ResearchSpace :: Browsing by Author "Lück-Vogel, Melanie"

Browsing by Author "Lück-Vogel, Melanie"

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Advancing land-sea integration for ecologically meaningful coastal conservation and management
(Elsevier, 2019-09) Harris, LR; Bessinger, M; Dayaram, A; Holness, S; Kirkman, S; Livingstone, TC; Lombard, AT; Lück-Vogel, Melanie; Pfaff, M; Sink, KJ; Skowno, AL; Van Niekerk, Lara
Coasts are among our most valuable natural assets but are under intense pressure from human use and climate change. Despite this, coasts – as a coherent ecological unit – have been poorly included in conservation plans, largely because they are inadequately delineated. There are usually gaps and overlaps at the edges of the separate terrestrial-, estuarine- and marine-realm maps, and often no clarity on which specific coastal boundary (e.g., high-water mark) was used, other than vaguely, ‘the coastline’. This particularly compromises conservation and management of ecotonal, intertidal ecosystems along realm-map seams because they are poorly defined and mapped. Therefore, a key step in advancing coastal conservation, assessment, planning and management is to generate a fine-scale ecosystem-type map that is seamless across realms. We undertook this for South Africa, aiming to delineate the ecotone into ecologically meaningful zones comprising structurally and functionally appropriate ecosystem types. We defined and mapped (at<1:3000) the ‘seashore’ as the land-sea interface between the dune scrub-thicket break and the back of the surf zone. The seashore is divided at the dune base into a landward ‘backshore’ and seaward ‘shore’, with the inherent dynamic variability included in the boundary delineation and constituent ecosystem types. Estuaries were also embedded into the map. Finally, we created rules for including adjacent terrestrial and marine ecosystem types in an ecologically determined coastal zone. We describe what tools this seashore integration and coastal delineation has unlocked, and how this places South Africa in a strong position to manage and conserve its coast
Assessing habitat type in KZN estuaries using VHR remote sensing imagery
(2014-10) Lück-Vogel, Melanie; Mbolambi, Cikizwa; Van Niekerk, Lara; Rautenbach, K; Adams, J
Within the presented project, we are comparing ecosystem and land cover classifications for the Greater St Lucia region derived from multispectral RapidEye (5m resolution), WorldView-2 (2m resolution), SPOT-6 (5.55m resolution) data with and without the additional use of LiDAR derived elevation data. Aiming for transferability of the classification approach, prior to classification, all images were corrected for atmospheric and radiometric effects. As ground reference, a GIS-derived wetland classification based on site visits and aerial photos from 2013 have been used. The respective wetland classes are aligned with existing habitat keys (e.g. from the South African National Biodiversity Assessment), which will enable implementation of our classification in existing management practices. For non-wetland areas, existing land cover classes from the SPOT-5 based KZN Land Cover from 2008 were used as reference. From both reference data sets, stratified random points for each class were extracted and part of it was used for the training of the classification and the remainder for the validation of the results. The same set of points was used for each satellite classification. This allowed an unbiased comparison of the classification results. Classification algorithms used are Maximum Likelihood and a non-parametric decision tree approach.
Assessing South Africa’s coastal climate change risk
(The African Climate Risks Conference (ACRC) Secretariat, 2019-10) Lück-Vogel, Melanie
In South Africa, about 40% of the people are living within 60km of the Oceans' coasts, and approximately 60% of the South African economy depends on coastal natural resources and trade infrastructure such as ports. These figures highlight the enormous importance of coastal environments and resources but also indicate the risk and vulnerability of coastal populations and assets in South Africa. To create a baseline of areas, settlements, people and assets at risk, the South African National Department for Environment, Fisheries and Forestry (DEFF), together with the German Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ) launched the Coastal Climate Change Vulnerability Assessment. This project assesses the risk of South Africa's coasts to storm and sea level rise related flooding and erosion, considering future climate scenarios. Under South Africa's National Climate Change Adaptation Strategy, and building on the National Coastal Assessment, this work will integrate high resolution remote sensing, multi-criteria GIS analysis, hydrodynamic modelling and expert knowledge based models to create spatially continuous hazard risk maps for the entire South African open coast and estuaries. An effective Decision Support Tool and training material will be created in collaboration with coastal managers and climate change adaptation responsibles at all government spheres.
Assessment of accuracy: systematic reduction of training points for maximum likelihood classification and mixture discriminant analysis (Gaussian and t-distribution)
(AJOL, 2018-09) Ritchie, Michaela C; Debba, Pravesh; Lück-Vogel, Melanie; Goodall, V
Remote sensing provides a valuable tool for monitoring land cover across large areas of land. A simple yet popular method for land cover classification is Maximum Likelihood Classification (MLC), which assumes a single normal distribution of the samples per class in the feature space. Mixture Discriminant Analysis (MDA) is a natural extension of MLC which can be used with varying distributions and multiple distributions per class, which simplifies the classification process tremendously. We compare the accuracies of MLC and MDA (using a Gaussian and t-distribution) as the number of training points are systematically reduced in order to simulate varying reference data availability conditions. The results show that the more robust t-distribution MDA performs comparatively with the Gaussian MDA and that both outperform MLC when sufficient training points are available. As the number of training points increases the MDA accuracies increase while the MLC accuracy stagnates. At very low numbers of training samples (ranging from 22 to 169 dependent on the class), there is more variability in terms of which method performs best.
Assessment of coastal Strandveld integrity using WorldView-2 imagery in False Bay, South Africa
(Elsevier, 2018-05) Lück-Vogel, Melanie; Mbolambi, C
The coastal zone as interface between land and sea faces much pressure from human activities. These pressures make it difficult for the coastal zones to fulfil their natural functions, so threatening the state of coastal environments and making them vulnerable to coastal disasters and degradation. This study aimed to test whether high resolution remote sensing imagery can be used to assess the integrity of coastal Strandveld vegetation at the high spatial resolution required as baseline information for local environmental management. The study focused on the Cape Flats Dune Strandveld vegetation in northern False Bay near Cape Town, South Africa. The approach modifies and adopts a method developed by Lück-Vogel et al. (2013) for a remote sensing derived habitat intactness assessment for the Sandveld region at South Africa¿s west coast. A regression analysis was performed on the eight spectral bands of two WorldView-2 images and five image derivatives to evaluate the most suitable bands for producing an ecosystem integrity index. Based on the results, only the RED and the NIR bands were required to perform a decision tree classification for the integrity classification, which significantly simplifies the application and opens the way for transfer to sensors with similar spectral bands. The overall accuracy of the results was 80.5% with a kappa value of 0.75. This means that this approach provides results accurate enough for coastal management and conservation applications at a local scale. A further finding is the importance of seasonality to delineate natural and alien vegetation accurately.
Assessment of coastal vegetation degradation in False bay, South Africa, using WV-2 imagery
(2017-05) Lück-Vogel, Melanie; Mbolambi, C
Vegetation of the coast around the world fulfils an important role. It acts as a buffer against the impacts from the oceans such as waves and wind and protects the coastal hinterland from wind-blown sand and coastal erosion. However, due to the increasing pressure those coastal environments are experiencing from urban encroachment, pollution and direct usage impacts e.g. through trespassing, the intactness of coastal vegetation frequently is being impaired. As a result, its capacity to function as a coastal protection decreases. Monitoring and management of coastal vegetation belts is therefore of utmost importance, in particular in urbanised and industrialised areas where the hinterland hosts infrastructure of enormous economic value and importance. However, the assessment of coastal vegetation condition is frequently difficult, due to the large extent and frequently inaccessibility of the zone. Furthermore, in many countries such as South Africa, there is a scarcity of coastal vegetation expert to perform the task locally. Therefore remote sensing holds a huge potential for coastal vegetation condition assessment. In the work presented here, the use of WorldView-2 imagery was investigated for assessing the intactness of a stretch of coastal vegetation in the Municipal area in Cape Town. In an object-based approach, a decision tree classification was developed to identify pristine, slightly, moderately and severely degraded Cape Flats Dune Strandveld vegetation as well as areas infested with alien Acacia species in the vicinity of Khayelitsha, one of the fastest growing settlements in the region. Overall accuracies of >80% show that the results hold promise for being a useful tool for assessing the degree of intactness of coastal Strandveld vegetation. This would provide a valuable tool for environmental managers for monitoring and managing natural coastal zones and their functionality.
Biodiversity monitoring in Europe: the EU FP7 EBONE project. European biodiversity observation NEtwork
(2008-09) Lück-Vogel, Melanie; Jongman, R
On April 1st, 2008 the EU FP7 project EBONE was launched. The aim of the project is the development of a (cost-effective) biodiversity data collection and monitoring system based on local field data, landscape metrics and remote sensing data to assess biodiversity at a regional, national and European level
Coastal flood risk
(2017-07) Lück-Vogel, Melanie
This presentation provided an overview of the degree of risk of coastal flooding in South Africa and demonstrated decision support tools for mitigation and adaptation.
Coastal remote sensing – towards integrated coastal research and management
(2012-10) Lück-Vogel, Melanie
The CSIR’s coastal systems research group conducts trans-disciplinary research from basic research up to the provision of policies and technical guidelines to prepare the coastal communities in South Africa and beyond with coastal protection and climate change adaptation solutions. Through this, we constructively support coastal managers to establish and maintain the sustainable use of our natural coastal resources and anthropogenic infrastructure for a safer future. Coastal remote sensing focusses on the seamless assessment of processes and dynamics from the shallow near-shore ocean up to the land. This capability is, however, very scarce and underdeveloped in South Africa and Africa.
Coastal vulnerability and climate change adaptation in South Africa: Remote sensing challenges and opportunities
(2022-05) Lück-Vogel, Melanie
South Africa is nestled between the Atlantic, the Southern and the Indian Ocean. Its coast is about 3000 km long and comprises 300 estuaries. Its coast stretches across three bioclimatic regions, namely the Cool Temperate South-West, a Warm Temperate South, and a Subtropical East. Accordingly, natural coastal vegetation includes desert-like sparse low shrubs on the west coast, dense evergreen fynbos shrublands in the south and subtropical thickets and coastal forests in the east. Being a very attractive environment for economic and leisure activities, the population in the coastal zone and the related land use pressure are extremely high: In South Africa, about 40% of the population lives within 60 km of the ocean and in 2011 an estimated 3.5 million South Africans resided within 5-7 km of a coastline, and 60% of these people were in the four densely populated metropolitan areas. Populations in coastal municipalities grew by approximately 1.8 million people between 2001 and 2011, and this rate, which far exceeds national growth rates in other areas, continues to date. This continued growth increasing forces urban sprawl into spaces affected by coastal dynamics and predicted climate impacts such as increased storm frequency and intensity and sea level rise. Both, human development pressure and predicted climate change impact alert to the need of effective integrated spatial planning and geospatial vulnerability assessments, as well as preservation of natural coastal environments and the services these ecosystems provide. South Africa has embraced this challenge and is conducting various projects that will provide information to guide decision making in these challenging and complex fields.
Coloniality of birds in the Kalahari – spatial distribution of trees and nests of the Sociable Weaver (Philetairus socius)
(Klaus Hess Publishers, Göttingen & Windhoek, 2010) Rösner, S; Giesselmann, UC; Meyer, J; Schwager, M; Wiegand, T; Lück-Vogel, Melanie; Brandl, R
The spatial distribution of suitable nest sites is a limiting resource for many colonial breeding animals. Therefore, we investigated and mapped the spatial distribution of nests of Sociable Weaver (Philetairus socius) to evaluate whether the size and distribution of suitable nesting trees influences the variability of colony size and spatial distribution of colonies in two study sites in the Kalahari, South Africa. We used spatial statistics to describe characteristics of point patterns. Nests of communal weavers were clustered at distances up to 300 m, whereas nests were distributed regularly at distances greater than 1,000 m. We therefore suggest that functional colonies of the social weaver consist of several nests on adjacent trees. From our analyses the question arises why sociable weavers establish sub-colonies instead of adding more chambers to the natal nest.
Comparative assessment of the GIS based bathtub model and an enhanced bathtub model for coastal inundation
(Springer, 2020-03) Williams, LL; Lück-Vogel, Melanie
Coastal zones are dynamic spaces where human activities and infrastructure are exposed to natural forces, climate change and extreme weather events such as storm surges. Coastal inundation is regarded as one of the most dangerous and destructive natural hazards, and while there are many studies to analyse these events, GIS based methods are limited. This research aimed at developing a GIS based enhanced Bathtub Model (eBTM) that improves on the widely used simple Bathtub Model (sBTM) to make it more appropriate to a storm surge related coastal inundation context. The eBTM incorporates beach slope, surface roughness and instils hydrological connectivity relevant for event scale coastal flooding, unlike the sBTM which only uses topographic elevation above sea level as input. For a test site in Cape Town, South Africa, inundation levels for 3 independent scenarios were calculated using the average spring tides level, extreme sea level for a 1-in-100-year storm and two sea-level rise scenarios. Each scenario was run on both the sBTM and the eBTM developed through this study. Comparing the results, the eBTM method overall produced more conservative inundation results and also produced less disconnected areas of (unrealistic) inundation. The eBTM also produces inundation water levels relative to structures, thus showing the potential for quantifying the coastal inundation risk to infrastructure, which is of relevance in the disaster response context. Additionally, the impact of using Digital Terrain Models (DTMs) instead of Digital Surface Models (DSM) on the inundation results was tested. The use of a DSM, including buildings and other objects, showed more realistic trajectories of the inundation water moving through the model area.
Compound flooding due to interaction of waves and river discharge at Breede Estuary, South Africa
(2022-05) Kupfer, S; Santamaria-Aguilar, S; Pieterse, Amy; Lück-Vogel, Melanie; Vafeidis, AT
Recent studies on compound flooding have considered the interaction of storm-tide and fluvial or pluvial flood drivers, whereas the contribution of waves to compound flooding so far has been neglected. In this study, we investigate compound flooding from waves, tides and river discharge at Breede Estuary, South Africa, using a hydrodynamic model. We estimate the contribution of extreme waves to compound flooding by analysing the driver interaction and by quantifying vertical and horizontal differences of flood characteristics. We further consider the additional effect of waves on flood timing and compare results of compound flood scenarios to scenarios in which single drivers are omitted. We find that flood characteristics are more sensitive to river discharge than to waves, particularly when the latter only coincide with high spring tides. When interacting with river discharge however, the contribution of waves is high, causing larger flood extents and higher water depths. With high wave intensities the first flooding can begin up to 12 hours earlier. Our findings provide insights on the magnitude and timing of compound flooding in an open South African estuary and demonstrate the need to account for the effects of waves during compound flooding in future flood impact assessments of similar coastal settings.
Considerations for kelp aquaculture on South Africa’s west coast: Geospatial analysis and research implications
(2024-08) Lück-Vogel, Melanie; Bolton, J; Rothman, MD; Bernatzeder, A; Macey, B; Cyrus, MD; Arendse, DCZ; Pillay, PJ; Brown-Webb, B
The commercial use of kelp continues to gain interest worldwide. While in some East Asian countries kelp farming has a long history, the kelp industry in South Africa is based on harvesting of kelp from natural kelp forests or by beach-cast collection. This study examined the potential for kelp aquaculture on South Africa’s west coast, focusing on the three indigenous species of kelp, Ecklonia maxima, Laminaria pallida and Macrocystis pyrifera. Geospatial analysis was used to identify and assess nine potentially suitable areas for kelp farming, based on natural habitat conditions, and examination of potential conflicts with other users and enabling land-use factors. An assessment of the market, technical and financial aspects of a kelp farming opportunity indicated that a 4 ha kelp farm, with longlines producing 750 to 1,000 t of fresh kelp per annum, could be viable as an integrated aquaculture activity adjacent to an existing mussel or oyster farm. We recommend a detailed feasibility study for kelp aquaculture in South Africa, with market and technical research, and financial modelling. Current seaweed industry legislation is mostly concerned with the wild resource, and there is a need for specific policies relating to seaweed aquaculture to facilitate growth of the industry.
Ecosystem pressures: Ecklonia maxima and Laminaria pallida
(2017-06) Dunga, LVA; Blamey, LK; Rothman, MD; Lück-Vogel, Melanie; Sink, K
This poster depicts the generation of a distribution map of Kelp forests on South Africa's coasts using Sentinel-2 Satellite imagery
Evaluating the Enhanced Bathtub Model for Coastal Flood Risk Assessment in Table Bay, South Africa
(2024-10) Lück-Vogel, Melanie; Van Coller, J; Williams, LL
Coastal zones are susceptible to increasing pressures from urban development and natural hazards, such as storm events, climate change, and rising sea levels. The GIS-based enhanced bathtub model (eBTM) enables the identification of areas at risk of flooding as a baseline for disaster management and coastal adaptation. This study aims to establish the methodological robustness of the eBTM for coastal flood modeling, by analyzing eight sites flooded during a recent storm event in Table Bay, Cape Town by comparing eBTM outputs with observed flood extent data collected after the storm. The validation showed that for 74% of the 332 validation points the spatial modeling error was <6m and for 56% below 3m. The root mean square error for the model was 4.88m, indicating an acceptable level of accuracy of the eBTM outputs for coastal risk assessments where more sophisticated models are unavailable.
Extraction of coastal ocean wave characteristics using remote sensing and computer vision technologies
(2017-05) Johnson, M; Lück-Vogel, Melanie
The coastal zone occurs at the interface of three major natural systems. These systems include the atmosphere, the ocean and the land surface. Ocean waves are among the most important forces shaping the world¿s coastlines. They drive environmental processes and human activity that occur within the coastal zone as well as on the open ocean. The assessment of wave characteristics, such as wave direction, wavelength, wave period and wave velocity, is critical to understanding coastal processes as baseline for better coastal management. However, monitoring and assessment of wave characteristics is challenging, given the high complexity of the ocean dynamics and large spatial extent. Traditionally, wave observation instruments such as wave buoys, wave poles, pressure transducers, inverted echo-sounders and current meters have been used to record ocean wave characteristics. Although delivering very accurate measurements, they only record punctual data. The work presented here is assessing whether optical imagery from the RapidEye satellite can be used to extract ocean wave characteristics such as wave direction, wavelength, wave period and wave velocity. If successful, the advantage of the proposed remote sensing-based approach would be the spatially continuous provision of wave characteristics for large areas, including the near-shore in a very cost-effective way.. As ground truth data for validating open ocean wave conditions are sparse, a lab test with simulated, controlled wave conditions was conducted to assess various approaches for the extraction of wave characteristics from remote sensing imagery. The techniques identified and developed under lab conditions are to be tested using RapidEye imagery on two study areas on the South African coast. Results are expected to significantly contribute to a more comprehensive understanding and monitoring of waves dynamics for better coastal planning.
Finite mixture models for sub-pixel coastal land cover classification
(2017-05) Ritchie, Michaela C; Lück-Vogel, Melanie; Debba, Pravesh; Goodall, V
Medium spatial resolution sensors (10-30 m pixel size) have been used for land cover classification and monitoring for decades. However, these sensors do not have the required resolution to detect coastal specific land cover classes and boundaries thereof as the spatial extent of the target features frequently is too small (e.g. bands of dune vegetation or the water line). Higher resolution satellite imagery which would be more suitable is, however, frequently too costly for operational coastal monitoring and management. A solution for this problem might be the spectral unmixing classification approach on medium resolution imagery (e.g. Landsat 8; Sentinel-2) which have no acquisition cost and are therefore affordable for operational use. Finite mixture models have been used to generate sub-pixel land cover classifications, however, traditionally this makes use of mixtures of normal distributions. However, these models fail to represent many land cover classes accurately, as these are usually not normally-distributed. A potential improvement could be to use models using other distributions which are more robust to non-normally distributed feature classes, such as the student-t distribution. This presentation aims to show the results of the fitting of various finite mixture models to land cover class signatures derived from radiometrically corrected WorldView-2 imagery of the Strand region of Cape Town. We aim to determine which finite mixture model best fits the signatures for this region. WorldView-2 imagery is used as it allows for the extraction of pixels with pure spectral signatures that is pixels containing one land cover class. However, the long-term goal of this project is to apply finite mixture models for the monitoring of land cover using medium resolution imagery (Landsat 8; Sentinel-2). If successful, this will provide a more robust land cover classification algorithm, which is affordable, for routine monitoring land cover in coastal environments.
Geographic information system data considerations in the context of the enhanced bathtub model for coastal inundation
(2022-10) Williams, LL; Lück-Vogel, Melanie
This study determines input data appropriateness for geographic information system-based enhanced bathtub model (eBTM) modeling of coastal inundation in an urban setting. Various tests were conducted concerning digital surface models (DSMs) to determine: (a) the highest appropriate resolution achievable from available LiDAR data and consider variations between derived sub-meter DSMs; (b) optimal DSM horizontal resolution for coastal inundation modeling based on “out-the-box” solutions; and (c) mechanisms to address the challenge presented by DSMs regarding overhanging structures for a study site in False Bay, South Africa. Results showed that while sub-meter DSMs are achievable, low point cloud densities may result in the misrepresentation of structures, which affects the inundation extents. High horizontal resolution DSMs are required for inundation modeling in an urban setting to account for narrow thoroughfares. Challenges posed by first return LiDAR depicting bridges as solid structures could be circumvented by modifying the input water source for the eBTM processing.
Geographic information system data considerations in the context of the enhanced bathtub model for coastal inundation
(2022-10) Williams, LL; Lück-Vogel, Melanie
This study determines input data appropriateness for geographic information system-based enhanced bathtub model (eBTM) modeling of coastal inundation in an urban setting. Various tests were conducted concerning digital surface models (DSMs) to determine: (a) the highest appropriate resolution achievable from available LiDAR data and consider variations between derived sub-meter DSMs; (b) optimal DSM horizontal resolution for coastal inundation modeling based on “out-the-box” solutions; and (c) mechanisms to address the challenge presented by DSMs regarding overhanging structures for a study site in False Bay, South Africa. Results showed that while sub-meter DSMs are achievable, low point cloud densities may result in the misrepresentation of structures, which affects the inundation extents. High horizontal resolution DSMs are required for inundation modeling in an urban setting to account for narrow thoroughfares. Challenges posed by first return LiDAR depicting bridges as solid structures could be circumvented by modifying the input water source for the eBTM processing.

Browsing by Author "Lück-Vogel, Melanie"

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