Master Thesis
submitted within the UNIGIS MSc. programme at the Centre for GeoInformatics (Z_GIS)
Salzburg University, Austria
under the provisions of UNIGIS joint study programme with Goa University, India
GIS for Assessing and Monitoring Coastal Changes, Flic en Flac, Mauritius.
by
Naim Ahmad Shaik Joomun
U0422949
A thesis submitted in partial fulfilment of the requirements of the degree of
Master of Science (Geographical Information Science & Systems) – MSc (GISc)
Advisors:
Dr. Shahnawaz & Dr. Mahender Kotha
Montagne Blanche, Mauritius, 19th September 2007
Science Pledge
By my signature below, I certify that my thesis is entirely the result of my own work. I have cited all sources I have used in my thesis and I have always indicated their origin.
(Montagne Blanche, Mauritius, 19th September 2007) (Signature)
Acknowledgements
First of all, I would like to express my eternal gratitude to the Almighty God, for His Grace, Blessing and Help, He bestowed upon me all through my lifetime and more especially during this course. Without his favors, you would surely not have read this thesis today.
My deepest gratitude goes to Dr Shahnawaz for setting up this course and making our dreams come true. Not to mention his precious advice, excellent guidance,
invaluable discussions, infinite patience and support in helping me to climb each step of the ladder all through this course.
My thanks go to all the UNIGIS crew, Dr Khota my course coordinator, all my tutors, my colleagues R. Goolamally, D. Dewan and my course mates Mr. Shiva, Mr. Jaggi and Mr.
Ramasamy, for their advices, support and help.
My special thanks goes to Mr. R. Bheeroo, Director of Reefwatch Consultancy Ltd, Mr. G. Langut, Surveyor at Ministry of Housing and Lands, and Mr. S. Ramreka, Environment Officer at the Ministry of Environment for their support, knowledge and expertise.
My heartfelt gratitude goes to my wife for her patience, support and encouragement through the hardest times. Special thanks go to my dear parents and son who have been my inspiration to undergo this course and to whom I dedicate this thesis.
For all of you, Thanks,
May God Almighty reward you with the best of rewards.
Abstract
The study of shoreline change is of great importance in coastal management for plan development and decision making. Long term shoreline analysis uses data acquired over several time periods to identify regions where the shoreline has changed. The rate of change of erosion or accretion can be calculated to forecast future shoreline position. Shoreline analysis also reveals the trends in shoreline change which gives a holistic view of the evolution of the shoreline over time which is important in making accurate prediction of the rate of change.
The coastal area of Flic en Flac village has degraded and is affected by erosion due to natural and anthropogenic processes. Arbitrary decisions and actions, without knowledge of coastal processes, taken to remedy the problem have deteriorated the beach instead of protecting it. In order to take informed and responsible decisions, it is essential to have correct information on the evolution of the shoreline.
The shorelines of four different points of time (1967, 1979, 1991 and 2003) were acquired from aerial photos and satellite imagery. The areas affected by erosion and accretion were identified using the overlay methods and the extent was also calculated. The rate of change of shorelines where unidirectional trends occurred was calculated using linear regression methods. Moreover the relationship between the changes in shoreline and land use has been investigated. A geodatabase and GIS-based methodology were developed to monitor the area affected by erosion.
The results obtained in this study show that significant changes, both in erosion and accretion, have occurred along Flic en Flac coast. The total area affected by erosion from 1967 to 2003 is 25,542m² whereas the amount of accretion is 31,955m². The study has also revealed that some areas along the shoreline have undergone a reversal trends. It is worthwhile to note the result of the land change analysis which shows that the extent under vegetation cover has decrease significantly from 92.3% in 1967 to 47.2% in 2003 whereas as the extent under development cover has increased from 1.8% to 52.8% for the same period.
Table of Contents ………... Page
Science Pledge ...i
Acknowledgements ...ii
Abstract ... iii
1 Introduction 1 1.1 Background ...1
1.2 Importance of assessing and monitoring shoreline ...3
1.3 Function of a GIS in this study ...3
1.4 Problem Statement ...4
1.5 Motivation...5
1.6 Research objectives...6
1.7 Outline of the Methodology...6
1.8 Study Area ...7
2 Literature Review ...10
2.1 Causes of Coastal Erosion ...10
2.2 Classification of Coastal types...11
2.3 Coastal erosion in Mauritius ...12
2.4 Shoreline Mapping Techniques ...13
2.5 Shoreline monitoring ...16
2.6 GIS for shoreline analysis...17
3 Shoreline analysis...18
3.1 Data Acquisition ...18
3.2 Data preparation...19
3.3 Methodology of Analysis...21
3.4 Shoreline Change Trends ...23
3.5 Rate-of-Change Calculation Methods...23
3.6 Analyzing change in Shoreline ...24
3.7 Change in Shoreline with Relation to Landuse...27
4 Monitoring 30 4.1 Data Acquisition Method...30
4.2 Creation of Geodatabase ...32
4.3 Data Analysis Methodology ...34
4.3.1 Creation of raster surface ...34
4.3.2 Analysing the Monitoring surface using Cut/Fill Operation ...35
5 Results and Discussion...37
5.1 Shoreline Change Trends ...37
5.2 Shoreline Rate of Change ...39
5.3 Analyzing Change in Shoreline ...40
5.4 Change in Shoreline with relation to Landuse ...46
6 Conclusion ...52
References ...53
List of Figures ……… Page
Figure 1 : Location of Mauritius in the Indian Ocean ...1Figure 2 : Helicopter view of a coastal area in Mauritius...2
Figure 4: Erosion affecting the coast of Flic en Flac ...4
Figure 5 : Aerial Vew of Flic en Flac Coast (Source: Google Earth)...7
Figure 6 : Location of Flic en Flac Villlage in Black River District ...7
Figure 7 : Limits of Study Area ...8
Figure 8 : A comparative shore-normal section showing relationships of the various component facies of the Fringing Reef Coast coastal type...11
Figure 9 : A schematic principle of LIDAR mapping ...15
Figure 10 : Georeferencing the 2003 image using Arcmap ...20
Figure 11 : Vectorising process of the 1967 shoreline using ArcGIS 9.0 ...22
Figure 12 : The polygon feature class of the 2003 shoreline area ...24
Figure 13 : The Overlay operation using the Union tool for two different shorelines. ...25
Figure 14 : Assigning values of change to the new feature class ...26
Figure 15 : Converting the polygon feature class into raster ...26
Figure 16 : Shoreline change map showing areas affected by erosion and accretion between 1991-2003 ...27
Figure 17 : Selecting and exporting to a new feature class...29
Figure 18 : Change in land use occurred in the study area from 1967-1979 ...29
Figure 19 : A typical cross section of beach and its nearshore bathymetry...31
Figure 20 : Position of Baselines and Transects of the monitoring area ...32
Figure 21 : The Feature classes in the Flic en Flac Geodatabase ...33
Figure 22 : Creating a raster surface using the natural neighbors interpolation ...34
Figure 23 : Map showing region affected by erosion and accretion...36
Figure 24 : Shoreline position and trends ...38
Figure 25 : Graph of Distance retreat (m) against Time period (years)...39
Figure 26 : Chart showing extent of erosion and accretion for specific time periods along the shoreline...41
Figure 27 : Shoreline Change from 1967 to 1979...42
Figure 28 : Shoreline Change from 1979 to 1991...43
Figure 29 : Shoreline Change from 1991 to 2003...44
Figure 30 : Shoreline Change from 1967 to 2003...445
Figure 31 Change in Land use cover from 1967 to 2003 ...47
Figure 32 Change in shoreline and Land use from 1967 to 1979...48
Figure 33 : Change in shoreline and Land use from 1979 to 1991...49
Figure 34 : Change in shoreline and Land use from 1991 to 2003...50
Figure 35 : Change in shoreline and Land use from 1967 to 2003...51
List of Tables .……… Page
Table 1: Statistics on number of tourists and earnings ...8Table 2 : Extent of Public Beaches at Flic en Flac ...9
Table 3: Estimated accuracy of the shorelines extracted from different sources ...16
Table 4 : Details of aerial photographs ...18
Table 5 : Data model for generating a geodatabase ...33
Table 6 : The volume and area of a region affected by erosion and accretion ...35 Table 7 : The amount change in Land Use cover for different time period in the study area .46
1 Introduction
1.1 Background
Coastal Erosion is generally regarded as a volumetric reduction of shoreland by natural and/or human induced processes. Natural processes are mainly cyclone hit, tidal waves and rising sea level whereas human induced processes can be summarized as inappropriate land use in the near shore zone, encroachment of the near shore zone, building of hard structures in the dynamic zone and destruction of marine habitat such as coral reef and sea grass. Coastal erosion, whether it is caused by natural or human-induced factors, is known to be one of the most devastating environmental problems of the coastal zone of a number of countries of the Sub-Saharan Africa, and has serious implications on the entire national economies. Mauritius is of no exception (GEF-MSP, 2002, p.10).
The Republic of Mauritius is a small island developing state (SIDS), situated at longitude 58° East and latitude 20° South in the Indian Ocean (Figure 1). It has a total surface area of 1865 km², approximately 320 km of coastline, and is almost completely surrounded by fringing coral reefs.
According to the Environment Protection Act (2002), the coastal zone is defined as any area which is situated within 1 kilometer or such any distance as may be prescribed from the high water mark extending either side into the sea or inlands. It includes the coral reef, the reef lagoons, beaches, wetland, hinterlands (inland region adjacent to the coast) and all islets within Mauritius territorial waters (Figure 2). The coastal zone links the land to the sea and supports a large number of important functions. It attracts human settlement, fishing
Figure 1 : Location of Mauritius in the Indian Ocean
activities, recreational users, hotels development, tourism and other associated activities and
contributes substantially to the island’s economy.
Figure 2 : Helicopter view of a coastal area in Mauritius
The tourism industry is an important economic pillar of Mauritius and is almost entirely coastal-based. It depends on the limited characteristic features of the island, which include its white sandy beaches and safe lagoon surrounded by coral reef of unique natural beauty. However, with the development of the tourism industry in Mauritius over the past 30 years, the preservation of the marine environment and near shore was considered secondary.
Any degradation of this marine environment will have a negative impact on the tourism industry.
The consequences of rapid development in the coastal area has resulted in the loss of beach, infrastructure and marine habitats, resulting in a potential decrease in earnings from tourism and increased pressure on the coastal zone for other accommodations. With the increasing frequency and intensity of extreme natural disaster (tsunamis, cyclones and storms), coupled with the rise in sea level and inappropriate construction of hard structures along the seafront, many beaches continue to erode, and some very popular ones in an irreversible manner (EU - Mauritius CSP, 2006).
Open Sea
Sandy Beach Lagoon
Wetlands Vegetation
Settlements Reef
1.2 Importance of assessing and monitoring shoreline
The shoreline along Flic en Flac coastal area is dynamic in nature, shifting over time in response to natural coastal processes, cyclones, and the effects of human intervention.
Changes in the position of the shoreline are affecting beaches, infrastructures, communities, and ecosystems (Baird et al, 200l).
It is imperative for planners, engineers, resource managers, property owners and other stakeholders to get correct information on the evolution of shoreline to be able to take informed and responsible decisions.
Accurate and reliable information on both current and historical shoreline trends, together with their erosion and accretion rates and predictions of future shoreline positions can help identify appropriate and inappropriate areas where coastal infrastructures can be placed .(Ali, 2002).
The study of changes in shoreline position can aid in predicting the life expectancy of coastal infrastructure by calculating rate of change of erosion. Shoreline position measurements for various time periods are used to derive quantitative estimates of the rate of shoreline change (erosion or accretion). These rates are used to further our understanding of the magnitude and timing of shoreline changes in a geological or scientific context and of the evolution of coastal environments in response to wave, current processes and change in land use. This knowledge, in turn, provides a basis for the implementation of sound coastal zone management strategies (Thieler et al. 2001).
Monitoring is conducted so as to provide accurate and adequate data for managing the shore.
The purpose of monitoring is to assist the authority in:
Illustrating more specifically, the magnitude of the shoreline loss, Identifying potential problems and priority areas for stabilization, Predicting the future trends in shoreline, and
Assisting management operation in more successful and cost effective solutions.
1.3 Function of a GIS in this study
For an effective management of the shore, it is necessary for the policies to be based on informed decision-making. This in turn requires ready access to appropriate, reliable and timely data and information in suitable form. Since much of this information and data is likely to have spatial component, a geographical information system (GIS) can be used to assess and monitor coastal erosion.
In a GIS, digital shoreline data sets can be easily stored, retrieved and analysed for
quick and informed decision-making. It also allows engineers, planners and researchers, to model alternate management scenarios and coastal behavior, before a proposed strategy is imposed on the real-world system. Coastal Terrain Model (CTM) can also be generated and spatial analysis can be performed for predicting erosion rate. Moreover there will be significant increase in the accuracy and precision of the data which will generate highly reliable and accurate information (Bhardwaj, 2003).
The ability of a GIS in analyzing and managing broad scale data sets as well as the integration of regional and local scale environmental data is central to the success of environmental monitoring programs. Although coastal erosion may possibly be assessed and monitored without a GIS, it would be difficult to adequately address the environmental issues at the appropriate breadth of scales. In short, without GIS, integrated environmental monitoring would not be possible (Hollister J.W, 2000).
1.4 Problem Statement
Flic en Flac is one of the most heavily used public beaches in Mauritius. The beach is degraded as a result of uncontrolled heavy use and is affected by erosion. The erosion problem is washing out the sandy beaches resulting in a reduction in the extent of beaches, which causes a lot of inconveniences to the public and tourists (Figure 4). “Flic en Flac has a history of intense coastal development over the last 15 years. Filling of wetlands and creation of morcellement over coastal areas, hotel development and associated activities have had their impact on the coastal system”, quote from (Baird et al, 2003, p.2-12).
The Council of Science & Industrial Research (CSIR) of South Africa carried out a study in September 1992.
It concluded that the shoreline of Mauritius mainly the coastal areas in Flic en Flac are extremely vulnerable to human related impact. Protective measures taken as well as sand quarrying activities have accelerated the erosive process. Furthermore, rapid development of housing and commerce on the coast and near the coastline does
Figure 4: Erosion affecting the coast of Flic en Flac
It has also been observed that the introduction of coastal structures such as gabion
and groins that have been put in place to halt erosion along certain specific region in Flic en Flac, have deteriorated the beach instead of protecting it (Baird et al, 2003, p2-13). This is due to lack of knowledge on coastal processes, and arbitrary decisions taken to arrest erosion.
1.5 Motivation
Base on the above problem statement, studying the historical shoreline trends and understanding the change occurred over the past few decades along Flic en Flac coast will help in identifying areas affected by erosion or accretion and predicting future shoreline position so that timely action could be initiated to halt or remedy the situation
This will also enable a proper management and strategic planning of the coastal area for wise economic development of the natural, human and material resources. Part of good planning is to understand the range of natural variability and the processes that cause change to the environment.
In order to avoid the grave consequence of the widespread loss of beaches Baird et al (2003, p.8-20) have recommended an urgent implementation of a beach monitoring program for Flic en Flac. Monitoring of shoreline will enable detection of significant change in the short time and give feedback on beach response to operations which will guide future management.
GIS will assist the Integrated Coastal Zone Management (ICZM) unit of the Ministry of Environment in Mauritius as a decision support tool for effective management, planning and monitoring of coastal erosion. It will be on a pilot basis and if successful will be implemented to other regions. The GIS will enable judicious use of resources for developmental planning The project will be beneficial for the whole country both socially and economically.
The Ministry of Environment has designated Flic en Flac as a high priority site and the Tourism Development plan for Mauritius (Deloitte and Touche, 2002 cited in Baird et al.
2003) identified it as one of the priority development areas. Flic en Flac is one of the most intensively used public beaches in Mauritius and demonstrates many problems occurring on the sandy beaches on the west coast of Mauritius and provides an excellent case study.
1.6 Research objectives
The goal of the thesis is to use GIS to assess and monitor coastal erosion at Flic en Flac.
The following are the specific objectives of the thesis:
To analyse shoreline changes for assessing its evolution.
To identify zones affected by erosion / accretion and predict future shoreline behaviour.
To identify relationship between the change in the shoreline and land use changes in the coastal area of Flic en Flac.
To develop a GIS based methodology and geodatabase for monitoring of erosion for the affected zones.
1.7 Outline of the Methodology
A shoreline change analysis of the Flic en Flac region has been carried out using aerial photographs of four different points of time at an interval of 12 years each i.e. year 1967, 1979, 1991 and 2003. The relation between land use and shoreline change has been investigated and finally a GIS methodology and geodatabase will be developed for monitoring of the affected zones.
The following methodology has been used:
1. Aerial photographs and satellite imagery were acquired from the Ministry of Housing and Lands and Google Earth respectively.
2. Ground Control Points (GCPs) were identified on the aerial photographs and their coordinates were recorded from the filed using surveying method.
3. The aerial photos and satellite imagery were georefenced and rectified using the coordinates of GCPs.
4. The shoreline on the four sets of aerial photographs was vectorized and analyzed to assess the change in the shoreline position.
5. Based on the above result, areas highly affected by erosion were identified and classified into various levels of erosion-hazard.
6. The relationships between changes in land use and changes in shoreline were analyzed by calculating the percentage change in different land use types and its spatial relationship the change in shoreline.
7. A topographic ground-survey transects at selected locations was carried out in the
areas identified in step 4.
8. A geodatabase was created and a GIS-based methodology was developed to monitor the affected areas.
1.8 Study Area
The beach of Flic en Flac constitutes the coastal area of the Flic en Flac village (Figure 5) situated in the Black River District on the West coast of Mauritius (Figure 6).
Figure 5 : Aerial Vew of Flic en Flac Coast
(Source: Google Earth) Figure 6 : Location of Flic en Flac Villlage in Black River District
Island of Mauritius
For the purpose of the thesis, only a part of the coastal zone has been considered. The
area under study is delimited by the shoreline starting at La Pirogue Hotel, Point A (982704.5mE, 988900 mN) and by the beach adjacent to Klondike Hotel, Point B (933488.3mE, 991800mN) (Figure 7).
In the 1980’s, the Government of Mauritius decided to develop tourist sector and five- star hotels where built on the coastal area of Flic en Flac village. From that time onwards, Flic en Flac village has become the second most visited tourist village of Mauritius.
The rapid development of the tourist sector entailed an increase in the arrival of tourists. Table 1 shows the number of tourists coming to the island and the earnings they generated in the year 1998 and that expected in 2007.
No. of Tourists Earnings (Mauritian Rupees)
1998 558,195 845 millions
2007(Expected) 875, 000 36,430 millions
Table 1: Statistics on number of tourists and earnings
(Source: Census 2000 & Government Information Service)
To cater for that considerable increase in tourists, the number of hotels for the whole island have increased from 90 in 1998 to 99 in 2006 (Annual Digest of Statistics, 2006).
Figure 7 : Limits of Study Area
in the study area, namely La Pirogue Hotel, Villa Caroline Hotel, Gold Beach Hotel and Pearl
Beach Hotel.
Hotels are situated along the coast of Flic en Flac and have a direct impact upon the economic and social activities of the area. Besides hotels and restaurants, a number of boat houses and individuals operate their businesses to offer water sports and recreational facilities to tourists and nationals. All these activities induce a considerable pressure on the coastal zone.
Public beaches being the places of leisure activities have high importance also for the local people where they come to relax and enjoy the free time. The public beach of Flic en Flac / Wolmar starts at the end of Pearle Beach Hotel up to the beginning of Villa Caroline Hotel and has a sea frontage of approximately 2 Km. It is under continuous stress due to high pressure exerted by the public.
Table 2 shows details of public beaches for Flic en Flac:
Name Extent (ha) Sea frontage m (Approx) Government Notice - G.N
Flic en Flac/
Wolmar
12.8 1,920 142/1984
Flic en Flac 2.1 545 206/1940
Flic en Flac 2.1 512 63/1998
P.G Anna 0.4 105 348/1991
Table 2 : Extent of Public Beaches at Flic en Flac
(Source: Annual Digest of Statistics, 2005)
The amenities provided by the public beach have a direct impact upon the environmental degradation of the beach. The amenities provided to the public include 2 toilets, 105 waste collection bins, 14 benches, 4 kiosks, 3 parking areas, 2 dangerous bathing signposts and 5 indicative panels. (Annual Digest of Statistics 2006).
The climate on the west coast is relatively dry. It can get very hot in summer (average of 32°C and 23°C in winter). It is therefore a pleasant region all year round, especially during the windy month of June to August.
2 Literature Review
A shoreline is defined as the line of contact between land and a water body and is difficult to map since the water level is always changing, quote from (Li et al, 2001).
Shoreline position reflects the coastal sediment budget, and changes may indicate natural or human-induced effects along shore. Coastal shorelines worldwide are changing rapidly as a result of natural physical processes (sediment supply, wave energy, and sea level). Human activities act as catalysts in causing disequilibrium conditions that accelerate changes. The interactive forces, geological and hydrodynamics processes and climate condition causes changes of coastline situation and create transgression and regression coastlines. (Choopani et al. 2005)
2.1 Causes of Coastal Erosion
Several studies (Mahood & Padwa, 1997, Kairu and Nyandwi, 2000 and Baird et al, 2003) have investigated shoreline change and found it a good indicator for assessing the occurrence of coastal erosion. Coastal erosion is generally related to wave energy, shoreline material, coastal topography, and the direction of the approaching waves with respect to the shoreline direction (Ali, 2002). The factors influencing the shoreline position are both natural and human induced which include change in sea level, change in the rate of sediment supply, effects of wind-waves and tides as well as a range of human interventions.
Wind, waves, and long-shore currents are the driving forces behind coastal erosion.
Waves lose energy when they come closer to shore, hit the ocean bottom and then reach the beach. The removal and deposition of sand permanently changes beach shape and structure.
The sand can be moved to another beach, to the deeper ocean bottom, into an ocean trench or onto the land side of a dune. The breaking waves and currents in the near-shore zone are mainly responsible for the transport of shoreline sediments resulting in shoreline change. The construction of sea walls, jetties and groynes may exacerbate erosion of adjacent beach since they may interfere with the longshore drift processes hence modifying the sediment budget.
Coastal shorelines differ obviously in physical characteristics and in vulnerability to erosion. Erosion rate over time at a given point along the shoreline depends on factors such as: direction of littoral drift, inlet dynamics, sand supply, short- and long-term climate fluctuations, gradient of submerged ocean or Lake Bottom, relative mean sea level and human actions affecting shoreline processes. (Mahood and Padwa, 1997)
2.2 Classification of Coastal types
In his paper entitled “Guidelines for studies of physical shoreline change in the western Indian Ocean region” (Kairu and Nyandwi, 2000), elaborated on the classification of coastal types in the western Indian Ocean region. Different coastal types are due to the result of significant difference of several factors like coastal geology, sediment supply, climate, ocean temperature and turbidity, in the coastal ecosystem and affect the shoreline in different ways, rates and with different socio economic consequences. Before undertaking any type of analysis, it is fundamental to classify the coastal type to which it belongs.
Kairu and Nyandwi, (2000) have classified the coast of the western Indian Ocean region into five primary coastal types and their component facies in relation to their resource implications and susceptibility to physical change. The five coastal types are: exposed low- lying sandy coasts, exposed rocky coasts, fringing reef coasts, patch reef coasts and inlets, estuaries and creeks associated with primary coastal types. Most of the coast around Mauritius including Flic en Flac, is of fringing reef coasts type (Figure 8). The component facies of a fringing reef coast are; Fore reef and reef apron, Reef bar, Lagoon, beach rocks, Sand beaches, Sand dunes, Beach plains, Rock cliffs, Hinterland, and Reef limestone terraces.
(Source: Kairu and Nyandwi, 2000)
(Baird et al, 2003, p.2-2) has classified the coastline of Mauritius into different shore /types namely Sandy, Rocky, Muddy, Mixed, Cliffs, Wetlands and Calcareous limestone shores which are directly linked with the coastal geomorphologic features of the site.
Flic en Flac has a sandy shore which is composed essentially of sediments of carbonate origin and form part of the living reef-lagoon-beach system which consists of four
Figure 8 : A comparative shore-normal section showing relationships of the various component facies of the Fringing Reef Coast coastal type
main parts namely, Reef (front and flat), lagoon, Active beach and Coastal dune and
vegetation.
Reef front and wide shallow reef flat provide the primary protection from the severe waves and reduce the wave height by 90%. The lagoon corals and associated biological community supply almost all of the sand that makes up the beaches inshore of the reef systems. It also act to further dissipate wave energy before it reaches the beach. The beaches of the reef-lagoon-beach system play a vital role in dissipating wave energy that is able to cross the reef, thus protecting the shore. Sand dunes store excess beach sand and serve as natural erosion buffers, protecting coastal properties during storms. The active beach together with the coastal dune and vegetation comprise the dynamic beach zone and any degradation of any part of the system will disrupt a fine balance and lead to the onset of irreversible erosion along the beach. Healthy dunes that are vegetated by native vegetation, salt-tolerant and having dense root systems are effective at trapping wind-blown sand.
2.3 Coastal erosion in Mauritius
The coastline of Mauritius is about 322 km long with a lagoon area of 243 km² surrounding and is highly vulnerable to the threat of natural and environmental events like cyclones, tsunamis, droughts, floods and diseases. With the increasing frequency and intensity of such events, coupled with the rise in sea level and inappropriate construction of hard structures along the seafront, many beaches continue to erode, and some very popular ones in an irreversible manner. To better comprehend the problem, the Ministry of Environment in Mauritius, commissioned a study on Coastal Erosion (Baird et al, 2003), and most of the recommendations which in fact necessitate thorough scientific investigations, are pending implementation. (EU - Mauritius CSP, 2006)
Natural and reversible process erosion has been observed along the sandy shores of Mauritius. During larger waves and higher water levels combine to erode the upper part of the beach resulting in either a scarp with sand transported offshore a short distance to the toe of the beach and/or overtopping of the beach and onshore transport of sand and coral rubble.
Healthy beaches recover fully from this process known as reversible erosion, through a combination of wind and wave forces in the hours, weeks and months following the cyclones.
When the system is disrupted or degraded, long-term and irreversible erosion takes place, leading to the permanent disappearance of beaches. There are initial and alarming indications supported by hard evidence that irreversible erosion is occurring and has the potential to become widespread along the sandy beaches of Mauritius (Baird et al. 2003).
The audit report has stressed upon the causes and consequences of coastal erosion,
which is one of the main acute problems Mauritius is facing. During the past decades, human related activities have mainly contributed to the coastal problems.
The Council of Science & Industrial Research of South Africa (CSIR, 1992), carried out an investigation of beach erosion in Mauritius. It concluded that the shoreline of Mauritius is extremely vulnerable to human related impact. Protective measures taken as well as sand quarrying activities have accelerated the erosive process. It has also highlighted the effect of rapid development of housing and commerce on the coast and near the coastline does not conform to planning guidance particularly coastal areas of Flic en Flac and the Northern Tourist Zone. The effects of the above factors include:
Beach erosion and restricted public access to the beach Pollution of coastal waters with sewage and solid wastes
Threat to the tourism industry as the coastal zone is a major attraction for the tourists Degradation of biodiversity, especially coral eco-systems that require nutrient poor water to flourish.
2.4 Shoreline Mapping Techniques
Shoreline mapping issues such as mapping methods used to acquire shoreline data, models used to represent shorelines in the geographic database, and shoreline-change analysis methods have to be taken into consideration. By knowing the data acquisition method, the inherent errors that normally exist in the underlying measurement processes can be identified and modelled. Manual extraction of shoreline features is a process that involves digitizing the borderline between water and land. The automatic shoreline extraction process involves the classification of the gray values in the processed aerial photographs to obtain the borderline between land and water (Ali, 2002).
A lot of mapping techniques have been developed to capture the shoreline over time (Thieler et al, 2001, Elkoushy and Tolba, 2002, Niu et al, 2004, Di et al, 2003).They are basically ground survey, aerial photographs, satellite imagery, airborne LIDAR, wireless mobile GIS and so on.
Satellite / aerial imagery play an important role in mapping and analyzing the change in shoreline. A study carried by (Elkoushy and Tolba, 2002) has shown the effectiveness of aerial imagery as a tool to extract shoreline information to understand what is happening in the shoreline and to predict future events. It has also investigated on the usefulness of aerial photography in investigating shoreline change with high accuracy. Aerial photographs and
satellite images give an overview of much wider areas in a shorter period of time than the
generally used methods of field surveying or GPS. Aerial photograph can provide two or three dimensional measurements but needs to be geocoding and orthorectified before mapping the shoreline. This is necessary to introduce geographic coordinates using ground control points and compensate for image geometric distortions due to various causes such as tilt and noise. The shoreline extracted from aerial photos can easily be integrated into a GIS where spatio-temporal changes in the shoreline can be analysed which can help in predicting the future shoreline changes. Aerial images could be a faster and more efficient monitoring system with high accuracy when using all available techniques for tracing the shoreline such as least squares matching, coordinates transformation, minimum GPS control points and GIS.
According to (Li et al. 2001) analytical photogrammetry has always been the principal acquisition method for shoreline mapping and this is due to its reasonable cost and high accuracy. However the temporal resolution has always been an issue for shoreline change monitoring. With the advances in data acquisition techniques such as digital photogrammetry sensors, Global Positioning Systems (GPS), and other all-weather sensors, a lot of work has been done to examine the potential, efficiency and economic costs of shoreline mapping methods.
Recently, satellite-imaging systems have increasingly improved image resolution including the new generation of the high-resolution satellite imagery such as IKONOS I, which has a resolution of 1-meter with stereo imaging capability. An investigation of shoreline mapping using high-resolution satellite images demonstrated a promising mapping accuracy of 2-meters and a great reduction in the number of the required ground control points (Li et al. 2001).
New methods of shoreline mapping have been developed since the availability of high resolution satellite imagery. Di et al. (2003) investigated upon a new method of automatic shoreline extraction using high resolution IKONOS imagery. The image was segmented using the mean shift segmentation and the major water body is identified for shoreline generation. An accuracy of 1-2 m was achieved from the 1m-resolution IKONOS Geo stereo images, which is comparable to the accuracy of expensive Precision Stereo Imagery. The process is not fully automatic but needs human intervention. The method also uses ground control points for improvement in accuracy.
With the application of latest technology in GPS field and in order to increase efficiency and to reduce operation cost, Niu et al, (2004) has developed and applied a wireless mobile GIS for on site decision making. The latest advantage is no doubt the
accessibility of spatial data over the web and the prevalence of web-based GIS. Based on
historic shorelines, future shorelines are predicted and published in the shoreline erosion awareness subsystem using a shoreline prediction model.
Shoreline mapping techniques have developed from conventional field survey methods through expensive, airborne coastal mapping techniques to new automatic or semi- automatic processes. Some of the new techniques such as image processing for the automatic extraction of shoreline features, land vehicle-based mobile mapping technology and Light Detection and Ranging (LIDAR) for water depth data acquisition have been applied to shoreline mapping (Di et al. 2003).
Shoreline mapping based from Air Borne LIDAR is an efficient and cost effective method of acquiring shoreline data. Mapping using LIDAR technology rely on the accurate round trip travel time of a laser pulse transmitted from the LIDAR system to a surface target (Figure 9). It can generate high quality Coastal Terrain Model (CTM). Shoreline can be extracted from the CTM by intersecting it with the level of water at any specific time.
Woolard et al, (2003) has used LIDAR technology for the shoreline mapping of the Shilshole Bay. Multiple LIDAR datasets from different sensors were acquired over a two year period and have been combined with a recent GPS ground survey to establish ellipsoidal – tidal relationships for the auto-extracting of the Mean High Water (MHW) shoreline.
Figure 9 : A schematic principle of LIDAR mapping
(Source: Tinker, 2007)
All the various shoreline mapping techniques described above have their own
advantages and limitations. The major factors that are taken into account in choosing a particular technique are accuracy, cost and temporal resolution which are all interrelated. A comparative study of shoreline mapping techniques was undertaken by Li et al. (2001) where different mapping techniques have been described and analyzed. The objective of his study was to investigate upon the possibility of using remote sensing imagery for shoreline mapping so as to reduce the costs and improve mapping efficiency and accuracy. Three shorelines are generated using three different techniques namely digitizing from aerial orthophotos, intersection of a coastal terrain model (CTM) with digital surface and extraction of shoreline from stereo IKONOS image. The shoreline extracted from the tide-coordinated aerial photos was used as the reference shoreline since it has a high accuracy and other shorelines were compared to it. The accuracies of the shoreline were estimated and the potential of these techniques were analyzed by comparing with shorelines extracted from topological maps and nautical charts. Table 3 below shows the estimated accuracy of the shorelines extracted from different sources.
SHORELINE ESTIMATED STANDARD DEVIATION
Orthophoto 2.6 meters
IKONOS 1-meter simulated image 2-4 meters
CTM and water level 2-13 m depending on CTM quality
ODNR map 6m (1: 12,000)
IKONOS 4-meter image 8.5 meters
USGS DLG 12m (1: 24,000)
T-Sheet 2.5-20m depending on scale
Table 3: Estimated accuracy of the shorelines extracted from different sources
(Source: Li et al, 2001)
Ali (2002) studies the relationship between shoreline-change and shoreline-curvature based on a new concept called shoreline-segment orientation. It has been found that there exist strong correlations between the average shoreline-changes with local shoreline- curvature. That is the concave shoreline-segments experience more erosion than convex and straight segments.
2.5 Shoreline monitoring
Monitoring of coastal change has until recently been 2-D, focusing on shoreline evolution that could be extracted from aerial photography supported by a limited set of shore
coastal changes caused by natural processes or human intervention. Identification of
protective beach dune loss, assessment of moved sand volumes, or evolution of nourished beaches are changes that can influence the design of large coastal management projects.
Accurate data and a better understanding of coastal topographic change can significantly improve the success rate of such coastal engineering projects (Mitasova et al. 2006)
Monitoring coastal erosion effectively requires data on the initial character of the beach, changes over a range of timescales and the factors which cause change.The data collected will be an integral component for analyzing erosion trends and rates, more effectively than simple observations and photo-documentation alone (Harvey, 2003). Baird et al, (2003) and Harvey (2003) had investigated and elaborate on the different techniques and methods for monitoring shoreline change.
2.6 GIS for shoreline analysis
Determining the accurate length of the shoreline is important for coastal zone management applications such as shoreline classification, monitoring erosion, mapping biological resources, habitat assessment and for the planning and response to nature and man made disasters. Coastal zone management, by definition, is a type of spatial management.
Geo-referenced spatial data is map data in a digital form which mean that each of the earth’s features that are stored as spatial data has a unique geographic reference such as latitude and longitude. The increasing use of spatial data and GIS (Geographic Information System) by organizations and researchers is a valuable tool to help solve the planning and management issues in the coastal zone.
Advanced 3-D GIS tools substantially increase efficiency in data processing and provide the capabilities to gain new insights into geospatial aspects of complex coastal systems. GIS is becoming an important tool in several areas of coastal research and management, such as monitoring, analysis and risk assessment, prediction of impacts using modeling and simulations, as well as in planning and decision support (Mitasova et al. 2006).
There are many different Geographic Information Systems in use today and they tend to differ in certain aspects such as linking attribute with geographic data, accuracy, type of analysis and visualization. There are several GIS programs such as Digital Shoreline Analysis System (DSAS) or the Shoreline Shape and Projection Program, which have been specially developed for shoreline analysis. (Hollister, 2000)
3 Shoreline analysis
3.1 Data Acquisition
Since imagery from IKONOS or LIDAR has not yet been covered for Mauritius, aerial photographs have been used in this study as it is only data available at a quite good spatial and temporal resolution ( 3 different points of time) for performing shoreline analysis.
It is available for almost all the coastal area of Mauritius and the shoreline can be extracted effectively and accurately.
The aerial photographs have been acquired from the Ministry of Housing and Lands of Mauritius (Table 4). The latest series of photo available for Flic en Flac region has been covered in 1991; hence 2003 satellite imagery from Google Earth has been used as the most recent image in this study. Since the aerial photos are available in hard copy, it has been scanned into high resolution raster images at 1200 dpi.
Year of Series
Photo acquired by
Date Taken Scale Size Flying
Height (m) 1967 British Royal
Air Force
02 Oct 1967 1/10000 24cm x 24cm 1800 1979 National
Geographical Institute of France ( IGN)
05Dec 1979 1/10000 24cm x 24cm 1905
1991 National Geographical Institute of France ( IGN)
24 Sep 1991 1/20,000 24cm x 24cm 3500
2003 Google Earth 2003/2004 1/1000 Seamless N/A
Table 4 : Details of aerial photographs
Ground control points (GCPs) are used for georeferencing and rectification of aerial photos. For the purpose of this study, the geographic coordinates of the ground control points have been recorded by traditional surveying methods using total station by establishing traverse between two known points using the nearest Tertiary Trigonometric Point (TTP) and GPS. In order to use a minimum amount of GCPs, 8 distinct and identical points which are present in all the three sets of aerial photos and the satellite image from Google Earth have been identified.
3.2 Data preparation
Aerial photographs are characterized by distortion caused by tilt of aircraft, camera lens and relief displacement. One important characteristic of aerial photographs is that distortion increase as the farther a point is from the centre of the image. The distortion needs to be corrected through selecting sufficient number of ground control points with correct coordinates usually from maps, geodetic survey or GPS points, which can be accurately localized in the aerial photos. In order to be able to use the aerial photos in a GIS, it is fundamental to georeference and rectify the images before they are used for further analysis.
The georeferencing and image rectification have been performed using ESRI ArcGIS 9.0 software for the purpose of this thesis.
Retification / Rubbersheeting correct the distortion/ flaws of the aerial photos through the geometric adjustment of coordinates. The images are being rectified using the natural neighbour rubbersheeting methods from the spatial Adjustment tool using ArcMap.
Georeferencing raster data, allows it to be viewed, queried, and analyzed with other geographic data. Thus, in order to use the 4 sets of images to investigate the changes in shoreline for given time periods, the scanned photo need to be in conjunction with other spatial data and need to be georeferenced to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface (Figure 10).
The 3 sets of aerial photographs and the google image were georeferenced using an orthomorphic projection with a relatively low RMS and the resampling algorithm used was the bilinear interpolation. The Lambert Conical Orthomorphic projection has been used in this study because it is the sole adopted national coordinate system for the whole island. The projection details used in this study are shown in the table below;
Figure 10 : Georeferencing the 2003 image using Arcmap Projection Type: Lambert Conical Orthomorphic
Spheroid Name: Clark 1880
Datum Name: WGS 84
Longitude of Central Meridian: 57d31'18.58" E Latitude of Origin of Projection: 20d11'42.25" S False Easting at Central Meridian: 1,000,000 meters False Northing at Origin: 1,000,000 meters
Unit of Measurement Meter
3.3 Methodology of Analysis
In this study, shoreline analysis is being performed so as to;
1. Examine the change and trends in the shoreline along the coast of Flic en Flac from 1967 to 2003.
2. Calculate the rate of shoreline change.
3. Identify region where change (erosion / accretion) has occurred along the shoreline.
4. Investigate the relation between the change in shoreline and land use.
After the geo-referencing and rectification processes of each set of image as elaborated in chapter 3, the new images of the Flic en Flac coastal area are permanently being transformed into new datasets using the rectify command from the Georeference toolbar of ESRI ArcGis 9.0 software.
The shoreline from each set of photo is vectorized on screen for further analysis. Four different shapefiles (.shp) of polyline feature type are created for the raster datasets of 1967, 1979, 1991 and 2003. The vectorization of the shape of the shoreline recognized in the photos relies on a careful set of boundary demarcation decisions and visual interpretation.
According to Thieler et al. (2001), there are several options/methods for delineating shoreline from aerial photographs namely, local wet/dry line, high-tide wrack line, vegetation line, algal line and seawall interface. Previous studies (Thieler et al. 2001, Baird et al. 2003 ) have suggested that the wet/dry line method which indicates the tonal change between wet and dry beach material (sand, gravel, cobble), is a relatively stable feature with respect to its horizontal – seaward – movement during a falling tide. Hence the wet/dry line method has been used to vectorize the shoreline using the raster images of the four different time periods (Figure 11).
Vectorising shoreline is a very delicate job since a wrong interpretation of the shoreline can result into misleading information about the evolution of the shoreline during the specific period. In order to increase the accuracy of the shoreline position, the interpretation and vectorization of the shorelines have been done under the supervision of a marine scientist who has a lot of experience on coastal erosion of the study area.
Figure 11 : Vectorising process of the 1967 shoreline using ArcGIS 9.0
According to Thieler et al. (2001), there will always be gross and sometimes systematic errors, in a large data set. In the present case, a gross error could include a misidentification of the shoreline or a poor resolution of photograph. A systematic error would involve an offset in the shoreline such as occurs with mismatched datums (e.g., an entire shoreline might be shifted if an incorrect datum was used to digitize the map).
In order to identify gross errors in the data, the shorelines must meet certain criteria:
1. There must be an immobile point of reference, e.g. bedrock outcrops, groins, and jetties, for this study the roof outline of buildings near the shore has been taken into consideration.
2. The reference (2003) shoreline and the tested (historical) shoreline must disagree at the reference object by a minimum distance that is taken as the diameter of an "error ellipse."
The error ellipse (E) can be calculated as follows:
E = E ref + E test
Where E ref and E test are the maximum position errors for the reference (2003) and test shorelines, respectively. For this study, the size of the error ellipse has been computed as 5 meters. Consequently, there is an error ellipse around any given shoreline point (e.g., at a transect location) that is 5 m in diameter. For example, if a feature shown on the 1979 shoreline is offset by >5 m from the 2003 shoreline position, it is likely to be in error, but anything less than 5 m is essentially undetectable since it falls within the error ellipse.
3.4 Shoreline Change Trends
Shorelines are constantly moving in response to winds, waves, tides, sediment supply, rise in sea level, and human activities. These processes change the position of the shoreline over a variety of time scales, from the daily and seasonal interaction of winds and waves, to changes in sea level over thousands of years. Shoreline changes are not constant through time and frequently reverse in sign, i.e. accretion to erosion, and vice versa. Most shorelines undergo patterns of erosion and accretion on a daily and seasonal basis (Thieler et al. 2001).
Understanding the shoreline change trends is important in making good prediction of the rate of change of shoreline. Short-term shoreline data is being analyzed in order to determine whether the long- or short-term shoreline change rate is the more appropriate statistic to use in evaluating and managing shoreline dynamics. According to (Thieler et al.
2001) there are basically 3 types of shoreline trends namely,
• Unidirectional long-term shoreline change trends;
• Shoreline change trend reversals; and
• Human-induced shoreline alterations and influences on data interpretation.
Unidirectional Long-Term Shoreline Change Trends indicate a continuous change erosion/accretion in the shoreline movement because the area exhibits a unidirectional linear trend in shoreline movement. Calculating the long-term shoreline change rate is appropriate and can be used to extrapolate future shoreline positions.
Shoreline change trend reversals indicate that a shoreline has undergone both erosion and accretion on a long-term basis. If such is the case then calculating long term shoreline change rate will lead to unreliable results in predicting shoreline position since the shoreline has undergone significant short term (erosion/accretion) trends reversal in between.
Human interference with coastal processes and sediment supply can cause shoreline trend reversal. Interfering with shoreline sediment sources and transport patterns can significantly impact the trend of shoreline movement.
3.5 Rate-of-Change Calculation Methods
In order to measure changes in the position of the shoreline using four different time series raster datasets, a transect normal to the baseline (inland line which is parallel to the shoreline) has to be established. The rate of shoreline change is based on measuring the movement of shoreline over a specific time period by calculating the distance between each shoreline position along the transect.
Various methods of determining shoreline rates-of-change have been described
(Thieler et al, 2001). All methods used for calculating shoreline rates-of-change involve measuring the differences between shoreline positions through time. Rates of shoreline change are expressed in terms of distance of change per year. Negative values indicate erosion (landward movement of the shoreline); positive values indicate accretion (seaward movement of the shoreline). These methods are End Point Rate, Average of Rates, Linear Regression, Jackknife, and Average of Eras Rates. Each method has there own advantages and disadvantages.
The linear regression method has been used as the long-term rate-of-change statistic in this study. The rate (the slope of the line) is calculated by fitting a least squares regression line to all shoreline points for a particular transect. This computational method uses all the data in spite of changes in the trend that may occur and is easy to adapt.
3.6 Analyzing change in Shoreline
The method developed to identify and measure regions affected by either erosion or accretion in the study area, is a vector base polygon overlay analysis. It can be overlaid and analyzed in basically any GIS system but for the purpose of this thesis ESRI ArcGIS 9.0 is used for the analysis. The overlay operation is a simple, practical and easy to perform.
Since GIS need polygon (closed chain of arcs) feature class to represent an area, the 4 shorelines which have been vectorised from the aerial photos of the year 1967, 1979, 1991 and satellite imagery 2003, have to be converted into polygon feature class. This is done by vectorising the shoreline and the boundary of the study area as a whole polygon (Figure 12).
Shoreline Study area
boundary
Two polygon feature classes of shoreline area for different time period are overlaid
using the UNION command (Figure 13). The overlay operation merges spatial features on separate data layers to create a new feature class. The Union tool computes a geometric intersection for the two different polygon features, which are the shoreline coverage of two different years. The result of the overlay operation resulted in new polygon feature class showing three distinct categories along the shoreline namely erosion, accretion and no change.
Figure 13 : The Overlay operation using the Union tool for two different shorelines.
A new field is added to the resulting feature class so as to easily identify the extent and location of the change occurred from the result of the overlay operation (Figure 14). The following values are assigned in the attribute table;
0 – No Change 1 – Erosion 2 – Accretion
Figure 14 : Assigning values of change to the new feature class
The resulting feature class is converted into a raster format where the output cell size is set to 1 and the field to Change value (Figure 15). The new raster image shows the region where change (accretion and erosion) has occurred along shoreline for different time period.
Since the pixel size has been set to 1m, the extent covered by each category can easily be obtained from the attribute table itself as one count represents 1 m².
Figure 15 : Converting the polygon feature class into raster
Finally, the color and text of the three categories (No change, Erosion and Accretion) are being edited for better visualization of the shoreline change map (Figure 16).
Figure 16 : Shoreline change map showing areas affected by erosion and accretion between 1991-2003
3.7 Change in Shoreline with Relation to Landuse.
Initially it was suggested to digitize land use map for the four time series so as to obtain the change in land use for the study area. But after proper consideration, it is found that there is hardly, no previous land use map for the particular area. The only land use map that is available in the Outline Scheme Development Plan (2003) from the planning department, which is district wise. Moreover digitization of the existing land use map will lead to a lack in the level of accuracy.
Consequently, the Land Use data are vectorised using all the 4 points of time raster datasets so as to have a more precise extent of the land use boundary. The land use cover type of the study area can be classified into several categories (Sandy beach, Public Beach, Rock patches, forest, grazing, Sugar cultivation, vegetation, bare land, hotels, built out, Rivers, wetlands etc). For the purpose of the analysis the land use cover type has been divided into three main categories namely:
VEGETATION DEVELOPMENT WETLANDS
The boundaries delineating the cover types are vectorised and attributes are assigned to each polygon. Once the categories were digitised, the result is being analyzed using different analysis tools from Arcmap.
The formation of sliver polygons while using overlay analysis is caused mainly due to
existence of gap between two adjacent boundaries during the vectorising process. In order to avoid such problem, a simple technique is used to correctly calculate the location and extent of the different land use cover types.
First, WETLAND and DEVELOPMENT land use cover are initially digitized and overlaid with the whole study area using the UNION tool. Since the Land use cover type has been grouped into three main categories, the resulting feature class shows the region covered by all the three land use cover types of the study area.
The VEGETATION cover type is then extracted from the attribute table and exported to a new vegetation polygon feature class.
To perform the land use change analysis for the four time series, the following process is carried out;
All the three land use Land cover types feature classes are merged into a single one using the UNION command for each time period. The UNION operation has to be carried twice since it can process two feature classes at a time. A new field is added in the attribute table of the merged feature class and each polygon is reclassified into their respective cover types.
Two polygon feature classes representing the 3 land use cover types of the study area, for two different points of time which have been obtained from the above procedure are then overlaid using the UNION operation so as to get the specific location and extent where change has occurred in the land use. Each change in the cover type (e.g Vegetation to Development from 1967-1979) are being selected from the attribute table of the resulting union operation and is exported to a new feature class (Figure 17).
Figure 17 : Selecting and exporting to a new feature class
Subsequently new group layers representing change in Land Use for different time period (1967-1979, 1979-1991 and 1991-2003) which are of 12 years interval are created (Figure 18).The feature class of the change in land use is viewed and analyzed along with the result of the section 4.3 showing area affected along the coast to have a better idea of the change occurred in the study area and its relation to the change in the shoreline for the three different time periods. The change in land use for the time period 1967-2003 has also been carried out so as to see the overall change in land use cover for the whole period.
Figure 18 : Change in land use occurred in the study area from 1967-1979
4 Monitoring
The primary objective in monitoring procedures is to record what aspects of the coast are changing, and where and why these changes are taking place. Monitoring at its simplest involves recording what is present at one baseline instance in time, and then comparing this pattern with that of preceding or subsequent stages (Bhardwaj, 2003).
One of the objectives of the thesis is to develop a GIS based methodology and geodatabase for monitoring of erosion of the affected areas. It is also to outline an effective, easily followed, and consistent method for long term monitoring of coastal erosion at Flic en Flac.
Base on the result of the shoreline analysis of the previous chapter, the major affected area by erosion has been identified which start from the public beach adjacent to Pearle Beach Hotel up to area adjacent to the end of the cemetery. Hence this area has been selected for monitoring.
4.1 Data Acquisition Method
For a successful monitoring program, it is important to record the appropriate features which will give a good idea about the evolution of the beach. According to Baird et al.
(2003), the distance and elevation of the following features (depending on presence at site) have to be measured for each transect:
Representative intermediate points between control point and edge of shore vegetation or beach
Dune (shoreside toe of slope, crest, seaside toe of slope) Seaside edge of vegetation line
Landward limit of wave borne flotsam ( highest high water mark) Structure if any (include top of structure, toe of structure at beach level) Back of beach berm (top of scarp and bottom of scarp)
Normal high water mark
Water’s edge at time of survey (record date and time) Normal low water
Limit of sand if hard bottom encountered Extend survey into water.
Generally for lagoon-reef beaches, the initial profile should extend 50 to 100 m
perpendicular to shore. Subsequent surveys should extend 25 to 50 m offshore (or approximately to limit of active sand movement). The spacing of points will depend on the site conditions, but typically will be every 5 m (Figure 19).
For this study, the length of the profile/ transect is set to 100m and of 25 m interval.
Figure 19 : A typical cross section of beach and its nearshore bathymetry
Initially baselines have to be established well back from the shoreline, beyond action of cyclones from which future change will be compared. The baseline has to be on the upland side of all historic shorelines to provide a good origin point for all transects which will extend perpendicular to shoreline orientation (Figure 19). The location of the baseline starting from Point A up to point D has been established so as to be parallel from the shoreline. It has to be physically marked for control point and location tied and recorded to three nearby reference points. The control points are to be referenced to the Mauritius National Grid (horizontal and vertical control) which is the only adopted coordinate system used in Mauritius.
Secondly, transects 25m apart have been established starting at point A and has to be perpendicular to the baseline (Figure 20). The features (described above) defined by Baird et al. (2003) have to be surveyed along each transect using conventional surveying techniques.
The surveys can be conducted in two ways either using a total station or a theodolite.
Subsequent surveys are to be undertaken annually or as soon as possible following significant cyclones (before beach recovery occurs).
Figure 20 : Position of Baselines and Transects of the monitoring area
4.2 Creation of Geodatabase
A geodatabase is a database that stores geographic data. It offers many advantages for GIS users. The range of functionality available is extensive and includes centralized data storage, support for advanced feature geometry, and more accurate data entry and editing through the use of subtypes, attribute domains, and validation rules.
The Data to be store in the database will be;
The location and elevation points along each transect available in CAD format.
The location of the baseline, transects, coastal road, and features such as Lime kiln and Toilet on the beach.
The Create New and Import methods will be used for this study.
The Flic en Flac geodatabase will consist of the following feature classes (Figure 21):
Spot height Baseline Transect Structures Road
