INSTRUCTOR NOTES FOR LECTURE1_EXXON_VALDEZ_IMPACTS.PPT
The Exxon Valdez represents the largest marine oil spill in the history of maritime shipping and
occurred in 1989. Despite this statistic it could have been even more severe and its severity was
not so much how much oil was spilt but the incredibly sensitive environment in which it was spilt
in. This slide show was extracted from the NOAA website and serves to illustrate what needs to
be considered when trying to contain and clean up following a major oil spill. The slide show
progresses from the point of departure of the Exxon Valdez tanker from the Port of Valdez
through to the clean-up following the aftermath of the spill.
The state of California gets a significant proportion of its oil from the trans-Alaska pipeline and is
shipped via large oil tankers such as the Exxon Valdez. The story of the Exxon Valdez is that
shortly after leaving the Port of Valdez, the Exxon Valdez tanker ran aground on Bligh Reef not
far off the port of Valdez. The site of the spill was extremely sensitive from a marine ecosystem
perspective. When the tanker ran aground as a first step to control the potential pollution oil was
transferred from the stricken Exxon Valdez to the sister tanker the Exxon Baton Rouge. About
one-fifth of the oil carried by the Exxon Valdez was spilled during this process, but the balance of
42 million gallons of oil was safely transferred to the Baton Rouge. Now all efforts we needed to
prevent what oil that did spill from impacting on Prince William Sound. Following the offloading of
the oil from the Exxon Valdez it was refloated and moved away from Prince William Sound to
affect temporary repairs to the vessel.
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Despite these efforts within a couple of days of the spill, heavy sheens of oil covered large areas
of Prince William Sound. As the spilled oil moved across the waters of Prince William Sound, it
become necessary to try and protect especially sensitive locations, such as this salmon hatchery
in the eastern Sound. Protection was effected through deploying physical booms at the entrance
to inlets and bays. Such booms form a physical barrier to oil to prevent it from entering into such
sensitive areas.
Three days after Exxon Valdez grounded, a storm pushed large quantities of fresh oil onto the
rocky shores of many of the beaches in the Knight Island chain and this represented the most
significant ecological impacts.
Even before the oil reach various sensitive coasts attempts were made to contain the spill by
towing various booms. Once the oil is collected within the two towed boom a small skimmer at
the apex of the booms removes the oil from the water surface. The skimmed oil is then pumped
through a hose into one of the barges.
Within hours of the Exxon Valdez grounding NOAA scientists at the Port of Valdez initiated steps
to forecast the movement and fate of floating oil, to identify sensitive environments, and to
evaluate various coastlines based on the prediction of oil spill movement to assess their
sensitivity to oiling, and finally to review various methods of coastline cleanup and ensure that all
these steps are coordinated. Unfortunately in many locations in Prince William Sound, the action
of tides and currents distributed oil throughout the entire intertidal zone. Especially badly
effected was Northwest Bay on Knight Island where the tides had deposited oil on this rocky
beach face right up to the top of the intertidal zone. The backs of many bays were heavily
impacted with thick oil deposits such as Herring Bay.
The extend of the oil spillage and its trajectories made it clear that much effort needed to be
deployed into transporting captured, oiled wildlife to a rehabilitation center for cleaning and later
rehabilitation. Although researchers often debate the effectiveness of wildlife rehabilitation, in
case of South African oil spills notable success has been achieved such as the evacuation of
birds during the treasure oil spill off Dassen Island . The rehabilitation following the Exxon Valdez
could only be considered partly successful.
Following an oil spill on to the coastline, cleansing is undertaken using high-pressure, hot-water
washing. This treatment was used on many Prince William Sound beaches. In this process oil is
hosed from beaches and collected within floating booms located close to the coastline and the oil
skimmed from the water surface. Other common treatment methods included cold-water flushing
of beaches, manual beach cleaning (by hand or with absorbent pom-poms), bioremediation
(application of fertilizers to stimulate growth of local bacteria, which degrade oil), and the
mechanical relocation of oiled sediments to places where they could be cleaned by wave and/or
tide action. Although the booms contain the oil that is flushed from the shoreline a risk always
exits of this getting back into the sea to re-infect somewhere else. All of these processes of oil
cleansing often causes a release of sediment plumes into the sea that can cause additional
environmental harm.
During the clean up it is important to appreciate that the amount of visible oil on the surface of a
beach doesn't necessarily indicate the amount of oil that is on the beach, since oil can penetrate
into beach sediments. During the initial response to the spill, scientists should also assess the
depth of oil penetration and trenches may be dug to determine the depth of oil penetration.
During the cleanup really bad sediments and debris materials need to be contained with plastic
bags eventually deposited in a landfill site. In the case of the Exxon Valdez this material was
transferred out of the State of Alaska to landfill site in Oregon State, the closest facility certified to
properly handle this type of waste.
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INSTRUCTOR NOTES FOR LECTURE2_EXXON_VALDEZ_GIS.PPT
In the slideshow we used a Geographical Information System based on information supplied by
the National Biological Services, Alaska Science Centre and Pacific GIS (Contact Pacific GIS
pacificgis@igc.apc.org) to demonstrate how a GIS can be used in a marine pollution such as the
Exxon Valdez oil spill of 1989 which is considered to have been the largest marine oil spill in the
history of ship-base oil transportation. It had a devastating impact on marine life, but without
scientific services and good information the disaster would have been many orders of magnitude
larger. In the slide show we demonstrate the deployment of a GIS in developing and oil spill
contingency plan.
The first step to deploying a GIS is to identify and source different layers of information. In the
case of this example a satellite image is used as a backdrop for the study. On their own and
without processing satellite images are not very useful. This image has been processed into
different land-feature categories and an arbitrary palette of colours applied. The mid-blue areas
shows the Pacific ocean, the green areas represent the landmass and is categorised from
darkest green being the lowest lying to light green being higher lying areas. The highest areas
are mapped in white and represent the snow-covered mountains. The satellite image is used in
combination with a digital elevation model. The digital elevation model is reconstructed from
contours (lines of equal elevation) that can be extracted from normal topographic map sheets.
These contour lines are converted into discrete point information and points aggregated (usually
averaged). From this point data an image is interpolated using various geostatistical methods.
Essentially a continuous surface model is generated from the discreet point data. This allows a
user to determine fairly precisely the height at any point on the map surface. This also allows the
user to categorise areas of height at any level of categorising they wish to use. In this case the
use of the digital elevation model (DEM) is used to refine the satellite image to produce the
enhanced images that are used in the backdrop to these maps. These images are only used for
display purposes.
Before we get too far with the mapping, it would be best to reconstruct the trajectory of the oil spill
which started a short distance offshore. The oil spill was made worse due to a storm that
developed during the incident. Wind and tides were largely responsible for driving the oil spill
onto sensitive parts off the Alaskan coastline. By clicking on the map in the Power Point you will
advance the oil spill and see which parts of the coastline were most impacted as the oil spill
spread. It is recommended that this animation is repeated to familiarized learners with the pattern
of spread. This will make the next slides more meaningful.
During the actually event aerial reconnaissance and ground surveys the coastline were
undertaken and the results of these were mapped. Ideally a sensitivity atlas identifying all
features should have been developed as a pre-requisite for coastal management and certainly
sensitive issues such as eagle nests and diving bird colonies. Consistent with normal
environmental sensitivity mapping areas most sensitive or highest risk areas are mapped in red,
the next most sensitive areas are mapped in orange and the light areas are mapped in blue. Red
and other warm colours are usually used as a warnings and cool colours such as green indicate
safety or relative states of assurance. In this case site with just a slight impact were mapped in
light green. From this map you can see that areas that were identified as being most impacted
were largely east-facing coastlines whereas with one exception west or south- facing coastline
were only relatively lightly impacted by the spill.
Due to economics and taking into account public concerns recreational areas are first mapped as
black huts and the effects of the oil spill are superimposed onto this. In Cape Town a very high
priority is placed on cleaning the more popular beaches. A mouse click will add a red arrow which
identifies the sites most sensitive in sequence of priority.
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Marine birds are always considered to be a high priority in the case of an oil spill, since they have
to dive into the water to obtain their food (fish). Where these coincide with breeding sites they
become especially sensitive. In this map we used a black dot in a yellow circle as a symbol.
Like for the recreation sites these are prioritized using red arrows.
Finally in Alaska the Bald Eagles are top predators in the ecological food chain and therefore are
especially sensitive to the effects of changes in the food chain below them. Consequently
contaminated marine resources will have a major impact on them. Since they are the top
predators (carnivores) they have large feeding territories in which they may encounter
contaminated prey items. All breeding nest site of Bald Eagle where identified (purple hexagon)
since they will return regularly to the nest to feed their young and such sites need to be also
documented and assessed with respect to the impacts of the oil spill. Again the overlaying of the
oil spill intensity onto the eagle nests identifies various sites of sensitivity (this time six sites).
By integrating these different layers of sensitivity a ranking system for the contingency analysis is
undertaken. From the integration four sites were prioritised for rescue operations and post-spill
cleansing.
This operation can only really be undertaken through implementing a Geographical Information
System. This speeds up the ability to track changes in the dynamics of the oil spill so priorities
can be changed (adapted) during the clean up operation. As new data is collected it can be
instantly added to the information already existing and improved decision making undertaken.
Hopefully this exercise will show how a GIS is an indispensable tool for managing a marine
pollution event such as the Exxon Valdez or the Treasure which effected the coastline of the
Cape Peninsula some five years ago and threatened to contaminated the largest African
Penguin Breeding colony in the world.
INSTRUCTOR NOTES FOR LECTURE3_GIS_PRINCIPLES.PPT
In this slideshow we review the essential definitions, ingredients and applications of a GIS.
Possibly the simplest definition of a GIS is “a System of computer software, hardware and data,
and personnel to help manipulate, analyze and present information that is tied to a spatial
location”
Consequently four components are usually identified these being
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2.
3.
4.
spatial location – usually a geographic location
information – visualization of analysis of data
system – linking software, hardware, data
personnel – the most critical key to the successful use of a GIS
Spatial location is the most essential ingredient in the above list since almost 80% of all data has
some special reference … be it a postal code, a street address, or province locality.
Since we are increasingly connecting databases into “Relational Information Systems” where
data is linked to each other virtually all data can now be analyzed for spatial trends using a GIS.
To illustrate this a persons identity number is linked to both their credit card details and the house
ownership and as a consequence of this you can map age of occupants in any suburb using the
ID number to determine ages and tying this to the ownership of individual erf (plot) numbers.
Possibly even more revealing is as people spend at various shops using their credit card for
effecting payment it can be plotted in real space (since each shop in South Africa has a captured
locality in a GIS). Similarly use of a cell phone can also track a person’s whereabouts since each
cell call is sent to a reception tower for call delivery and these are distributed in a fairly tightly
managed spatial configuration that covers some 65% of South Africa, this latter feature has been
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used by South African Police to track criminal activities. This shows why information and system
are critical components of a GIS.
Finally the most critical issue is that people are trained to use a GIS. Use of a GIS occurs at
many levels of skill ranging from simply making a enquiry (spatial or non-spatial), to actually
preparing information for GIS, through to importing and exporting information between GIS
applications and different databases to actually developing various analytical techniques for
inclusion with a GIS as an application. All too often business and government agencies purchase
sophisticated GIS software (computer programs) and hardware (physical computer systems) but
do not factor in costs of training their workforces to use and develop systems so the full capacity
of their investments are not optimized.
Some other definitions…
A system for capturing, storing, checking, manipulating, analysing and displaying data which are
spatially referenced to the Earth (DoE 1987)
any manual or computer based set of procedures used to store and manipulate geographically
referenced data (Aronoff 1989)
An institutional entity, reflecting an organizational structure that integrates technology with a
database, expertise and continuing financial support over time (Carter 1989)
An information technology which stores, analyses, and displays both spatial and non-spatial data
(Parker 1988)
a special case of information systems where the database consists of observations on spatially
distributed features, activities, or events, which are definable in space as points, lines or areas. A
GIS manipulates data about these points, lines and areas to retrieve data for ad hoc queries and
analyses (Dueker 1979)
A database system in which most of the data are spatially indexed, and upon which a set of
procedures operated in order to answer queries about spatial entities in the database (Smith et al.
1987)
An automated set of functions that provides professionals with advanced capabilities for the
storage, retrieval, manipulation, and display of geographically located data (Ozemoy, Smith and
Sicherman 1981)
A powerful set of tools for collecting, storing, retrieving at will, transforming and displaying spatial
data from the real world (Burrough 1986)
A decision support system involving the integration of spatially referenced data in a problem
solving environment (Cowen 1988)
A system with advanced geo-modelling capabilities (Koshkariov, Tikunov and Trofimov 1989)
A form of MIS (Management Information System) that allows map display of the general
information (Devine and Field 1986)
Analysing these definitions you can see that they range from a narrow technical (DoE 1987;
Koshkariov, Tikunov and Trofimov 1989) to the broad institutional perspective (Carter 1989).
As you can see these definitions generally confirm that a GIS comprises technology (software
and hardware), a spatially referenced database (non-spatial data is linked to spatial objects) and
infrastructure which includes staff and facilities.
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Type of data and application that a GIS can be used for include
1. Cadastral information: this is parcel data that includes geographical areas such as
suburb, farm or plot boundaries. These are stored as vector files (see slide 15 of this
show).
2. Images: are usually used to help orientate users or to provide the most up-to-date “view”
of land features or a more “realistic” view of what is on the ground. Images are always
stored digitally as pixels (a rater based system see slide 14 of this slide show) and at a
particular resolution and generally are not used for manipulation. Images can be
acquired from satellites which either fairly course in their resolution (example LANDSAT
tm with 30 m ) but are fairly “inexpensive” to acquire (600 US$ for 185 x 185 km scenes)
through to high resolution commercial satellite images from IKONIS and THUNDERBIRD
which are 1-4 m resolution but very expensive to acquire (about 100~1000 times more for
the same size foot print as a LANDSAT image. Between these two extremes are SPOT
imagery which is 20 m resolution for colour and 10 m resolution for panchromatic (black
and white) and cost about 30 times more than the equivalent LANDSAT footprint. It
should be realized that these higher resolution image contain vastly more data since if
you increase the resolution by three times (viz what you get by using a SPOT
panchromatic versus a LANDSAT tm image) your increase you data amount by nine-old (
three times three). Other images can included scanned orthophotos (geo-referenced
black and white photos that include data such as contour) and even geo-referenced
colour aerial photos such as the City of Cape Town has for 1998 and 2002 which is 30
cm resolution for the entire Unicity but cost several hundred thousand US$ to acquire.
3. Land Uses – These can include different crops on a farm to different land use zoning in a
city (such as Industrial, multi-residential or single residential use). This type of data is
useful in our application for Marine Pollution since it could help with identify areas that are
potentially effected by an oil spill and have a high economic value (e.g. a commercial
oyster farm in a lagoon).
4. Inventory of Natural Resources - This would include may natural features that are
especially sensitive to the effects of an oil spill such as a Marine Bird Breeding colony or
a Bald Eagle nest site.
5. Market Analysis and Trends – Many companies use GIS to help do market analyses
such as introduction of a new product in a local area and use the Census data to
determine what the potential acceptance of a product and its projected sales would be.
6. Planning Schemes - This is the real domain of a GIS- since as we have seen in the
Exxon Valdez oils pill you pull data that is image based, with land use (recreation sites)
and an inventory of natural resources (bird colonies and eagle nest sites) into a
contingency planning for doing environmental clean up and to take precautionary steps
to minimize effects of a disaster such as relocation of populations of seabirds.
7. Risk Analyses – By collecting information and maintaining it (through updates) we can a
make situation analysis without the events actually taking place and identify areas most
vulnerable and effective “plan for an event” – this is the essence of a risk analysis and
again the dynamic nature of a GIS allow different “what if” scenarios to be generated and
vulnerability or risk of particular human activities (high valuation recreation sites) or
ecologically sensitive sites (e.g. eagle nest sites) be assessed. Using Risk analyses we
can modify certain activities so that they can reduce the risks to wildlife and the
environment such as the route of entry into a harbour of an oil vessel based on different
prevailing climate and tide conditions.
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8. Analytical Models and Simulations – these applications take the risk assessment one
step further with developing quantifiable models that simulation a particular scenario. In
South Africa the Council for Scientific and industrial Research (CSIR) has developed
models to assess an oil spill from a tanker entering a sensitive Bay/Lagoon system and
this will be explored in the fourth Power Point presentation.
So how does a GIS vary from other Graphics Programs?
Computer-aid design (CAD), computer cartography, database management and remote-sensing
were all important in the development of GIS as we know it today. Most current GIS packages
can trace their roots to a CAD, which automated the process of technical drawing. Considering
that maps are also no more than technical drawings – this is not a surprising fact. A feature that
came through fairly early on with GIS and other graphically orientated software was the ability to
store information in layers and that these layers can be switched on and off. Such a feature is
important with respect to annotation, so for example you do not always want to always have
lettering and this you might want to switch off or on depending on the scale of presentation
(drawings can be customized so that if they a printed at a small scale they will carry less detail
than if they are printed at a large scale they will carry more detail). This feature is also important
for visualizations were a simple 3-D framework can be enhanced by adding a texture over it –
rather like adding skin and flesh to a bony skeleton. This allows for significantly improved
visualization of objects or of environments.
Although almost all graphics-based software have improved with respect to rendering more
realistic images, a GIS is fundamentally different in that it links specific objects (e.g. a coastline)
to other (non-derived) information and allows information to be directly customize in its final
representation and so the coastline sensitivity can be attached to any coastline object.
Information linked to an object can either be derived through inherent object calculations whereby
in a CAD drawing you can determine length, size and area parameters of technical drawing if
prepared to a certain scale and that scale calibrated in some way – these are inherent object
variables and do not need to be stored in a table that is attached to the object. Simply re-scaling
of any feature drawn will automatically recalculate such parameters.
In contrast to these inherited object features that are calculated from the drawing itself information
can be attached to the object and stored in a separate table. A simple example could be the
hyperlink function we commonly encounter in our Internet page, where we click on parts of an
image and this opens different documents which are dependent and which parts of the image
was selected. Modern GIS take this simple link between object and data a good few steps
further. For example we might have categorized the coastline into rocky shoreline, cliffs, estuary
mouths (open and closed), sandy beaches or pebble/boulder beaches. If this coastline were to be
impacted by a large offshore oil spill, even before the spill has reached our shores we could start
planning the clean-up, allocate resources and estimate the financial costs of the disaster. All
previous information and experiences could also be quantified into spreadsheets or accessed
from various databases and then linked to a GIS. This is easier than you might think since it has
been estimated that more than 80% of all data has spatial dimensions.
A really powerful tool is the concept of thematic mapping where a variable in the database is used
to shade various land parcels (districts) and dynamic maps are thus generated. This makes
identification of spatial relations within the data set very easy to identify and represent through
different renderings – the impact of the oils spill is an example where we have mapped the
highest impacts in red to lowest impacts in green.
Difference between a GIS and maps/atlases
Maps for a long time have served as a guidance for navigation and to display and extract
information about features on the earth’s surface. It is this latter role that maps have been used
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as an aid to decision making, whether it is where to locate a development? or which parts of a
coastline is especially sensitive to development and risks of pollution? Accessibility of maps has
generally been good and the information is relatively easily extracted from them, but they do have
certain drawbacks. Possibly the most frustrating problem is that they have to be printed in a
relatively large publication format and invariable there are problems with features that are situated
on the edge of map sheets. This is made worse if the maps are compiled into an Atlas and you
have to compare one page of the atlas with another which is some pages on in the publication.
Imagine if you did not have all of these seams and you can more your “area of interest” to the
centre of the screen. Arising from this is that maps have to be printed at fixed scales which are
often not suitable for your particular query with it being either too small or too big. Now image
further that you can change the scale of the map. Printed maps invariable cannot provide all the
annotation you might require with respect to shading and place names. With printed maps
different features are not easily compared, and while a scale bar is always provided it is still not
easy to calculate the lengths of features represented on the map and is virtually almost
impossible to determine areas of features (e.g. with any degree of accuracy).
GIS Maps are Customizable
With a GIS you can combine information that you wish to use and ignore information that is
redundant to your needs. Each feature of a Map is stored in a GIS in a series of files that are
collectively referred to as a “layer” or “coverage”. Usually features are collected around themes
and stored within separate layers, for example estuaries would be one layer, coastline features a
second layer, and bathymetric contours a third layer etc. Consequently you can concentrate on
the information that is relevant to your inquiry, this is facilitated by the ability to work at any scale
you choose and that you can add or leave out labels of features at will.
Further you can change the colour and style of lines, the colour and shading properties of
polygons representing areas, the colour, font, size and orientation of labels and even symbol,
including making your own. Although we have said that you can add layers to one another an
important aspect is that the layers should use the same projection, datum and units of
measurement, in other words are drawn using the same basic ways of representing the Earth.
These elements are further defined as follows
Projection – this is the way in which a curved surface of the earth is essentially flattened for
presentation on a map sheet or a computer screen.
Since a spherical object cannot be flattened without distortion, no map projection can do more
than approximate the region it attempts to represent. Lengths, areas, shapes and angles are
distorted to varying degrees for different map projections.
Projections can be divided into the following categories and properties:Area: Many map projections are developed to be an equal area representation of the real world.
distort spatial information in some what or another. Shape, direction or scale are distorted in
order to achieve the equal area criteria. Albers and Azimuthal Lambert and are equal area conic
projections.
Shape: Projections which represent the shape of features are referred to as conformal.
Conformal projections usually maintain the accuracy of relative directions. Most large-scale maps
are prepared using conformal projections. Lambert conformal conic is a good example of this
projection.
Distance: Projections which correctly represent the lengths between two points are referred to as
equidistant. Equidistant projections are useful for calculating and summarizing lengths and
perimeter measurements of features
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Direction: Projections which correctly depict directions (azimuths) between points on the map
and its centre rare referred to as azimuthal. These projections will distort one of the other maps
parameters, but will represent all routes from the centre to other points as straight lines.
Mercators projection work on these assumptions are derived from estimates based on cylindrical
estimates.
Equal Area Projections
 Area relationships are maintained.
 Linear or distance distortion often occurs.
 Shape is often skewed.
 Intersections of meridians and parallels are not at right angles.
 The map is most distorted at the edges.
 Used when you want to see the distribution of a variable by land area (e.g. population
density).
Conformal Projections
 Angles are preserved around points and the shapes of small areas are maintained.
 Meridians intersect parallels at right angles.
 Scale is the same in all directions about a point (but the scale may change from point to
point).
 Shapes that cover large areas are distorted.
 Area is distorted.
 Used for navigation (want to maintain a set angle) and mapping phenomena with radial
patterns (e.g. radio broadcast areas, wind directions, etc.).
Equidistance Projections
 Great circle distances are preserved.
 Distance can be held true from one point to all other points or from a few points to others
but not from all points to all other points.
 Scale is uniform along the lines where distances are held true.
 Used in airplane navigation.
Azimuthal Projections
 True directions are preserved from one central point to all other points.
 Directions (or azimuths) from points other than the central point are not true.
 Azimuthality can occur along with equivalency, conformality, and equidistance.
 Used in navigation and large scale map series (USGS).
The simplest map projections use geometric shapes, which can be flattened without stretching
their surfaces. These shapes include cylinders, cones and planes. These shapes can either be a
tangent or a secant to the sphere of the Earth. In a tangent projection, the shape just touches the
surface at either a line or a point. In the secant case, the shape intersects as two circles (or as
one circle in the case of a plane). The place of intersection is the area of least distortion in
portraying features on the earth’s surface.
Map projections fall into the following general classes.
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Cylindrical projections are derived from projecting a spherical surface onto a cylinder. For
example if you took you’re orange and wrapped an A4 sheet of paper around it. The paper can
be arranged around the orange in a variety of arrangements
A Tangent Projection would result if you wrapped your paper vertically so that the cylinder was
parallel to the meridians (lines of longitude).
When the cylinder upon which the sphere is projected is at right angles to the poles, the cylinder
and resulting projection are referred to as transverse.
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Cylindrical projections that have equal area properties will have straight meridians and parallels
with the meridians being equally spaced but the parallels will not be unequally spaced. There are
normal, transverse, and oblique cylindrical equal-area projections. Scale is true along the central
line (the equator for normal, the central meridian for transverse, and a selected line for oblique)
and along two lines equidistant from the central line. Shape and scale distortions increase near
points 90 degrees from the central line.
The Mercator projection is one of the best known and has straight meridians and parallels that
intersect at right angles. Scale is true at the equator or at two standard parallels equidistant from
the equator. This projection seriously distorts distances and areas. The Universal Transverse
Mercator (UTM) is probably the best known projection system for displaying large surfaces of the
earth since it provides high levels of precision. To minimize the distortion the cylinder is wrapped
around the earth transversely and is place at 60 of rotation East and West of 1800 meridian for
each hemisphere. Consequently 60 zones north and 60 zones south are generated and are
numbered eastward from the 1800 meridian. Cape Town is the 34 th Zone and is referred to as
UTM 34S. The UTM system is only applied from 840 North to 800 South Latitude.
Conic projections which result from projecting a spherical surface onto a cone. When the cone
is tangent to the sphere contact is along a small circle such as a latitude. You can view this by
twisting your A4 sheet into a cone and placing over the orange.
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Albers Equal Area Conic projection allows areas to be proportional and directions true in limited
areas but distorts scale and distance except along standard parallels. This is one of the most
common projection used to map large countries where the east-west distances are greater than
the north-south extent (e.g. USA and Russia). It is often used to represent South Africa.
Azimuthal or Planar projections are where a flat sheet is placed in contact with a sphere, and
points are projected from the sphere to the sheet. You can do this by taking your A4 sheet and
pressing it against the orange.
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Azimuthal Equidistant projections are used to show route since distances measured from the
center are true. Lambert Azimuthal Equal Area projection has a central meridian that is a straight
line but other meridians are curved.
Finally there are non-projections often referred to as Plane (Cartesian) - they contain no
projection information and thus not good for accurate measurements, especially areas.
Datum - while we often refer to the earth as a sphere, it is more correctly referred to as a geoid
(defined as a hypothetical surface of the earth that corresponds to mean sea level). The earth is
not a sphere since it is flattened at both poles and bulges at the equator. In addition there are
significant bulges and depressions on the surface. There are hundreds of different datums which
have been used to estimate the size (areas and distances) of features on the earth. Datums have
evolved from those describing a spherical earth to ellipsoidal models derived from years of
satellite measurements. To best describe this geoid mathematically, we use reference ellipsoids
to approximate the size and shape of the earth.
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Each reference ellipsoid has a set of measurements associated with it, including the equatorial
radius, polar radius, mean radius, and the ellipticity (flattening).
A datum sets the origin and orientation of the coordinate systems used to map the earth.
Therefore, a geodetic datum is the starting point for the coordinate system. Different countries
and agencies within those countries use different datums to best match the geoid in their area
and/or to meet their agency's specific needs. The World Geodetic System 1984 (WGS84) is
probably the most used datum since it is used by Global Positioning Systems which derive their
position with reference to a system of satellites. In North America, the most commonly adopted
standard has been the Geodetic Reference System 1980 (GRS80) which is used as the basis for
the North American Datum 1983 (NAD83). In South Africa we traditionally used the Clarke 1880
ellipsoid as the datum. Using the wrong datum can result in position errors of hundreds of
meters. The diversity of datums in use today together with technological advancements have
made possible global positioning measurements with sub-meter accuracy. Consequently it is
important to reference all your positional information with the correct datum and projection
system. Extreme care is required for the conversion between different coordinate systems using
in different datums and significant errors can be generated with multiple conversions. For
example if you define a 1 km by 1 km grid using Clark 1880 and then change to UTM 34 South
and then convert back and re-measure your grid you will find that it is about 999.6 metres. While
this does not sound great, when to hundred and thousands of kilometers significant errors
become apparent.
Note on South African Projection Systems
Local reference system is based on a projection and datum. In South Africa maps generally use
a Gauss Conform projection based on the 1880 Clark Ellipsoid .and a specified meridian in 2 0
segments (from 170 to 330) . This has been replaced with the Haartebeeshoek 94 as from
January 1999. For Namibia the projection system is based on the Bessel. These reference
systems are based on metres as the unit of measurement.
Units of Measure - these can be either units of distance such as metres, kilometers, feet, miles
etc or expressed as degrees.
Considerations of projection, datum and nits of measurement are important since the most used
and older GIS software (e.g ESRI ArcView 3 series) does not allow multiple projections to be
displayed simultaneously, and even those that multiple projections do so providing you have all
the projection information stored for access by the software. Working with multiple projection
should only be used for viewing information and never used to edit information or prepare new
coverages, failure to observe this rule will result in serious data errors.
As you can see many problems for professional GIS users arises from confusion over projections
and datums. Consequently many organizations store their data in Latitudes and Longitudes that
are based on the WGS 84 datum. This is a convenient form for storage of spatial information by
institutions since it allows information from different sources to be directly used with each other
and for the information to be re-projected to different datum’s, projections and measurements on
a case by case basis. It does, however, have the disadvantage that calculations of distances and
areas are not truly accurate, and this can be very critical under certain conditions hence
surveyors and other high accuracy requirements should never use it as a system.
GIS Maps are Searchable
Each feature in a map can be considered to be an object which has its own identification, as well
as other associated information such as numerial values, categories, string texts and these are
all stored within a database as well as information on the object itself such as geographical
position, area, perimeter, centroid co-ordinates etc. Any of the data, whether it be within the
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database itself, or a measurement of the object, and whether it’s numerical or text can be
searched and identified.
Searches can be simple such as finding all estuaries which are always open (and therefore
especially sensitive to an oil spill) through to compound searches such as find all estuaries that
are always open and have a mangrove population (mangrove are especially productive
ecosystems and and oil spill that impacts on these systems will be especially significant).
Sophisticated GIS functionality can also allow you to search for all features which possess certain
inherent object parameters such as all line segments of the coastline that are longer than 5km
and are characterized as coarse-grained sandy beaches without having this data duplicated
within the database (in other words the search uses both the object’s inherent characteristics and
data that is attached as table to that particular feature). This allows you to identify both individual
features that meet specified criteria or groups of features with shared parameters and features.
You can also search all features that are within a certain a distance from a specified point e.g. all
estuaries that are within 5 kms of a certain point located on the map, or you can select within a
drawn rectangles, circle/ellipse or evening an irregular user-defined polygon.
The results of such searches are identification of specific rows of information from within the
database together with highlighting the features on the map in a contrasting colour (often yellow
or red or even definable by the user). Sometimes you simply want to group certain features
according to some grouping criteria and to shade each category in a different colour. Height data
is often represented as isolines or contours which each contour representing a specified value.
Using a thematic classification, each contour can be mapped depending on its values and often
represented as a gradient of colours (increasing height is often represented using the following
colours - green, yellow, orange, brown, purple and white). This allows much easier interpretation
of information and the quick production of a map that defines your specific search criteria.
GIS Maps are Updatable
Since the information is stored electronically and the user defines their requirements via a
software interface - information is more quickly updateable and information collected only hours
before can be used by an entire networked office within hours. Alternatively by simply writing the
information to CD the latest information can dispatched to offices outside the network and this is
also far quicker than waiting for the information to be published and distributed as a book. More
recently advance in GIS applications allow information to be updated and available to the entire
World Wide Web user community. Consequently information can be maintained in its most
current form for optimised decision-making.
The definitions of the GIS refer to it having a data storage, retrieval and presentation role and
requires having both software and hardware components together with human resources that are
usually divided into developers of the information and users of the information. A typical GIS is
fairly complex and are developed in a climate of strong competition therefore they tend to be fairly
demanding on the hardware used to run them. Since GIS databases are usually large and getting
larger and more complex they take up considerable disk space with their drawings and tables
they need considerable quantities of both disk space and memory for processing the information.
These data sets can run into hundreds and even thousands of megabytes. Backups of data can
be undertaken using re-writable CDs, although data sets larger than 640 Mbytes are getting
commonplace and alternative storage mechanisms are required.
GIS data needs to be accessed via software programs such as ARC INFO/VIEW (now called
ARC GIS) and MAPINFO. Often GIS software is graded into being able to view data, customize
and do minor alterations to both features and their tabulated data, to full authoring tools and the
ability to customise functions within the GIS package using BASIC computer language through to
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centrally managing large “corporate” data sets and distributing it to users via networks and the
World Wide Web. Each of these grades requires different hardware and software configurations.
In computer jargon we often speak about fat and thin applications and this is usually related to
whether you are a client (receiving information or called the host computer) or a server
(distributing information via a network). Consequently we might have a thin client which simply
means a computer that is light on resources (memory, processor or hard disk capacity) and this
would typically receive information via Intra/Internet and a fat server (a high capacitor computer).
The lightest and most inexpensive GIS application would be to access the World Wide Web and
use one of the map services that are provided. This allows you to do many of the viewing and
customizing of coverages (including selection of coverages and specific features within
coverages that meet certain selection criteria) locating geographical position and scale on the
maps as well as zoom and pan functions. This functionality is complemented by searches for
information and reporting it in both tabular and mapped renderings and the printing out the final
results as tables and maps. In such situations the servers do all of the GIS processing and
renders a snapshot of the results as a graphics file (JPEG) which is sent to the client for viewingand this is termed server-side applications. With increasingly more powerful personal computers
and higher bandwidth (or working within an Intranet) allows users to migrate to more client-side
processing (processing on the host computer) where information is sent via the network and the
client machine interprets the information and renders the results. Under these circumstances a
computer with at least 128 Mbytes of RAM is necessary, but otherwise this approach puts little
demand on the client computer’s disk space resources but still needs a fat server to deliver the
information and store all of the data. Until fairly recently most Desktop GIS systems would have
needed a similar amount of memory together with adequate disk space to store the data and
would normally have used either Window-based or Unix operating software. Recent releases of
some products have increased the specifications to 256 Mbytes of RAM and Windows
NT/2000/XP plus at least one large capacity hard-disk (30 Gigabytes plus). Most GIS applications
that are distributed via a network would required a high-end server and are migrating to Windows
NT or Window 2000 platforms. The web-based servers at the Biodiversity and Conservation
Biology Department, UWC use ARC GIS Internet Map Server software and Windows 2000
platform. In this case the hardware are a couple of IBM Netfinity Server with 4.3 Gbytes of RAM
and about 400 Gbytes of hard space which uses a Storage Area Network – a dedicated hardware
application that links a series of hard drives together and creates virtual hard drives that are
several times larger than the largest physical hard drives you can purchase. This setup also
allows any one of the hard disks to crash and for the data to be recovered and since the data is
spread across more than one hard disk faster disk access time is achieved.
Getting data and maps into a GIS
One of the biggest breakthroughs has been the ability to link existing data to various spatial
features through geocoding. It has been estimated that more than 80% of data contains spatial
elements, a postal code, street address, region, country etc. This allow data to be more easily
accessed spatially and for patterns in the data to be explored with more insight. Geocoding is
consequently linking data sets that where not spatial explicit with GIS data that does contact
spatially distributed features. To illustrate this imagine having a table of population summaries
such as income, education level, gender, age demographics and occupation for each magisterial
district in South Africa. It is impossible to comprehend such a large table of information, however
if each parameter describing the population can be colour-coded within thematic ranges for each
magisterial district and displayed on a map a much clearer interpretation of the data can be
presented. Geocoding involves capturing information that has some ID and spatial description
and character, e.g. a road or lake and address matching via a column in the table with other data
such as traffic flow and water quality.
The method of geocoding has large implications for the structure of a GIS database. In South
Africa address mapping to our Postal Code system should be virtually error free, since each
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postal code is unique, however address map to street name alone would not work, since the
same street name may be found in several suburbs of even the same city. To address map using
street information would require complementary information of suburb name to get a reasonably
accurate linking between the tble and the geographical objectives.
Other issues in geocoding are whether the map features are based on scanned images which
would have required manual post-processing and are very scale sensitive or data that was
obtained by digitizing through a digitizer tablet and storing the information as vectors. To scan
map features required for a GIS would require the use of a high-quality scanner which is simply
like a photostat machine. The resolution at which something is scanned equates with the number
of raster cells or grids and dictates the final quality and accuracy of the information (see slide 14
of this presentation) . Raster images are simply a grids that are coded with a number that
indicates some degree of reflectance/absorption and consequently has little intelligence. If fairly
coarse resolution is used features may drop out or be inaccurately rendered. Scanning a one in
50 000 topographical sheet at different resolutions will show this with text labels being especially
sensitive to "drop out" or become indecipherable. Trying to ascribe intelligence and management
operations to a raster image is fairly slow. Often raster images are converted to vector features
and these are edited and unique IDs ascribed to each unique object generated and this is fairly
slow process.
In contrast to scanning features into a GIS you can use a digitizing tablet to manually draw
features, this is also a slow process, but is generally more accurate, since it is scale independent.
A digitizing tablet consists of a board with a very fine network of wires embedded within it. By
using a pukker (like a mouse) it can detect very fine movements of position and record these.
With the advent of the GPS real time positions can be collected for very detailed field mapping
and relatively fast production of maps to about 4 m accuracy. Differential GPS will allow
positional accuracy of up to 10cm with post-processing and real time differential collection of
information of less than a meter is the normal accuracy. The University of California Santa
Barbara has been developing a system where your GPS is attached to your clothing, a small
screen is attached to set of glasses and a small hand set allows you to select and register an ID
against a particular feature you wish to map and you can start and stop collecting information as
you move around. A small-sized computer allows the information to be processed in real time and
you can see what data you have collected and even interrogate this data in relation to other data
sets pre-installed on you’re the computer to assess how much more and what type of information
is still required to be collected. This allows for progressive sampling and based on existing
partial datasets will determined how much more information is required to obtain a complete and
accurate map representation.
INSTRUCTOR NOTES FOR LECTURE4_CONTINGENCY_PLAN.PPT
In this PowerPoint slide show we demonstrate how you can use an Internet-based GIS for a
hypothetical analysis of an oil spill. In this case, we use modelling derived from a study that CSIR
undertook in the Saldanha Bay. This study was undertaken due to the very real threats of
pollution in this sensitive bay. Since it is the exit point of almost all iron ore produced in South
Africa. In the late 1970s the Harbour and entry routes were deepened to accommodate massive
iron-ore carrying vessels. Since these vessels are extremely large they carry large reserves of
fuel.
Description of the Saldanha Bay Area
While the north-eastern part of Saldanha Bay is extremely built up, the rest of the bay area is
extremely ecologically sensitive and is a Rock Lobster sanctuary. The southern end is a Lagoon
(referred to as Langebaan Lagoon). The lagoon is a marine reserve with the very southern end
having no access for fishing and netting nor for any motorboat use. The lagoon is extremely rich
in bait organisms, birdlife and fish and is the main stop over for migrant waders. Since most of
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the southern section is relatively unspoiled, it represents one of the few places along the South
African coast that has not had considerable development and therefore warrants protection.
Unique for the South African coast are several offshore islands which are protected in terms of
the Seabirds and Seals Protection Act 46 of 1973. The lagoon has 29 species of fish with the
southern end used as a nursery area by juveniles fish species and considered to be very
important for re-stocking of marine reserves.
For illustration a satellite image of the northern part of Saldanha bay is shown with the position of
a hypothetical oil spill at the entrance to the deep water harbour.
Close to where we have hypothetically positioned the oil spill for a vessel entering the Harbour is
Marcus Island which has now been connected to the mainland by a causeway. This causeway
was built to provide extra protection within the Harbour itself. Marcus Island was once one of the
largest African Penguin colonies of this Southern African endemic bird species. It still has
significant marine bird colonies which include the African Penguin (3000) and the relatively rare
Bank Cormorant (50) and African Black Oyster Catchers (120) and in many years is the site for
breeding for the Swift Tern.
Other island in Saldanha bay include Malgaseiland which has the largest breeding colony of
Cape Gannets in the world (27 000) and has African Penguins (4 500), Bank Cormorants (300),
African Black Oystercatchers (70) as well as well as Crowned and Cape Cormorants and Blackheaded Gulls). The Penguins and Crowned Cormorants breed throughout the year, Cape
Cormorants and Cape Gannets bread from September to February, Bank Cormorants in Winter
and the Gulls and Oystercatchers in summer and autumn (October to March).
Jutteneiland has a population of 48 000 Cape Cormorants, together with White-breasted and the
rare Bank Cormorant (100), 180 Oystercatchers, two species of gull (Haurtlaub’s and Blackbacked) and swift terns and also has some 4000 African Penguins.
Vondelingeiland in some years has significant breeding of the Swift Tern (3000), 15 000 Cape
Cormorant and 60 Bank Cormorant and Crowned Cormorants as well as some African Penguins
(300) two species of gull (Haurtlaub’s and Black-backed), 80 African Black Oystercatchers and
Sacred Ibis.
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Schaapeneiland and are also important breeding sites for Cape Cormorants (300) and Blackbacked Gullsand Sacred Ibis as well as occasionally the rare Caspian Tern during mid-summer
(December-January).
The entire southern end of the lagoon referred to as Langebaan Lagoon is a salt marsh
community and extremely sensitive. This is the largest salt marsh in South Africa. Although
referred to as a lagoon, it is geomorphologically a coastal Bay since there is no river entering the
lagoon. The lagoon is a very important site for wading birds especially those that migrate from the
northern hemisphere during the boreal winter periods. Common visitors include Ringed Plovers
(280); Turnstones (2000); Greater Flamingos (up 10 000 in winter);) Grey Plovers (5 500 of which
800 overwinter). Curlew Sandpipers (19 000-25 000) of which c 4000 overwinter) Knots (2 100-3
900 of which 750 overwinter); Bartailed Godwits (550) and Whimbrels (650). The main residents
are White-fronted Sandplovers, Black-backed Gulls which breed on an island in the south of the
lagoon - and African Black oyster-catchers. The population of the latter constitutes 12 % of the
total world population.
Within the Saldanha Bay/Langebaan area there are cottages and/or camping and caravan sites
at Hoedjiesbaai, Langebaan, Oupos and Churchhaven, and hotels in Saldanha Bay and
Langebaan. The main recreational activities are angling, sailing, power-boating and swimming.
There are a number of yachts anchored off Langebaan, and some in Saldanha Bay. There are
also a few yachts and house-boats in Kraal Bay.
On the coast there are cottages at Kreeftebaai, a fishing and diving locality. Further south,
Yzerfontein is a popular surfing, diving and angling spot. There are a number of holiday cottages
and a caravan park.
Access to the 15-mile beach at Yzerfontein. Commercial use of the area include about 15% of
the annual catch of pelagic fish by commercial purse-seiners. Langebaan and Saldanha Bay
support a commercial haarder fishery which constitutes about 12% of the haarder catch for the
whole coast.
Extensive catches of squid are made and kelp gathering operations on both the North and South
Heads of Saldanha Bay operate and yield about 300 tonnes (dry weight) per annum. In addition
castings of Gracilaria verrucosa are collected from Saldanha Bay beaches. A total annual catch
of the demersal fishery is about 165000 tonnes. The predominant species are hake, kingklip,
monk, snoek and squid. Extensive cultivated Mussel farms (reared from off shore rafts) exist in
the bay itself and some cultivation of seaweed (Gracilaria) has been done.
What will Sensitivity Map look like?
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This is a scanned map of Saldanha Bay showing the coastal sensitivity as a developed by
Jackson and Lipschitz 1984 “Coastal Sensitivity Atlas of southern Africa” ISBN 0908381263.
The highly sensitive areas are shaded in red and include the entire Langebaan Lagoon. Less
sensitive areas include sandy beaches which are in yellow and exposed rocky headlands which
are shaded in green and are the least sensitive to the effects of an oil spill. Various icons indicate
different specific sensitivities. The fish icon indicates fish spawning area, the penguin refers to
diving seabirds, the flying bird icon reflects general seabirds and the black triangles referred to
recreational sites. The dots around each icon reflect the sensitive season, but in this case all four
dots are present showing all year round sensitivity. This information is now available as a GIS
system but reflects the state of art for oil spill contingency planning some 20 years ago.
Subsequent to this map many other sensitivities have occurred such as commercial oyster,
mussel and seaweed mariculture.
Modelling the effects of an oil spill
The CSIR investigated the use of models to predict the effects of oil spill in Sandanha Bay. This
is part of a report prepared for the Saldanha Bay Water Quality Forum Trust and the report is
24
entitled “Saldanha Bay Marine Water Quality Management Plan – Phase 1: Situation
Assessment.
The following URL http://coastalmodels.csir.co.za will take you to a web page that allows users
to “perform online simulations using state-of-the-art hydrodynamic and water quality models”. The
models have been built by experienced research modellers at CSIR, Stellenboschand, South
Africa using the DELFT3D modelling system developed by WL|Delft Hydraulics in the
Netherlands.
This demonstration provides users with an on-line simulation models that can provide valuable
information to a wide range of users via the internet and users can develop their own scenarios
and then use another Internet GIS-based resource to develop a sensitivity analysis.
The Delft3D hydrodynamic and water quality model is used to simulate the following processes in
seas, estuaries, rivers and lakes and takes in the following potential variables.
1) currents
2) water temperature
3) salinity
4) dispersion of pollutants, e.g. oil, chemicals, bacteria, heavy metals, etc
5) eutrophication/dissolved oxygen
6) wave generation and transformation
7) sediment erosion-deposition
To develop our simulation for oil spill in Saldana Bay we have used the following six inputs, the
coordinates start duration and amount of spill together with a time period and interval report for
running the simulation. Please note that the X and Y coordinates reflect a projected coordinate
system and not degrees of latitude and longitude.
Coordinates of spill: x = 405124
y = 342433
Start of Spill: 06h00 9th June 2001
Duration of Spill: 1 hour
Total Mass of Oil Spilt: 25 ton
End of the Simulation: 06h00 12th June 2001
Time Intervals for Simulation: 8 hours
Average Wind Conditions: 50 km/h SE direction
When this model is run it will produce an animated gif showing the trajectory of the oil spill.
Remebering that we started the oil spill just off the penguin colony at Marcus Island you will note
in the bottom left corner a calendar showing the time period. Both the amount of oil floating on
the surface and the water depth are represented thematically (viz different shades from dark
brown to light yellow and representing the heaviest to the least heavy impacts).
Note that the oil spill is moving along the coast and is approaching the Cape Gannet breeding
colony at Malgas Island.The oil spill is sticking close to the coastline, however, in these
circumstances it might be wise to start an evacuation of Gannets from Malgas Island. It would
appear that the coast facing landwards should be prioritised for the evacuation of the birds. As
the oil spill continues to advance onto Malgas Island serious worries start to emerge. However, in
25
this case it is fortunate that the oil spill remains close to the mainland coastline and just a small
amount of oil seems to be set to pollute Malgas Island
In this simulation you can see that the oil spill largely missed the critical marine seabird colony at
Malgas Island. By running the simulation we have defined an area of interest in which the effects
of the oil spill will be most intense. You can then use this area interest in an online GIS system to
develop a contingency plan similar to the one demonstrated in the case of the Exxon Valdez oil
spill.
Now it is time to start using the results from the simulation analysis in a GIS system to develop a
contingency analysis.
The Power Point includes screen captures of the old SAcoast website (a new one is being
developed and more specially will address an oil spill contingency plan) – and represents one of
the first online GIS systems deployed in South Africa and used by the management of the South
African coastal environment. This is part of the South African Coastal Information Centre, which
is currently being re-developed for Launching in Late 2004
In the second screen capture of the SAcoast site your will note a toolbox the left hand side (in
the new application this will run along the top and about the same icons will be used. Along the
top are the various icons for environmental sensitivity – this will remain largely similar in the new
application. On the right-hand side is the layers/legend table of contents. This will be moved to
the lefthand side of the screen. At the bottom of the screen is a help menu. A more
comprehensive help systems will be developed and will use the same frame window as the
layers/legend table of contents.
In the next screen capture we have ensured that the layer reflecting the satellite image is selected
in the layers list and the map is refreshed using the refresh map button. The overview map will
also use the same frame as the legend/layers table of contents frame. This ensures that the
overview map is larger and please note that this is also clickable and offers users and easy way
to navigate the entire South African coast. Once the layers are selected and refreshed we will
then select the Legend to provide the map with an interpretation of all of the features that could
be of significance in the event of an oil spill.
In the fourth of the SAcoast screen captures we have drawn in an area of interest and have
ensured that all layers reflecting sensitivity to the oil spill are selected and the map has been
refreshed. You will note that the icons are broadly similar to those used in the 1984 Atlas of
coastal sensitivity shown previously. You can now use a square box to highlight the area of
sensitivity to the oil spill. In the new application a dedicated line tool will be developed. Once the
area of interest has been defined interactively on the map you can submit this to the GIS Web
portal and the results of all issues of sensitivity will be identified. In the new application results
will be reflected in the legend/layer table of contents frame.
Not only can detailed reports be generated based on users defining their areas of interest, but
also generic reports can be generated for each 1:250 000 map sheet of the South African coast.
In the above case it is map sheet number 10 and provides much of the detailed that we presented
at the start of this exercise.
In the final series of the SA coast screen captures we have highlighted two reports which might
help with developing the contingency plan for our simulated oil spill.
26
MASTERY TESTS.
Master TEST 1 – Revision (30 minutes)
1) Define what a DEM is and how it could be used together with a Satellite image in undertaking a
contingency oil spill analysis?
2) What were the most sensitive biological parameters in the Exxon Valdez oil spill and provide
reasons for your choice.
3) Describe events that could have made the Exxon Valdez oil spill even more environmentally
damaging.
An Answer Sheet in table format is provided. At the end of the document
27
Master TEST 2 – Putting a Contingency Plan into Action (75 minutes)
You have been asked to take responsibility for revising an oil spill contingency plans for your
National coast. As the first step you will need to define and describe the spatial data you wish to
use in developing these plans. You will need to organize your data under major headings and
codes (e.g. Recreation = R) and using a number rank each dataset from 1 equalling the highest
rank (=most significant). You can tie scores if you thing they equally important. You will also
need to work out whether it is seasonally sensitive or not. You will now need to invert these
scores and to do this you will add up the total number of dataset within each major heading and
then add 1 and now taking this score you subtract its ranking score – in other words you reverse
the ranks
To illustrate this we have identified four recreational datasets, namely bathing beaches R1,
general recreational beaches R2, angling sites (R3) and motorboat launch sites (R4). You have a
total of four site data sets so the highest bathing beaches will get (4+1)-1 = 4, recreational
beaches get (4+1)-2 =3, angling sites (4+1)-3 = 2 and finally motorboat launch sites (4+1)-4 = 1.
You will now need to work out rules that can be used to combine this new scores into an overall
prioritization score based on intersections as well. To do this you will need to identify whether the
data is highly localized (<100 m coastline) or fairly wide-spread. When combining highly localized
data you will use the summation function so where two of these data sets intersect you will sum
them in the intersection area. In contrast very wide-spread data you will use the overlay ensuring
the highest value is on top. The example below shows the combining rules in graphical form.
2
R
4
R
3
3
2
4
4
R
1
4
3
R
2
Final score for Recreation
Beach Bathing=R1
Beach General=R2
Angling=R3
Motor-boat Launch=R4
Score = 4 Widespread use Cover Rule
Score = 3 Widespread use Cover Rule
Score = 2 Widespread use Cover Rule
Score = 1 Localized use Intersection Rule
The combining rule sets using summation where they are localized and overlap where they are
widespread and seasonality. Note some features can be widespread or localized like sandy
beaches
Group
Layer
Code
Inverse
Distribution
Seasonal
Score
JFMAMJJASOND
Summer/Autumn/Winter/Spring
Recreation
Recreation
Recreation
Recreation
Beach bathing
Beach General
Angling
Motor-boat
launch
R1
R2
R3
R4
4
3
2
1
Widespread/Localized
Widespread
Widespread
Localized
Summer/Autumn/Spring
All Year
All Year
All Year
28
Mastery Test 1 ANSWER SHEET–Revision of the first two lectures
Name
Time 30 mins
Question 1 Define what a DEM is and how it could be used together with a Satellite image in
undertaking a contingency oil spill analysis?
Question 2 What were the most sensitive biological parameters in the Exxon Valdez oil spill and
provide reasons for your choice
Question 3 Describe events that could have made the Exxon Valdez oil spill even more
environmentally damaging
29
Mastery Test 2 ANSWER SHEET– Developing the Layers and Rule sets
Name
Group
Layer
Code
Inverse
Score
Distribution
Time 75 mins
Seasonal
JFMAMJJASOND
Summer/Autumn/Winter/Spring
30
Worked Example
Mastery Test 1 ANSWER SHEET–Revision of the first two lectures
Name
Time 30 mins
Question 1 Define what a DEM is and how it could be used together with a Satellite image in
undertaking a contingency oil spill analysis?
DEM stands for Digital Elevation Model.
A Satellite Image is obtained from space and effectively is a large-scale photograph of the earth
and can be processed in a variety of ways but essential will show the current status of rock
shores, estuaries, coastal vegetation and recent economic development. Used in combination
with an accurate DEM you can work out the lower lying and more susceptible areas in the event
of an oil spill. Also the satellite image is useful to identify shallow from deep water and just for
general referencing and interpretation of where the oil spill is likely to have the greatest impact.
Question 2 What were the most sensitive biological parameters in the Exxon Valdez oil spill and
provide reasons for your choice
Probably the most sensitive biological indicator was the Bald Eagle nests – namely because it is
a top predator in the ecosystem and therefore generally represented by fewer numbers (and is in
fact on the endangered list along most of the Pacific West Coast) and because it s home range
to secure food for its offspring is very large it therefore has a high frequency of encountering an
oiled sea surface. It is most especially vulnerable due to its long age and, like other raptors,
usually rears only a maximum of two chicks per season and it is slow to maturing taking about 5
years to reaching reproductive state. It is an iconic species, the national bird of the USA and in
Alaska there is the Bald Eagle Festive so it has economic benefits to the local community through
nature-based tourism.
Question 3 Describe events that could have made the Exxon Valdez oil spill even more
environmentally damaging
1) If the Exxon Valdex had been further along Prince William Sound more
biologically sensitive environments would have been affected.
2) Eighty percent of the oil was actually offloaded to the Exxon Baton Rouge – so
significantly more oil was present to pose even more of an environmental threat.
3) The storm could have started earlier and made conditions impossible to both
offload and to contain the oil using skimming techniques and booms.
31
Worked Example
Mastery Test 2 ANSWER SHEET– Developing the Layers and Rule sets
Name
Group
Layer
Code
Inverse
Score
Distribution
Time 75 mins
Seasonal
JFMAMJJASOND
Summer/Autumn/Winter/Spring
Recreation
Recreation
Recreation
Recreation
Physical
Physical
Physical
Physical
Physical
Physical
Physical
Physical
Physical
Economic
Natural
Resource
Economic
Natural
Resource
Economic
Natural
Resource
Economic
Natural
Resource
Biological
Biological
Biological
Biological
Biological
Biological
Biological
Biological
Biological
Beach bathing
Beach General
Angling
Motor-boat
launch
Estuary open
Estuary closed
River Mouths
Sandy Beach
Tombola
Coarse-grain
Beaches
Gravel/Pebble
Beaches
Wave-cut rocky
platforms
Rocky Headlands
Marine Fish
Stocks
R1
R2
R3
R4
4
3
2
1
Widespread/Localized
Widespread
Widespread
Localized
Spring/Summer/Atumn
All Year
All Year
Spring/Summer/Atumn
P1
P2
P3
P4
P5
P6
9
8
7
6
5
4
Widespread
Widespread
Localized
Widespread/Localized
Localized
Widespread/Localized
All Year
JASON
Winter/Spring
All Year
All Year
All Year
P7
3
Widespread/Localized
All Year
P8
2
Widespread
All Year
P9
E1
1
1
Widespread
Widespread
All Year
All Year
Oyster Farms
E2
3
Localized
All Year
Mussel Collecting
E3
3
Widespread
All Year
Seaweed
Mariculture
E4
3
Localized
All Year
Raptor nest sites
Turtle Breeding
sites
Juvenile fish
stocks
Marine sea bird
colonies
Salt Marsh with
eelgrass Zostera
Salt Marsh
Marine Mammal
Breeding sites
Significant
Intertidal
Community
General Marine
B1
B2
11
10
Localized
Localized
Winter/Spring
Spring/Summer
B3
5
Widespread
All Year
B4
5
Widespread/Localized
All Year
B5
5
Widespread
All Year
B6
B7
5
5
Widespread
Widespread/Localized
All Year
All Year
B8
5
Widespread/Localized
All Year
B9
3
Widespread/Localized
All Year
32
Biological
Biological
Strategic
Economic
Strategic
Economic
Strategic
Economic
Strategic
Economic
Strategic
Economic
Strategic
Economic
Birds
Terrestrial
Carnivores e.g.
Hyena
Terrestrial
omnivores e.g.
Baboon Intertidal
foraging
Nuclear Power
Plants
Harbours
B10
1
Localized
All Year
B11
1
Localized
All Year
S1
6
Localized
All Year
S2
5
Localized
All Year
Marinas
S3
4
Localized
All Year
Out falls
S4
3
Localized
All Year
Water Intake
S5
2
Localized
All Year
Pay Beach sites
S6
1
Localized
All Year
33