Modelling Coastal Erosion - Εθνικόν και Καποδιστριακόν ......significant...

42
Modelling Coastal Erosion By Vasilis KOTINAS, Niki EVELPIDOU, Anna KARKANI, Miltiadis POLIDOROU

Transcript of Modelling Coastal Erosion - Εθνικόν και Καποδιστριακόν ......significant...

  • Modelling Coastal Erosion

    By Vasilis KOTINAS, Niki EVELPIDOU, Anna KARKANI, Miltiadis POLIDOROU

  • Contents Introduction .................................................................................................................... 3

    Estimating Coastal erosion ............................................................................................ 4

    Coastal Vulnerability Index (CVI)............................................................................. 6

    Original Index (Gornitz et al, 1990) ...................................................................... 7

    Modified Index (Gornitz et al,1994) ...................................................................... 8

    Modified Index (Thieler and Hammar-Klose,1999) ............................................ 10

    Application of CVI ...................................................................................................... 11

    Study case area ......................................................................................................... 11

    Software Used .......................................................................................................... 12

    ARCGIS ............................................................................................................... 12

    DSAS 4.3 ............................................................................................................. 17

    Methodology ............................................................................................................ 18

    Calculating CVI ....................................................................................................... 19

    Loading Data ........................................................................................................ 19

    Slope Calculation ................................................................................................. 20

    Geomorphology ................................................................................................... 27

    Relative Sea Level Change .................................................................................. 28

    Mean Tidal Range ................................................................................................ 28

    Mean Wave height ............................................................................................... 28

    Shoreline Erosion/Accretion ................................................................................ 29

    Final map ............................................................................................................. 37

    Printing the Map. ................................................................................................. 38

    References .................................................................................................................... 40

  • Introduction

    The natural environment is very important for all human societies. Environmental management is critical for the well being, the economics and social systems of entire countries. Around 41% of Europe’s population live near the coast (Collet & Engelbert, 2013). Due to unsustainable use of coastal resources significant problems are experienced in these areas.

    Erosion is the gradual physical wearing of surface materials, either by water or wind. Along the coastline currents, wave action and tides are the most significant factors driving erosion. There is a delicate balance between the forces that erode the beach by carrying away the sand and the forces that tend to deposit sand onto the beach from other areas, a process known as accretion (Caldwell, 1949).

    Except from the normal factors, climate change during the last decades could cause significant changes in coastal areas, mainly due to sea level rise. The coastline is among the first systems to experience the effects of sea level rise caused by global warming. Coastal environments are in a dynamic relationship with the sea, with their sediments constantly shifting, creating new shorelines or eroding others. Sea level rise exacerbates erosion, and human activities, such as construction of buildings, roads, and seawalls, block the natural landward migration of marshes and dunes. As a result, shorelines erode, increasing the threat to coastal development and infrastructure (Briguglio, 2004). Continued sea level rise, as predicted by the Intergovernmental Panel on Climate Change (IPCC), will only exacerbate these problems.

    Islands are most sensitive to global climate change and sea level rise (Field et al., 2001). Because of their topography, islands and low-lying coastal areas are the most vulnerable to sea level rise. Smaller islands are particularly vulnerable to the effects of global warming, including sea level rise, because of their size, insularity, and susceptibility to natural disasters (Briguglio, 2004).

    Determining the physical response of the coastline to sea-level rise is one of the most important problems in coastal geology today, and the ability to predict shoreline retreat and land loss rates is critical to planning coastal zone management strategies.

    Recent estimates of future sea-level rise based on climate model output (IPCC,2013) suggest an increase of the rate of sea level rise (in comparison with that observed between 1971 and 2010). Various scenarios (Fig. 1) exist and all of them show an increase of Sea level (up to 1 meters until 2100). This rate is more than double the rate of eustatic rise for the past century (Douglas, 1997; Peltier & Jiang, 1997), and as a result, sea-level rise will have a large impact on coastal evolution in the future.

    Zhang et al. (1997) suggested that increased frequency or intensity of storm surges in the U.S.A was caused by sea-level rise in the last 80 years. Because of this, it is likely that historical record of sea-level change can be combined with other variables (elevation, geomorphology, wave characteristics, etc) to assess the relative coastal vulnerability to future sea-level change (Hammar-Klose & Thieler, 2001).

  • The prediction of future coastal evolution is not straightforward. There is no standard methodology, and even the data required to make such predictions are the subject of scientific debate. Although a quantitative predictive approach is not available, the relative vulnerability of different coastal environments to sea-level rise may be quantified at a regional to national scale using basic information such as:

    • coastal geomorphology

    • rate of sea-level rise

    • past shoreline evolution

    • other factors.

    This approach combines the susceptibility of the system to change with its natural ability to adapt to changing environmental conditions, and as a result the system's natural vulnerability to the effects of sea-level rise can be estimated (Klein & Nicholls, 1999).

    Estimating Coastal erosion

    To estimate coastal vulnerability to erosion, during the years a lot of methods have been used. In summary these methods take into account each parameter in relation with future climate change, and how this change will affect sea level.

    The most important methods are:

    Fig. 1: Global Mean sea level rise (IPCC, 2013)

  • • Bruun Rule

    One of the oldest methods, probosed by Bruun (1962) to relate shoreline retreat to an increase in local sea level. The Bruun rule states that a typical concave-upward beach profile erodes sand from the beach face and deposits it offshore to maintain constant water depth. The Bruun rule can be applied to correlate sea-level rise with eroding beaches and estimates the response of the shoreline profile to sea-level rise. In this simple model the beach profile is a parabolic function whose parameters are entirely determined by the water level and the sand grain size.

    ℎ = 𝐴𝐴𝑦𝑦2/3, where h is water depth at one point, and y is the distance from the shore to that point

    • Coastal Zone Simulation Model (COSMO)

    This model was developed in Holland, to improve coastal management strategies under various scenarios, including that of climate change. An interactive tool has been created that allows coastal zone managers to explore the impacts of development projects and environmental and coastal protection measures, and use it as a decision making tool. (Kay and Travers, 2008)

    • Shoreline Management Planning (SMP)

    Shoreline Management Planning is a generic approach to the strategic management of the hazards of erosion and flooding in coastal areas, which can increase climate change and sea-level rise. It was developed in the United Kingdom aiming to manage risks by using a range of methods which reflect both national and local priorities. This involves dividing the coast of an area into sub-areas, where a number of shoreline management plans are developed (for the next 50 to 100 years) which when combined cover the entire coastal length.

    • DIVA

    During DINAS-Coast European research program, a tooled called DIVA (Dynamic Interactive Vulnerability Assessment) was developed, to estimate vulnerability of coasts to sea level rise. It uses various variables like erosion, flood risk, salinity but also scenarios about climate change and socio-economic criteria, and by using a GUI (Graphical User Interface) it calculates the vulnerability. This has been applied to over than 180 nations worldwide (McFadden et al., 2004).

    • Coastal Vulnerability Indices

    Indices are used to estimate the relative vulnerability of Coastlines. There are various Indices used which are shown in Table 1 (Aduobha & Woodroffe, 2006). The most common one is the CVI index of Gornitz et al. (1994), on which a lot of other variations were based.

  • Table 1: Summary of Coastal vulnerability indices according to Abuodha Woodroffe, 2006.

    Index Variables Used Used from Coastal

    vulnerability index (CVI)

    Relief, vertical land movement, lithology, coastal landform, shoreline

    displacement, wave energy, tidal range

    Gornitz and Kanciruk (1989), Gornitz (1991),

    Gornitz et al. (1991)

    Coastal vulnerability index

    (CVI)

    Historic shoreline erosion rates, geomorphology, relative rates of sea-level rise, coastal slope, wave height ,

    tidal range

    Thieler (2000) and numerous other USGS

    reports

    Social vulnerability index (SoVI)

    Principal components analysis of Census-derived social data

    Boruff et al. (2005)

    Coastal social vulnerability score

    (CSoVI)

    Combination of CVI and SoVI Boruff et al. (2005)

    Sensitivity index (SI)

    Relief, sea-level trend,geology, coastal landform, shoreline displacement,

    wave energy, tidal range

    Shaw et al. (1998)

    Erosion hazard index

    As SI, plus exposure, storm surge water level, slope

    Forbes et al. (2003)

    Risk matrix Location, infrastructure (economic value), hazard

    Hughes and Brundrit (1992)

    Sustainable capacity index (SCI)

    Vulnerability and resilience of natural, cultural, institutional,infrastructural,

    economic and human factors

    Yamada et al. (1995)

    Sensitivity index Shoreface slope, coastal features, coastal structures, access, land use

    Carter (1990)

    Vulnerability index Disturbance event frequency, relaxation (recovery) time

    Pethick and Crooks (2000)

    Coastal Vulnerability Index (CVI) The numerical prediction of coastal evolution is a difficult task since there is no precise methodology and the relationship between the variables that determine the evolution of the coast is not well defined.

  • A number of predictive approaches have been used instead, using some variables of the coast, and one of the most common methods of assessing coastal vulnerability is the Coastal Vulnerability Index (CVI) introduced by Gornitz et al in 1990.

    This index allows the physical variables to be related in a quantifiable manner that expresses the relative vulnerability of the coast to physical changes due to sea-level rise. This method produces numerical data that don’t have a direct correlation with specific physical effects. However, those regions that are more vulnerable to sea level rise, are defined using this method.

    Along the years various methods for calculating the CVI have been introduced. These changed the variables used (added or removed variables) and also the way that the CVI was calculated. Gornitz et al. modified his original index in 1994 and Thieler and Hammar Klose (1999) inverted the ranking of the tidal range variable on the concept that large tide range is associated with strong tidal currents that influence coastal behavior.

    Original Index (Gornitz et al., 1990)

    The vulnerability classification that was originally used by Gornitz et al. in 1990 was based upon the relative contributions and interactions of seven risk variables:

    • Relief: The susceptibility of a coast to inundation by flooding and to the rapidity of shoreline retreat is affected by the relief of the area. This was changed later by the coastal slope.

    • Geology: The susceptibility of rock formations to erosion by sea.

    • Geomorphology (Landform): The erosion risk of a coastal area is in relation with the geomorphological features of the area. (e.g. sandy beaches have higher risk of erosion than cliffs).

    • Vertical movement: The relative sea level change in each area. This is calculated by taking into account the eustatic component and other vertical land motions. Subsiding coastal areas face greater inundation hazards.

    • Shoreline displacement: A measure of the past tendency of a shoreline to retreat or advance due to the SLR. Shores with accretion have low risk and those with erosion have correspondingly higher risk.

    • Tidal Range: Tide is linked with both permanent and episodic inundation events. A large tidal range determines the spatial extent of the coast. Areas with large tidal waves have wide, near zero relief intertidal zones and are susceptible to permanent inundation following sea level rise. Besides, they are susceptible to episodic flooding associated with storm surges, particularly if these coincide with high tide.

  • • Wave Height: Waves and longshore currents transform the shoreline via shoreline transport. This variable is an indicator of the amount of beach materials that may be moved offshore and as a result be permanently removed from the coastal system. The risk variable assigned to wave height is based on the maximum significant wave height for each coastal area.

    Because the aforementioned comprises qualitative, as well as quantitative information, at different scales and units each variable for each coastal segment is assigned a rank from 1 to 5, with 5 representing the most vulnerable class.

    The original CVI that was used is the square root of the product of the ranking factors divided by the number of variables. Since the geometric average was quite sensitive to small changes in individual ranking factors, the square root was used to dampen the extreme range (Gornitz et al., 1990). Five other algorithms were tested by Gornitz et al. in 1992, all of which were highly correlated (Table 2).

    The problem with the CVI approach as proposed by Gornitz et al. and adopted by the USGS is its non-consideration of socio-economic data. Boruf et al. (2005) combined the Social Vulnerability Index with the CVI to form the Coastal Social Vulnerability Index (CSoVI).

    Table 2: Modifications of CVI calculation (Gornitz et al., 1992)

    Geometric average CVI =(𝛼𝛼1 ∗ 𝛼𝛼2 ∗ 𝛼𝛼3 ∗ … .∗ 𝛼𝛼𝑛𝑛)

    𝑛𝑛

    Square root of Geom. Avg. CVI = �

    (𝛼𝛼1 ∗ 𝛼𝛼2 ∗ 𝛼𝛼3 ∗ … .∗ 𝛼𝛼𝑛𝑛)𝑛𝑛

    Modified Geometric average CVI =

    𝛼𝛼1 ∗ 𝛼𝛼2 ∗12 (𝛼𝛼3 + 𝛼𝛼4) ∗ (𝛼𝛼5) ∗ (

    12 (𝛼𝛼6 + 𝛼𝛼7))

    n − 2

    Average sum of squares

    CVI =𝛼𝛼12 + 𝛼𝛼22 + 𝛼𝛼32 + ⋯+ 𝛼𝛼𝑛𝑛2 + f2

    𝑛𝑛

    Modified Geometric average

    CVI =𝛼𝛼1 ∗ 𝛼𝛼2 ∗ 𝛼𝛼3 ∗ … .∗ 𝛼𝛼𝑛𝑛

    (5)𝑛𝑛−4

    Sum of products CVI = 4 ∗ 𝛼𝛼1 + 4 ∗ 𝛼𝛼2 + 2(𝛼𝛼3 + 𝛼𝛼4) + 4𝛼𝛼5 + 2(𝛼𝛼6 + 𝛼𝛼7)

    Modified Index (Gornitz et al., 1994)

    This index was later modified by Gornitz et al. (1994) and included 13 variables, seven physical land/marine variables and six climatological variables (for coastal segments along the U.S.). The physical land /marine variables are divided into two groups each one related to:

  • • Inundation (elevation, vertical land movements)

    • Erosion potential (geology, coastal landforms, shoreline displacement wave heights and tide ranges (Table 3)

    The six climatic variables provide information about storm frequencies, intensities and surge heights provide additional information critical for the correct estimation of the vulnerability of the coast to inundation and erosion (Gornitz et al., 1994).

    Table 3. Coastal Risk classification scheme, according to Gornitz et al. (1994)

    CVI Very low Low Moderate High Very High

    Variables 1 2 3 4 5

    Elevation ≥ 30.0 20.1 – 30.0 10.1 – 20.0 5.1 – 10.0 0 – 5.0

    Geology Plutonic Volcanic High-medium grade metamorphics

    Low grade metamorphics Sandstones and Conglomerates

    Most sedimentary rocks

    Coarse, poorly sorted unconsolidated sediments

    Fine unconsolidated sediments Volcanic ash

    Geomorphology

    Rocky, cliffed coasts, Fiords, Fiards

    Medium Cliffs, indented coasts

    Low cliffs, glacial drift, alluvial plains

    Cobble beaches, Estuary, Lagoon

    Barrier beaches, Sand beaches, Salt marsh, Mud flats, Deltas, Mangrove, Coral reefs

    RSL change (mm/yr)

    4.0

    Mean Shoreline

    displacement (m/year)

    >2.0 Accretion

    1.1 to 2.0 -1.0 to +1.0

    -1.1 to -2.0 6.9

  • Height (m)

    Annual Tropical

    storm prob. (%)

    0-8.0 8.1-12.0 12.1-16.0 16.1-20.0 >20.1

    Annual hurricane prob. (%)

    0-4.0 4.1-8.0 8.1-12.0 12.1-16.0 > 16.0

    Hurricane frequency intensity

    index (%)

    0-20 21-40 41-80 81-120 >121

    Mean forward velocity (m/sec)

    >15 15.0-12.0 12.1-9.0 9.1-6.0 40.1

    Mean hurricane surge (m)

    0-2.0 2.1-4.0 4.1-6.0 6.1-7.0 >7.0

    Modified Index (Thieler & Hammar-Klose, 1999)

    The Coastal Vulnerability Index (CVI) that nowadays in commonly used was proposed in 1999 by Thieler and Hammar-Klose. It is similar to the approach of Gornitz et al. but with a major difference.

    In previous and related studies (Gornitz, 1990; Shaw et al., 1998), large tidal coastlines were assigned a high risk classification, and microtidal coasts (tide range

  • This CVI was used by the United States Geological Survey (USGS) to assess the vulnerability of coastal area, throughout the United States (Thieler and Hammer-Klose, 1999, 2000) and will be used during the example we will discuss.

    Application of CVI

    Study case area The modified CVI of Thieler & Hammar Klosse (1999) will be applied along a coastal zone of Greece. The study area is located in NE Attica at the Gulf of Marathon (Fig. 2). It has a total length of 7.7 km. The wider area known as Marathon plain, is surrounded by the mountainous massif of Penteli. The main river in this area is Inois river with a general direction of NW-SE (Maroukian et al., 1993). The southern part of the coast is almost linear with a direction of NNW-SSE while the southern part has SSW-NNE direction and is characterized as a low slope sandy beach. Old and stabilized dunes and beachrocks are observed along the coast. The area is also characterized by a rapid and without rural planning expansion of urban activities (Xanthakis et al., 2007). The population of the wider area is 34. 000 inhabits, and in the summer much greater since Marathon is a resort for the Athenians. The balance of the sediments that are transferred to the area is affected by a Dam that is located 8 km west of Marathon. The Dam, also known as Marathon Dam is a gravity dam on the Charadros river. It was constructed between 1926 and 1929 to create an artificial lake (Lake of Marathon) that is used to supply water to Athens. The dam is often cited for its role in the modernization of Greece and the first recorded case of seismic activity associated with reservoir inundation. It was also designed to be symbolic of Ancient Greece, particularly Athenians and the Battle of Marathon. According to Maroukian et al. (1993) the shoreline near Inois river mouth has retreated 100 meters during the last 120 years. This is mainly because of the dam of Marathon. The data for the study area have been provided by Dimou et al. (2013), who has applied a modified version of CVI with 8 variables in the area.

  • Software Used For the Calculation of the CVI ArcGIS 10.3 software package, along with DSAS 4.3 (Digital Shoreline Analysis System), can be used. Alternatives are QGIS which is open source and ambuR tool that runs on R Programming language.

    ARCGIS

    ArcGIS is one of the many software packages working with maps and geographic information. It is used for the following:

    • Creating and using maps

    • Compiling geographic data

    • Analyzing mapped information

    • Sharing and discovering geographic information

    • Using maps and geographic information in a range of applications

    • Managing geographic information in a database

    The system provides an infrastructure for making maps and geographic information available throughout an organization, across a community, and openly on the Web. (ArcGis 10 Resource Center).

    Fig. 2: Study Area (Marathon Bay, Greece)

  • It includes a series of products like ArcDesktop, ArcCatalog, ArcGlobe, ArcScene, and ArcGIS Pro which needs an extra license.

    • ArcGIS Desktop

    ArcGIS Desktop is the primary product used by GIS professionals to compile, use, and manage geographic information. It includes comprehensive professional GIS applications that support a number of GIS tasks, including mapping, data compilation, analysis, geodatabase management, and geographic information sharing. (ArcGis 10 Resource Center)

    ArcGIS Desktop includes a suite of applications like ArcMap, ArcCatalog, ArcGlobe, ArcScene, ArcToolbox, and ModelBuilder. Using these applications and interfaces, you can perform any GIS tasks from simple to advanced.

    In ArcGIS Desktop, these applications are used to create and work with a number of different types of geographic information. For example, you create and work with map documents in the ArcMap application, globe documents in the ArcGlobe application, and geoprocessing models in the ModelBuilder application.

    In more detail:

    • ArcCatalog

    The ArcCatalog application provides a catalog window that is used to organize and manage various types of geographic information for ArcGIS Desktop. The kinds of information that can be organized and managed in ArcCatalog includes:

    • Geodatabases

    • Raster files

    • Map documents, globe documents, 3D scene documents, and layer files

    • Geoprocessing toolboxes, models, and Python scripts

    • GIS services published using ArcGIS Server

    • Standards-based metadata for these GIS information items

    ArcCatalog organizes these contents into a tree view that you can work with to organize your GIS datasets and ArcGIS documents, search and find information items, and to manage them. (ArcGis 10 Resource Center)

    ArcCatalog is used to:

    • Organize your GIS contents

    • Manage geodatabase schemas

    • Search for and add content to ArcGIS applications

    • Document your contents

  • • Manage GIS servers

    • Manage standards-based metadata

    ArcMap, ArcGlobe, and ArcScene include a Catalog window, which is similar to ArcCatalog and is used to organize and manage various types of geographic information as logical collections—for example, the data, maps, and results of your current GIS projects that you work with in ArcGIS.

    It is important to know that in order to work with a folder this folder has to be connected to ArcCatalog, and then you can use all the potential of ArcCatalog like a description or preview of the data table of a layer, managing files (copy, delete, rename) and other functions (Fig. 3).

    • ArcMap

    ArcMap is the central application used in ArcGIS. ArcMap is where the GIS datasets are displayed and explored for the area of interset, where you symbols are aaigned, and where map layouts are created for printing or publication. ArcMap is also the application used to create and edit datasets. (ArcGis 10 Resource Center)

    ArcMap represents geographic information as a collection of layers and other elements in a map. Common map elements include the data frame containing map layers for a given extent plus a scale bar, north arrow, title, descriptive text, a symbol legend, and so on.

    It is divided in 3 main parts:

    1. Table of Contents. This is where a list of layers that are active appear.

    Fig. 3: Using ArcCatalog to: 1.browse files, 2. Browse various information of files,

    3. Connect to folder.

  • 2. Main Map Window. Within the data frame, you display geographic datasets as layers, where each layer represents a particular dataset overlaid in the map

    3. Toolbars, which are selection of basic or advanced tools (like select, zoom in, zoom out etc) used to navigate through the map window, or to perform various other tasks (Fig. 4).

    • ArcToolbox

    ArcToolbox is a simple application containing many GIS tools used for geoprocessing. In the past there was an external application, but in the latest versions it is embedded inside ArcMap. Tools are logically organized in themes based on the functionality, and are available to use without any customization. These operations can be very powerful and achieve great results.

    In any ArcGIS Desktop application, the ArcToolbox window is activated with the Show/Hide ArcToolbox Window button found on the standard toolbar (Fig.5) or by clicking Geoprocessing > ArcToolbox.

    The contents of the ArcToolbox window can be customized. Adding and removing system and custom toolboxes is very useful to improve your working efficiency by displaying only the tools you need. The contents of the ArcToolbox window is saved with a map document. Browsing and opening tools is executed in the same way as browsing and opening files in ArcCatalog. Toolboxes can be expanded to reveal more toolst, then double-clicking the tool opens its dialog box.Tools can be dragged from the ArcToolbox window to ModelBuilder or Python window. (ArcGis 10 Resource Center).

    Fig. 4: ArcMap’s 3 main parts: Table of Contents, Toolbar, Main Map Window

  • • ModelBuilder

    ModelBuilder is an application used to create, edit, and manage models. Models are workflows that string together sequences of geoprocessing tools, feeding the output of one tool into another tool as input. ModelBuilder can also be thought of as a visual programming language for building workflows.

    While ModelBuilder is very useful for constructing and executing simple workflows, it also provides advanced methods for extending ArcGIS functionality by allowing the creation and sharing of models as tools (ArcGis 10 Resource Center). In summary:

    • ModelBuilder is an easy-to-use application for creating and running workflows containing a sequence of tools.

    • Customized tools can be created with ModelBuilder. , that can be used in Python scripting and other models.

    • ModelBuilder, along with scripting, is a way to integrate ArcGIS with other applications.

    Fig. 5: ArcToolbox activation through ArcMap and main Tool Categories

  • DSAS 4.3

    The Digital Shoreline Analysis System (DSAS) is a freely available software application that works within the Environmental Systems Research Institute (ESRI) Geographic Information System (ArcGIS) software. DSAS computes rate-of-change statistics for a time series of shoreline vector data (Thieler et al.,2009). Version 4.3 was released in April 2012 and is only compatible with ArcGIS v.10. It is supported on Windows XP, Vista, and Windows 7 operating systems.

    The Digital Shoreline Analysis System (DSAS) version 4.3 is a software extension to ESRI ArcGIS v.10 that enables a user to calculate shoreline rate-of-change statistics from multiple historic shoreline positions. A user-friendly interface of simple buttons and menus guides the user through the major steps of shoreline change analysis. Components of the extension and user guide include:

    DSAS computes shoreline rates of change using four different methods:

    • Endpoint rate • Simple linear regression • Weighted linear regression • Least median of squares.

    The standard error, correlation coefficient, and confidence interval are also computed for the simple and weighted linear-regression methods. The results of all rate calculations are output to a table that can be linked to the transect file by a common attribute field. DSAS is intended to facilitate the shoreline change-calculation process

    Fig. 6: Model created using Model builder to clip a soil map to a study area, add a field to

    the database of the clipped file and perform a calculation.

  • and to provide rate-of-change information and the statistical data necessary to establish the reliability of the calculated results. The software is also suitable for any generic application that calculates positional change over time, such as assessing rates of change of glacier limits in sequential aerial photos, river edge boundaries, land-cover changes, and so on (Thieler et al., 2009).

    Methodology The Coastal Vulnerability Index (CVI) that will be used is the one proposed in 1999 by Thieler and Hammar-Klose. It has six variables (Geomorphology, Coastal slope, Relative sea level change, Shoreline displacement, Tidal range, Significant wave height) and is calculated as the square root of the product of six variables, ranked from 1 to 5 according to Table 4, on the basis of its potential contribution to physical changes on the coast and divided by their total number:

    CVI = �(a∗b∗c∗d∗e∗f)6

    Where:

    a: geomorphology, b: coastal slope, c: rate of relative sea-level rise, d: rate of shoreline erosion-accretion, e: mean tide range, f:mean significant wave height

    Table 4. CVI variables (Hammar-Klose & Thieler, 1999).

    CVI Very low Low Moderate High Very High

    Variables 1 2 3 4 5

    Geomorphology Rocky, cliffed coasts, Fiords, Fiards Artif. Constructions

    MediumCliffs, indented coasts

    Low cliffs, glacial drift, alluvial plains, beachrocks, dunes (mixed material)

    Cobble beaches, Estuary, Lagoon

    Barrier beaches, Sand beaches, Salt marsh, Mud flats, Deltas, Mangrove, Coral reefs

    Coastal slope (%)

    >20 7-20 4-7 2.5-4

  • Shoreline erosion/ accretion(m/yr)

    >2.0 1.0-2.0 -1.0-+1.0

    -1.1- -2.0

    6.0 4.1 – 6.0 2.0 – 4.0 1.0 – 1.9

  • Slope Calculation

    The slope will be calculated by measuring the distance from each shoreline segment to the contour of 4 meters. The slope is calculated in % by dividing rise with distance and multiplying by 100 since the distance and the rise are known (4 meters) the slope in % can be calculated (Fig.7).

    There are various ways to calculate the distance, however the most educative one will be used. A DEM will be created, then the area (polygon) that has a height of over 4 meters will be selected, and finally distance between the shoreline and the polygon will be measured. The distance measured will be used for calculating coastal slope.

    Step by Step Guide

    • Import Data. Through Add Data, the necessary files (Altitude_points.shp, Contours.shp, Shoreline.shp and Study_area.shp) have to be imported (Fig. 8). By pressing ok the data appear on the Table of Contents and on the Main Map Window.

    Fig. 7: Slope Calculation

  • • Create DEM. A Digital Elevation Model is a raster layer that has elevation

    data for every cell. A DEM can be created with the help of Topo To Raster Tool, that is activated through ArcToolbox->Spatial Analyst->Interpolation->Topo to Raster. In the new window that appears in Input Feature Data, the layers that will be used have to be selected. In Type set: Altitude Points as Point Elevation, Shoreline and Contours as Contour, Study_area as Boundary.

    In Field (the field of the attribute table that stores altitude for each layer) set: “elev” for Altitude_points, Contours and Shoreline, and “none” for Study area (Fig. 9).

    In Output Surface Raster, the location of the new file is specified (your work folder). The file should be named “DEM”. In Output cell size, the size of each cell of the raster file is specified, and in this example it will be “10” meters. By pressing ok the DEM is created and added to the Table of Contents and Main Map Window.

    Fig. 8: Adding Necessary data for the creation of a DEM.

  • • Select Area of Over 4 meters. The cells that have a height of over 4 meters can

    be selected with the help of the conditional tool that can be activated through ArcToolbox->Spatial Analyst->Conditional->Con. In the Input Conditional raster select the DEM that was previously created. In Expression, a conditional expression has to be specified, in this example: “VALUE > 4”. In the Input True raster or constant value a value of “1” will be set. In Output raster, the location of the new file is specified (your work folder). The file should be named “over4m” (Fig. 10).

    • Convert raster to vector. In order to proceed with the calculation of the distance, in the next steps the raster has to be converted to a vector (polygon). This can be accomplished, through ArcToolbox-> Conversion Tools->From Raster->Raster to Polygon, and the new File should be named “over4m_polygon.shp”.

    Fig. 9: Creating a DEM.

  • • Split shoreline in parts. In order to estimate the nearest distance between small

    parts of the shore and the polygon that was created before and represents altitudes of over 4 meters, the shoreline polyline has to be split in smaller parts by using the vertices of the line, with the help of Split Line at Vertices Tool, that can be activated through ArcToolbox-> Data Management Tools->Features->Split Line At Vertices. In the Input Features the input layer that will be used as the source data (Shoreline.shp). In Output Feature Class, the location of the new file is specified (your work folder). The file should be named “split_shore.shp” (Fig. 11).

    Fig. 10: Calculating the area that has an elevation of over 4 meters with the Conditional

    Tool.

  • • Calculate Distance. Since all the necessary layers were created in the previous steps the distance from each part of the shore to the nearest point that has an altitude of 4 meters can be calculated, with the help of Near Tool that can be accessed through ArcToolbox-> Analysis Tools->Proximity->Near. In the Input Features, the splitted shoreline that was created has to be set (Fig.12). (“split_shore.shp”) and in the Near features the polygon that represents the area with an elevation of over 4 meters. By pressing ok, the distance will be calculated and added to the attribute table of split_shore shapefile, and can be seen by right clicking on the layer and selecting Attribute table. A new Field named NEAR_DIST, represents the distance that was calculated with the use of Near Tool (Fig. 13).

    Fig. 11: Splitting a Polyline at Vertices

  • • Calculate slope. The slope will be calculated, as discussed before by dividing rise (4 meters) to the distance. Firstly a New Field has to be created(Fig.14), in the Attribute table of split_shore layer that will be named slope. To accomplish this the Add Field Option from Table Options has to be selected. In the Add Field Window that is activated the Name of the new Field has to be specified as “Slope” and Type as Double. By right clicking on the newly created Field and selecting Field Calculator, the slope will be calculated. In the Field Calculator window the correct expression has to be provided to calculate slope, in this example “Expression Slope = 4 / NEAR_DIST * 100”. The slope will be calculated after pressing ok, in the field named slope (Fig. 15).

    Fig. 12: Calculating distance using Near Tool

    Fig. 13: Attribute Table, containing the calculated distance.

  • Fig. 14: Adding a Field to the Attribute table of a vector file.

    Fig. 15: Calculating slope

  • Geomorphology

    The Geomorphology of the coastal area is a result of field work, where the type of material has been mapped in a vector layer. Several values for the type such as sand, gravel, mixed material, cliff and artificial constructions that have different resistivity to erosion, exist in the database.

    Step by Step Guide

    • Import Data. Through Add Data, the layer geomorphology.shp should be added to the workspace. All other layers from previous steps have to be closed except split_shore.shp.

    • Join Information of Two Layers. Each shoreline part should be attributed a geomorphological feature and this can be accomplished by joining the 2 layers based on their spatial information, with the use of the Spatial Join Tool, that can be found in ArcToolbox-> Analysis Tools->Overlay->Spatial Join. In Target Features the splitted shoreline layer has to be set, in the Join Features the Geomorphology and in the Output Feature Class the location of the new file is specified (your work folder). The file should be named “split_shore_geom.shp”. By unchecking Keep all target features, only the needed fields that contain the geomorphological information and the slope can be selected to keep in the new file. Since the two layers not coincide in the Match Option select WITHIN_A_DISTANCE and set a search radius of “50” meters (Fig.16). After pressing ok the new file will be created, containing the information that was specified from Field Map of Join Features option.

    Fig. 16: Spatial Join of 2 layers

  • Relative Sea Level Change

    Relative Sea level change is a combination of tectonics global sea level rise. For the study area there is a tectonic uplift of 0.4-0.5 mm/year (Pavlopoulos et al., 2006), while there is a rise of the sea level of about 15 mm/year (Tsimplis et al., 2009). In total there is relative sea level rise of about 14.5 mm/year.

    Step by Step Guide

    Adding Information to Attribute table. To add this information to the database, a new field has to be created in the Attribute table of split_shore_geom.shp, by selecting Table Options->Add Field and then creating a new field named “RSLC”. By right clicking on the new field and selecting Field Calculator the field can be updated by providing in Field Calculator the Expression “RSLC = 14.5” (Fig. 17).

    Mean Tidal Range

    From Bibliographical data coming from tidal sensors in greek harbours in Chalkida and Syros Island there is a mean tidal range of 10 cm, and like the rest of the Mediterranean the study area is classified as microtidal. This informationcan be added to our database like before by adding a new Field named “Tidal_Range” and using the Field Calculator to fill it.

    Mean Wave height

    Using Bibliographical data for the area a significant wave height (Hs) of 0.4-0.5 meter is calculated. This information can be added in a new Field named Hs in our layer, as discussed before.

    Fig. 17: Adding Information to Attribute Table

  • Shoreline Erosion/Accretion

    Quantifying shoreline movements is usually performed by a ‘‘baseline and transect’’ method using manual or automatic (computer) techniques (Dolan et al., 1978; Clow & Leatherman, 1984). In a GIS environment, the user constructs a baseline by drawing a reference line either onshore or offshore of the historical shorelines in the GIS. Then, transect lines are cast perpendicular to the baseline at a user-specified spacing along the baseline. The transects are intersected with the shorelines to produce points, which identify the locations of historical shoreline positions along each transect. The statistics are calculated for each transect and stored in a data table

    In order to calculate erosion or accretion in different areas of the beach, a series of digitized shorelines are provided combined in a layer named shorelines.shp (years: 1960, 1977, 1996, 2010).

    A baseline is a reference line, which attempts to parallel the general orientation of the historical shorelines. Transect lines are cast, usually perpendicular to and at a spacing interval of interest, along the baseline, extending across the shorelines. The baseline is either landward or seaward. The shape of the baseline is important because it influences the orientation of transects that are cast along it. Some researchers construct a baseline by hand through digitizing or automated techniques can be applied like creating buffer zones. In our study case an automated technique has been pre-applied.

    Step by Step Guide

    • Creating a Geodatabase. For DSAS to work the data have to be organized inside a geodatabase., which can be created through ArcCatalog. By opening Catalog Window, and right clicking on the work folder of the example a new Geodatabase can be created through New->Personal Geodatabase. Name should be set as “DSAS”. Inside the Geodatabase the shorelines and the baseline should be placed, which can be performed by right clicking on the Geodatabase file, and selecting Import, then Multiple Feature class and selecting the layers to be imported in the Geodatabase. These are the baseline and shorelines shapefiles, that already include all the required fields for DSAS to run (like Date of shoreline) (Fig. 18).

  • • Import Data. Through Add Data, the layers baseline and shorelines that are located inside the geodatabase should be added to the workspace.

    • Setting Parameters in DSAS. DSAS Toolbar (Fig. 19), if not already activated should be activated by right clicking on the Toolbars Space in ArcMap. The parameters for running DSAS can be set through the Set/Edit Default parameters.

    In Cast Transect Settings Tab the Baseline Layer should be specified according to the data (in this example the baseline file that was imported). The Baseline Group Field should be set as ObjectId, the Transect Spacing as “20” (one transect for every 20 meters) and the Transect Length as “200” (there should be no transect that doesn’t reach all the shorelines). The baseline that was provided was created inland so the Onshore option should be selected.

    In Shoreline Calculation Settings the Shoreline Layer is set to direct to the shorelines layer that was imported, in the Shoreline Date the field “Date_1” should be specified (which exists in the shorelines layer attribute table) and in the Shoreline Uncertainty field the field “Accuracy”, that already exists in the attribute table of shorelines is set (Fig. 19).

    Fig. 18: Adding features to a Geodatabase

  • • Casting Transects. To cast transects, from the DSAS Toolbar, Cast Transects should be selected. In Transect Storage Parameters the location of the Geodatabase where the Transects will be stored is set and the Name of the layer is specified (in this case “Transect”). The option Smooth Baseline Cast provides more accurate transects since it uses a moving average window to dampen errors, and is recommended (Fig. 20).

    Fig. 19: Setting Parameters of DSAS.

    Fig. 20: Casting Transects in DSAS.

  • • Calculate Statistics. To Calculate the End Point Rate which represents the rate of erosion/accretion, in the Transect Layer Menu the Transect Layer that was constructed should be selected. By pressing Calculate statistics and selecting EPR: End Point Rate a processing of the data takes place and the results are stored in 2 tables. Transect rates table includes the necessary information (EPR rate for each transect) and should now be joined with the transects layer (Fig. 21).

    • Joining Information. To Join the Table that includes the EPR information with

    the Transects layer, a join must be performed. This will be based on a common field that exists on both layers. Right clicking on Transects layer brings up a Joins and Relates option. By selecting it and then then join a new window appears. In the Join Data Window, the table that will be joined with the transects layer is specified (in this case Transect_rates). The Join will be based on a common field in the attribute table which is the field named “object identifier” (Fig. 22).

    Fig. 21: Calculating EPR rate for each transect.

  • • Intersecting EPR values to the shoreline. Since EPR was calculated along each

    transect, this information will have to be joined to the original layer (that has a shoreline split to parts) which are not the same as the parts that DSAS calculated. To do so the Intersect tool can be used to create points that are along the shoreline in places where transects intersect. These points will be assigned with the EPR value of the transect before a spatial join will be applied, and in each part of the shoreline the EPR of the nearest point will be assigned. Intersection can be performed through the Tool Intersect located at ArcToolbox-> Analysis Tools->Overlay->Intersect. The 2 layers to be intersected should be selected in the Features option (split_shore.shp and transects). In the Output Feature Class the location of the new file is specified (your work folder). The file should be named “Intersect.shp”, and the Type should be set to POINTS (Fig. 23).

    Fig. 22: Joining EPR rates with transect layer.

  • • Join Information of Two Layers. Each shoreline part should be attributed an

    EPR rate and this can be accomplished by joining the 2 layers (intersect.shp and split_shore_geom.shp) based on their spatial information, with the use of the Spatial Join Tool, that can be found in ArcToolbox-> Analysis Tools->Overlay->Spatial Join. In Target Features the splitted shoreline layer has to be set, in the Join Features the Intersect layer and in the Output Feature Class the location of the new file is specified (the work folder). The file should be named “split_shore_final.shp”. By unchecking Keep all target features, only the needed fields can be selected to keep in the new file. Since the two layers not coincide in the Match Option select WITHIN_A_DISTANCE and set a search radius of “120” meters (Fig.24). After pressing ok the new file will be created, containing the information that was specified from Field Map of Join Features option.

    Fig. 23: Intersecting EPR values with shoreline to create points along the shoreline.

  • • Ranking values to calculate CVI. As discussed early in this chapter, the CVI is

    based on ranking various variables in a scale from 1 to 5. By using table 4, the database can be ranked and then the CVI can be calculated. Firstly the new Fields have to be created to host the rank values. Like before, when fields were added to the attribute table of split_shore_final the following fields will be created in the attribute table and set as integers (since only values from 1 to 5 will be assigned). These are: CVI_Slope, CVI_Geomorphology, CVI_RSLC, CVI_TIDAL CVI_Hs, Cvi_EPR. In order to complete the database, a lot of selections and assignment of values have to be made. For example, all the parts of the shore that have a slope value less than 2.5% are first selected. Then a value (rank) of 5 is assigned to these values. Then the values between 2.5 and 4 % are selected and assigned a value(rank) of 4. Because the steps involved in this procedure are almost 100, only a description of how the selection and assignment of a value is being made.

    Selection. From the Selection Menu of Arcmap, the Select by Attributes option has to be activated, and a new window will appear. The layer where the selection will be performed is selected in the layer option. The Create a new selection has to be used and the appropriate field has to be selected. For example, for slope the equivalent field “Slope” is selected and then the expression "Slope" < 2.5 is specified to select all values that have a slope lower than 2.5%. Then by right clicking on the layers name and opening the Attribute table, the records that are selected are highlighted in blue(Fig. 25).

    Fig. 24: Joining EPR information with the rest of Information that is located inside the shoreline attribute table.

  • • Assigning a value. To assign a value the Field Calculator will be used.

    Through attribute table, and with the records that have a slope lower than 2.5% selected, by right clicking on the field which will be updated (in our case CVI_SLOPE) and opening Field Calculator for this field, we can assign a value to the selected records (in the case of low slope a CVI of “5”). By doing this procedure for all the cases that exist in Table 4 we obtain the complete table of CVI values.

    Fig. 25: Selecting areas with a slope value less than 2.5%

    Fig. 26: Assigning Values using Field Calculator

  • CVI_TIDE, CVI_RSLC and CVI_Hs are constant for the whole area with values of 5 for the first 2 and 1 for the last, and so the procedure of selections - assignments has to be completed only for 3 variables.

    • Final CVI calculation. A new field named CVI has to be created, with a double precission. The following expression has to be provided to calculate the CVI for each part of the shoreline: “Sqr ( ([CVI_SLOPE] * [CVI_RSLC] * [CVI_TIDE] * [CVI_Hs] * [CVI_GEOMOR] * [CVI_EPR] ) / 6 )”. After pressing ok the CVI field will be updated (Fig. 27).

    Final map

    In order to obtain a usable Map the CVI will be classified into classes. Right clicking on the final Layer, and then choosing Properties will pop up Layer Properties window. By selecting Symbology, then Quantities and Graduated Colours and then setting as the field for the Classification(Value Field) the CVI. As a mode (method) for classification selecting Natural Breaks (which determines automatically the best arrangement of values into different classes) and 5 classes (Very Low, Low, Medium, High, Very High) is recommended. In the Legend change the name of each class and also change the colors from the color ramp.

    Fig. 27: Calculation of the final CVI values.

  • Printing the Map

    To Print a Map the Layout View has to be used. When in Layout View through the Insert Menu a North Arrow, a Scale a Legend and a Title can be added. When finished by pressing File->Export a high resolution Map can be exported.

    Fig. 28: Creating A CVI map of Marathon area.

  • Fig. 29: Preparing a Map for Print through the Layout View.

  • References

    Abuodha, P., Woodroffe, C., 2006. International assessments of the vulnerability of the coastal zone to climate change. Australia: Australian Greenhouse Office.

    ArcGis 10 Resource Center Help: http://help.arcgis.com/en/arcgisdesktop/10.0/help/

    Boruff, B.J., Emrich, C., Cutter, S.L., 2005. Erosion hazard vulnerability of US coastal counties. Journal of Coastal Research 21, 932-942.

    Briguglio, L., 2004. Small Island Developing States and their Economic Vulnerabilities. International Workshop on 'Vulnerability and Resilence of Small States'. The Global Development Research Center Programme, Partner of UN Ocean Atlas, The Ocean Project, GIN Global Island Network, World Ocean Network, University Gozo Centre, Malta.

    Bruun, P., 1962. Sea-Level Rise as a Cause of Shore Erosion, Proceedings Paper 3065. Journal of the Waterways and Harbors Division WW1, 117-130. American Society of Civil Engineers.

    Caldwell, J.M., 1949. Beach Erosion. The Scientific Monthly 69, 229-235.

    Carter, R.W.G., 1990. The impact on Ireland of changes in mean sea level. Programme of expert studies in climate change, No 2. Dublin: Department of the Environment, 128pp.

    Clow, J.B., Leatherman, S.P., 1984. Metric mapping: An automated technique of shoreline mapping. In: Proceedings of the 44th American Congress on Surveying and Mapping, Falls Church, Virginia, American Society of Photogrammetry, pp. 309–318.

    Collet, I., Engelbert, A., 2013. Coastal regions: people living along the coastline, integration of NUTS 2010 and latest population grid. Eurostat, Statistics in focus 30/2013.

    Dimou, A., Vassilakis, E., Antoniou, V., Evelpidou, N., 2010. An assessment of the coastal erosion at marathon East Attica (Greece). Proceeding of 10th International Congress of Hellenic Geographical Society, 1579-1587.

    Dolan, R., Hayden, B., Heywood, J., 1978. A new photogrammetric method for determining shoreline erosion. Coastal Engineering 2, 21–39.

    Douglas, B.C., 1997. Global sea rise; a redetermination. Surveys in Geophysics 18, 279-292.

    Forbes, D.L., Taylor, R.B., Solomon, S.M., Craymer, M., Manson, G.K., Dyke, A.S., Hodgson, D.A, 2003. Crustal motion, climate change and coastal morphodynamics in the western Canadian Arctic. International Conference on Arctic margins, September 30-October 3, 2003, Geological Survey of Canada (Atlantic), Dartmouth, Nova Scotia, Canada, Abstract, p. 3.

  • Gornitz, V., Kanciruk, P., 1989. Assessment of global coastal hazards from sea-level

    rise. Proceedings of the 6th Symposium on Coastal and Ocean management, ASCE, July 11-14 1989, Charleston, SC.

    Gornitz, V., 1991. Global coastal hazards from future sea level rise. Palaeogeography, Palaeoclimatology, Palaeoecology 89, 379-398.

    Gornitz, V.M., White, T.W., Cushman, R.M., 1991. Vulnerability of the US to future sea level rise. Proceedings of the 7th Symposium on Coastal and Ocean Management, American Society of Civil Engineers, pp. 1345-1359.

    Gornitz, V., White, T. 1992. A Coastal Hazards Database for the U.S. East Coast, ORNL/CDIAC-45, NDP-43A, Oak Ridge. Tenessee: Oak Ridge National Laboratory.

    Gornitz V., Daniels R., White T., Birdwell K., 1994. The development of a coastal risk assessment database: vulnerability to sea–level rise in the U.S. southeast. Journal of Coastal Research Special Issue 12, 327–338.

    Hammar-Klose, E.S., Thieler, E.R., 2001. Coastal Vulnerability to Sea-Level Rise, A Preliminary Database for the U.S. Atlantic, Pacific, and Gulf of Mexico Coasts. U.S. Geological Survey, Digital Data Series, DDS-68.

    Hughes, P., Brundrit, G.B., 1992. An index to assess South Africa's vulnerability to sea-level rise. South African Journal of Science 88, 308-311.

    IPCC, 2013. Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.

    Kay, C., Travers, A., 2008. Coastal Vulnerability and Adaptation Assessment. In S. o. Sciences, Compendium of Coastal Resources, Tools and Methodologies. University of Wollongong.

    Klein, R., Nicholls, R., 1999. Assessment of coastal vulnerability to climate change. Ambio 28 (2),182-187.

    Maroukian, H., Zamani, A., Pavlopoulos, K., 1993. Coastal retreat in the plain of Marathon (East Attica) Greece: Causes and Effects. Geologica Balcanica 23 (2), 67-71.

    McFadden, L., Vafeidis, A., Nicholls, R., 2004. A coastal database for global impact and vulnerability analysis.

    Pavlopoulos, K., Karkanas, P., Triantaphyllou, M., Karymbalis, E., Tsourou, Th., Palyvos, N., 2006. Palaeoenvironmental evolution of the coastal plain of Marathon, Greece, during the Late Holocene: Deposition environment, climate and sea-level changes. Journal of Coastal Research 22 (2), 424-438.

    Peltier, W. R., Jiang, X., 1997. Mantle viscosity, glacial isostatic adjustment and the eustatic level of the sea. Surveys in Geophysics 18, 239-277.

  • Pethick, J., Crooks, S., 2000. Development of a coastal vulnerability index: a

    geomorphological perspective. Environmental Conservation 27, 359-367.

    Shaw, J., Taylor, R.B., Forbes, D.L., Ruz, M.-H. and Solomon, S., 1998. Sensitivity of the coasts of Canada to sea-level rise. Bulletin of the Geological Survey of Canada 505, 1-79.

    Thieler, E.R., 2000. National Assessment of Coastal Vulnerability to Future Sea-level Rise. USGS 076-00.

    Thieler, E., Hammar-Klose, E., 1999. National Assessment of Coastal Vulnerability to Future Sea Level Rise: Preliminary Results for the U.S. Atlantic Coast. U.S. Geological Survey, Open-File Report.

    Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., Ergul, Ayhan, 2009. Digital Shoreline Analysis System (DSAS) version 4.0 — An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. *current version 4.3

    Tsimplis, M., Marcosh, M., Colinc, J., Sometc, S., Pascualb, A., Shawa, A., 2009. Sea level variability in the Mediterranean Sea during the 1990s on the basis of two 2d and one 3d model. Journal of Marine Systems 78, 109-123.

    Xanthakis, Μ., Xanthopoulos, G., 2007. Land use change evaluation in the area of Marathon in Attica since the end of 19th century using Geographical Information Systems. 13th Panhellenic Forestry Congress ΙΙ, 491-497.

    Yamada, K., Nunn, P.D., Mimura, N., Machida, S. and Yamamoto, M., 1995. Methodology for the assessment of vulnerability of South Pacific island countries to sea-level rise and climate change. Journal of Global Environmental Engineering 1, 101-125.

    Zhang, K., Douglas, B.C., Leatherman, S. P., 1997. East Coast storm surges provide unique climate record. EOS 78(37), 389-397.

    IntroductionEstimating Coastal erosionCoastal Vulnerability Index (CVI)Original Index (Gornitz et al., 1990)Modified Index (Gornitz et al., 1994)Modified Index (Thieler & Hammar-Klose, 1999)

    Application of CVIStudy case areaSoftware UsedARCGISDSAS 4.3

    MethodologyCalculating CVILoading DataSlope CalculationGeomorphologyRelative Sea Level ChangeMean Tidal RangeMean Wave heightShoreline Erosion/AccretionFinal mapPrinting the Map

    References