Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Coastal erosion is a worldwide hazard of which the consequences can only be mitigated via thorough and efficient monitoring of erosion and vulnerability to erosion. This study aimed to establish the accuracy, efficacy and efficiency of various remote sensing techniques for the detection and monitoring of coastal erosion and vulnerability occurring in False Bay, South Africa. There is a need to monitor the erosion in this area as well as to determine the most effective techniques for monitoring the erosion in False Bay and other similar environments in the future. This study provides an assessment of the usefulness of different data sources and techniques for change detection in the coastal environment. The data sources used were Landsat TM/ETM+ imagery and aerial photographs. Image differencing, tasselled cap transformations, vegetation index differencing, Boolean change detection, and post-classification change detection were all performed on the Landsat imagery. The aerial photographs were assessed using the Digital Shoreline Analysis System (DSAS) add-on for ArcGIS which determines statistical differences in the shoreline position as digitised in vector format. The results showed that while the resolution of the Landsat imagery was not sufficient to analyse erosion along the beach itself, the larger area covered by the satellite images enabled vulnerability indicators to be seen. Notably, the post-classification change detection indicated consistent increases in built-up areas, while sand dune, beach, and sand (not beach) all decreased. NDVI differencing showed consistent decreases in NDVI indicating decreasing plant health and density. The results of image differencing with both band 4 and the brightness band led to conclusions that vegetation health was decreasing while reflective surfaces such as bare sand and roads were increasing. All of these indicate an increased vulnerability to coastal erosion. The Boolean change detection method was found not to be useful in this case. Aerial photographs were studied on four focus areas: Bayview Heights, Macassar Beach, Strand, and Pringle Bay. The results showed erosion at all four areas, with Strand experiencing only erosion (no accretion) at an average of 53 cm erosion per year. Erosion at Macassar Beach and Pringle Bay was also severe, with Bayview Heights being the least severe and showing a combination of erosion and accretion. The higher resolution available on the aerial photographs was vital to view changes on the beach itself. In future studies requiring assessment of changes in the position or condition of the beach itself, aerial photographs or high resolution satellite data should be used. Studies of vulnerability extending over the entire coastal zone may make use of Landsat TM images. Post-classification change detection provides powerful change direction information and can indicate the percentage of area change from one class to another. However, image differencing and vegetation index differencing are much faster to perform and can provide information about general trends in the changes occurring. Therefore post-classification change detection might be used in areas of high and rapid change while image differencing and vegetation index differencing can be useful to cover vast areas where little change is expected. / AFRIKAANSE OPSOMMING: Kus-erosie is ‘n wêreldwye gevaar waarvan die gevolge slegs deur deeglike en doeltreffende monitering van erosie en kwesbaarheid vir erosie verminder kan word. Hierdie studie poog om die akkuraatheid, doeltreffendheid en effektiwiteit van verskillende afstandswaarneming tegnieke vas te stel vir die opsporing en monitering van kus-erosie en kwesbaarheid in Valsbaai, Suid Afrika. Daar is ‘n behoefte aan die monitering van erosie in hierdie area, sowel as om die mees doeltreffende tegnieke van die monitering hiervan in Valsbaai en ander soortgelyke omgewings in die toekoms te bepaal. Hierdie studie bied ‘n evaluering van die nut van verskillende data-bronne en tegnieke vir die opsporing van verandering in ‘n kusomgewing. Die data-bronne wat gebruik is, is Landsat TM/ETM+ beelde asook lugfoto’s. Beeld differensievorming, “tasselled cap” transformasies, plantegroei indeks differensievorming, Boolse verandering en post-klassifikasie verandering is toegepas op die Landsat beelde. Die lugfotos is ge-evalueer deur die Digitale Kuslyn Analise Stelsel (Digital Shoreline Analysis System – DSAS). DSAS is ‘n bykomstige sagteware vir ArcGIS wat statistiese verskille in gedigitaliseerde kuslyn posisie bepaal. Die resultate toon dat terwyl die resolusie van die Landsat beelde nie voldoende was om strand-erosie self te analiseer, die groter area wat deur die satellietbeelde gedek word toegelaat het om kwesbaarheid aanwysers te ontleed. Spesifiek die post-klassifikasie verandering het aangedui dat konsekwente toenames in beboude areas voorkom, terwyl afnames in sandduine, strand en sand-areas voorgekom het. NDVI differensievorming het konsekwente afnames in NDVI getoon, wat dui op afnames in die gesondheid en digtheid van plantegroei. Die resultate van die beeld differensievorming met beide Landsat Band 4 en die helderheid-band het gelei tot die gevolgtrekking dat die gesondheid van plantegroei afgeneem het, terwyl reflektiewe oppervlaktes soos oop sand en paaie aan die toeneem is. Al hierdie resultate dui op die verhoogde kwesbaarheid vir kus erosie. Die Boolse verandering metode is bevind om nie van nut te wees in hierdie geval nie. Lugfoto’s van vier fokus-areas is bestudeer: Bayview Heights, Macassar Strand, Strand en Pringlebaai. Resultate van die DSAS analise het gevind dat oorwegend erosie by al vier areas plaasvind, met Strand die enigste area wat slegs erosie (geen aanwas) ervaar teen ‘n gemiddelde koers van 0.53 m per jaar. Erosie by Macassar Strand en Pringlebaai was ook ernstig, terwyl Bayview Heights die minste erosie ervaar het, met ‘n kombinasie van erosie en aanwas. Die hoër resolusie beskikbaar deur die lugfoto’s was noodsaaklik om veranderinge in strand areas waar te neem. In toekomstige studies wat die assessering van verandering in die posisie of toestand van strande noodsaak behoort lugfotos of hoë-resolusie satellietbeeld data gebruik te word. Studies oor die kwesbaarheid van ‘n hele kusstreek kan wel gebruik maak van Landsat data. Post-klassifikasie verandering bied kragtige informasie oor die rigting van verandering en kan die persentasie van verandering van een klas na ‘n ander aandui. Beeld en NDVI differensievorming is egter veel vinniger om uit te voer en kan informasie rakende die algemene tendense in verandering lewer. Post-klassifikasie verandering kan dus gebruik word in gebiede van vinnige en beduidende verandering plaasvind, terwyl beeld en NDVI differensievorming nuttig kan wees om groot areas te dek waar min verandering verwag word.

Thesis (MScEng (Civil Engineering))--University of Stellenbosch, 2002. / 198 leaves double sided printed, preliminary pages i-xx and numberd pages 1-1-12-6.Includes bibliography. List of tables, figures and appendices and acronyms. Scanned with a HP Scanjet 8250 Scanner to pdf format (OCR). / ENGLISH ABSTRACT: In this study the numerical short wave model SWAN is evaluated for application to a selected coastal region in South Africa. The aim of this study was to evaluate the degree of accuracy with which SWAN can simulate prototype nearshore wave spectra and wave parameters (e.g. wave height, mean wave direction and mean wave period) for an Algoa Bay field case. Algoa Bay represents a typical deep, sheltered embayment on the South African south coast, which is exposed to high-energy swell. Sensitivity analyses on various wave-related processes were also done, with the aim of establishing the dominant physical processes and appropriate model setup for the Algoa Bay field case. With the dominant wave-related processes and appropriate model setup for the Algoa Bay field case established, selected final runs were performed to determine the degree of accuracy with which SWAN can simulate prototype conditions, by comparing its results with available field recordings. This study comprises a review of the SWAN evaluation work conducted to date by others, an overview of South African coastal conditions, and numerical model simulations. The model simulations, which represent the main focus of this study, were conducted for a selection of available offshore wave conditions (at 85 m water depth) observed during the Algoa Bay field case and were compared to available nearshore observations (at 17 m water depth). Environmental conditions of waves, wind and currents were included in these simulations. The study focuses on model application and sensitivity analysis, rather than model development, and includes evaluation of all relevant processes, without focussing on any specific model aspect. The results of this study show that SWAN simulations correlated well with observations at the nearshore station in Algoa Bay, both in wave spectral shape and its associated parameters. Dominant processes identified for the field case were depth-induced refraction, bottom friction and directional spreading. This finding agrees with those of previous evaluations of SWAN and previous modelling experience by others. It is shown that high-energy swell is relatively more sensitive to the choices of model setup than wind sea. Based on the simulation results of high-energy swell, it is concluded that the calculation of depth-induced refraction in SWAN seem to contain a degree of inaccuracy. It is also concluded that the findings of this study could be used as a guideline to SWAN modelling studies along the South African south coast. / AFRIKAANSE OPSOMMING: In hierdie studie word die toepassingsmoontlikhede van die numeriese kortgolf model SWAN vir 'n geselekteerde gedeelde van die Suid-Afrikaanse kuslyn beoordeel. Die doel van hierdie studie is om die vlak van akkuraatheid waarmee SWAN prototipe golfspektra en golfparameters (bv. golfhoogte, gemiddelde golfrigting en gemiddelde golfperiode) in die vlakwater kan simuleer te beoordeel, vir 'n Algoabaai gevallestudie. Algoabaai verteenwoordig 'n tipiese diep, beskermde baai aan die Suid-Afrikaanse kuslyn, wat blootgestel is aan hoe-energie deining. Sensitiwiteitstoetse is ook uitgevoer vir verskillende golfprosesse, met die doel om die dominante fisiese prosesse en gepaste modelopstelling vir die Algoabaai gevallestudie te vind. Nadat die dominante golfprosesse geidentifiseer is, en die toepaslike modelopstelling gevind is, is finale simulasies uitgevoer vir geselekteerde gevalle om die mate van akkuraatheid te bepaal waarmee SWAN prototipe kondisies kan simuleer, deur simulasie resultate met beskikbare veldmetings te vergelyk. Hierdie studie bestaan uit 'n samevatting van die evaluasiewerk verrig op SWAN deur andere, 'n samevatting van golf-, wind- en stroomtoestande aan die Suid-Afrikaanse kus en numeriese modelsimulasies. Die modelsimulasies, wat die hooffokus van hierdie studie is, is uitgevoer vir 'n seleksie van beskikbare diepsee golftoestande (in 85 m waterdiepte) uit die Algoabaai gevallestudie en is vergelyk met beskikbare vlakwater metings (in 17 m waterdiepte). Omgewingstoestande van golwe, wind en seestrome is ingesluit in hierdie simulasies. Die studie fokus op modeltoepassing en sensitiwiteits-analise, eerder as modelontwikkeling, en behels die beoordeeling van alle toepaslike modelprosesse, sonder om te fokus op enige spesifieke model aspek. Die resultate van hierdie studie toon aan dat die SWAN simulasies goed korrileer met vlakwater meetings in Algoabaai, vir beide golfspektraalvorm en verwante golfparameters. Bodemrefraksie, bodemwrywing en rigtingsspreiding is geidentifiseer as dominante modelprosesse. Hierdie resultaat kom ooreen met bevindings van vroeere beoordeling van SWAN en modelleer-ervaring deur andere. Dit word aangetoon dat hoe-energie deining relatief meer sensitief is vir modelopstelling as wind-see. Gebasseer op resultate van simulasie met hoe-energie deining, word die gevolgtrekking gemaak dat die berekening van bodemrefraksie in SWAN 'n mate van onakkuraatheid toon. Die gevolgtrekking word ook gemaak dat die resultate van hierdie studie as riglyn gebruik kan word vir modelleerwerk met SWAN aan die Suid-Afrikaanse suidkus.

The state of Georgia has two large ports that are accessed by way of navigable entrance channels. One of these ports is located in Brunswick, Georgia, and is maintained by the United States Army Corps of Engineers via periodic dredging. Sediments removed from the channel are typically pumped several miles offshore of Brunswick and placed in dredged material mounds, thus removing the sediment from the littoral cycle. This offshore placement, while being the most economically viable method, often negatively impacts the sediment budget of the coastal region and causes erosion downdrift of the channel, specifically along Jekyll Island. Onshore placement of the dredged material is not feasible due to increased associated costs and the high fraction of fines present in the material; thus, nearshore placement is a potentially viable alternative. Nearshore placement could possibly reduce erosion rates and provide protection to property from waves and storms. The USACE initiated a thorough field data collection campaign in 2002 to study the possibility of beneficial placement of dredged material. The author analyzed the existing data to predict the rate and direction of sediment movement away from an existing dredge mound. These predictions are then compared to bathymetric survey data in an effort to validate the results and methodologies used for sediment transport predictions. The ultimate goal is to use the results of this study along with numerical models currently being developed by the Corps to assess the possibility of sediments being transported toward the shore thus re-entering the littoral cycle and providing a benefit to the coast of Georgia.

A large proportion of the human population, their settlements and socioeconomic activities occur on land directly adjacent to the coastline. The increased demand for coastal leisure and tourism has interfered with natural landscape features and their associated processes. The Cape St Francis/St Francis Bay peninsula located on the southeast coast of South Africa was rapidly developed and transformed from a little fishing village into an urban coastal developed area over a 50-year period (1961-2014). A system that once existed in a state of dynamic or non-equilibrium was interfered with through anthropogenic disturbances, resulting in more frequent and intense natural events, which ranged from floods to debris flows, decreased sand supply and resulting beach erosion. The aim of the project was to identify and map landscape features and changes on the peninsula using an interdisciplinary approach. The triangulated methods of a desktop study using Geographic Information Systems (GIS) and media reviews, a crowdsourcing/participatory approach based on interviews, and a one year land surveying period of measurable field based surveys of physical features gave a well balanced view. The research showed that the natural landscape has been altered dramatically by settlement and associated infrastructure development. In particular, the loss of dunefields and the artificial modification of river paths were major impact areas. Beach erosion is a continual issue for the peninsula residents, particularly in St Francis Bay.

This study uses the predictive modeling program Sea-Levels Affecting Marshes Model (SLAMM) to evaluate sea-level rise hazards, such as erosion and inundation, on coastal archaeological sites with a vertical rise of sea level of .98 meters from 2006 to 2100. In total 177 archaeological site locations were collected and georeferenced over GIS outputs maps of wetlands, erosion presence, surface elevation, and accretion. Wetlands data can provide useful information about characteristics of the wetland classes, which make a difference in the ability for coastal archaeological sites to combat sea level rise. Additionally, the study evaluated predicted erosion of archaeological sites by presence or absence of active erosion on a cell-by-cell basis. Elevation map outputs relative to mean tide level allowed for a calculation of individual archaeological site datums to use NOAA tidal databases to identify the potential for their inundation. Accretion maps acquired from the SLAMM run determined the potential for the archaeological site locations to combat rising sea levels and potentially provide protection from wave effects. Results show that the most significant hazard predicted to affect coastal archaeological sites is inundation. Approximately 54% of the total archaeological sites are predicted to be inundated at least half the time by 2100. The hazard of erosion, meanwhile, is expected to affect 33% of all archaeological sites by the end of the century. Although difficult to predict, the study assumes that accretion will not be able to keep pace with sea-level rise. Such findings of hazards prove that SLAMM is a useful tool for predicting potential effects of sea-level rise on coastal archaeological sites. With its ability to customize and as it is complementary, it provides itself not only an economical choice but also one that is adaptable to many scenarios.