Abstract
Coastal erosion is a worldwide hazard, the consequences of which can only be mitigated via thorough and efficient monitoring of erosion. This study aimed to employ remote sensing techniques on aerial photographs and Landsat TM/ETM+ imagery for the detection and monitoring of coastal erosion in False Bay, South Africa. Vegetation change detection as well as post-classification change detection were performed on the Landsat imagery. Furthermore, aerial photographs were analysed using the Digital Shoreline Analysis System (DSAS), which determines statistical differences in shoreline position over time. The results showed that while the resolution of the Landsat imagery was not sufficient to quantify and analyse erosion along the beach itself, the larger area covered by the satellite images enabled the identification of changes in landcover conditions leading to an increased susceptibility to erosion. Notably, the post-classification change detection indicated consistent increases in built-up areas, while sand dune, beach, and sand (not beach) decreased. NDVI differencing led to the conclusion that vegetation health was decreasing while reflective surfaces such as bare sand and roads were increasing. Both of these are indicative of an increased susceptibility to coastal erosion. Aerial photographs were used for detailed analysis of four focus areas and results indicated that coastal erosion was taking place at all four areas. The higher resolution available on the aerial photographs was vital for the quantification of erosion and sedimentation rates.
Highlights
Coastal erosion is a worldwide hazard, often resulting in damage to roads and other infrastructure
Past studies on the susceptibility of the South African coastline to coastal erosion (Palmer et al, 2011; Unterner et al, 2011) have focused on the creation of an index of erosion susceptibility for the coastline based on factors such as beach width and wave height, but have not incorporated change detection to determine where erosion and changes to erosion susceptibility are occurring
The use of remotely sensed data enables repetitive data acquisition, which is vital for the detection of land cover changes over time (Mouat et al, 1993). Both aerial photographs and Landsat TM imagery have been used in numerous change detection investigations (e.g. Althausen et al, 2003; Hayes and Sader, 2001; Kwarteng and Al-Ajmi, 1996; Smith and AbdelKader, 1988; Thampanya et al, 2006; van der Werff and van der Meer, 2008; Zhang et al, 2002, and others)
Summary
Coastal erosion is a worldwide hazard, often resulting in damage to roads and other infrastructure. Natural forces such as wind, waves and currents cause reshaping of coastlines (Phillips, 2008; Unterner et al, 2011), while anthropogenic effects are associated with coastline degradation (Siripong, 2010; Smith and Abdel-Kader, 1988; Unterner et al, 2011). Various aspects of coastal erosion have been assessed in previous investigations These included the creation of coastal vulnerability indices Past studies on the susceptibility of the South African coastline to coastal erosion (Palmer et al, 2011; Unterner et al, 2011) have focused on the creation of an index of erosion susceptibility for the coastline based on factors such as beach width and wave height, but have not incorporated change detection to determine where erosion and changes to erosion susceptibility are occurring
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