New Zealand coastline mapping using satellite imagery
Globally, coastlines are subject to significant environmental and anthropogenic pressure. Over the last decade these pressures have increased and are expected to increase further in response to greater coastal population density and climate change impacts (including increased storm activity and sea level rise) (World Ocean Review).
Figure 1. Examples of shoreline derived from satellite imagery for three different sites in New Zealand: Otama Beach , Raglan area, and Tiwai Beach (top to bottom). The extraction was undertaken using methods and tools by Vos et al., 2019 using open-access Sentinel-2 imagery.
“At MetOcean Solutions, we have developed a strong in house GIS expertise and a great understanding of the New Zealand coastline changes. We have undertaken many projects where the analysis of photogrammetry, aerial imagery, survey data was required to assess shoreline evolution at short and long-term. However this added capability now allows us to look at trends of coastal erosion and growth not only at a local scale but also for the New Zealand coastline as a whole.“
— MetOcean Consultancy Project Manager, Dr. Alexis Berthot.
To effectively manage and plan coastal use and adaptation, stakeholders need to understand historical coastline variability as well as have visibility on the existing state of the coastline. Historically this has required regular, labor-intensive beach surveys which, while extremely valuable, can be cost or logistics prohibitive. Significantly, the true value of these manual surveys is only recognised if they are undertaken frequently and widely.
Scientists and researchers have begun looking into ways to supplement and ‘fill in the blanks’ inherent in the manual collection of coastline survey data, with recent developments in the analysis and processing of available satellite earth imagery providing an unparalleled source of information for studying the dynamics of coastal change. Methods of shoreline detection from satellite imagery have significantly improved in recent years, with sub-pixel shoreline detection techniques being able to be applied to medium resolution satellite images and tidal correction (Vos et al., 2019ab, Vos et al., 2020, Bishop-Taylor et al., 2021, Abdelhady et al., 2022).
Because of the temporal and spatial coverage of the available satellite data, as well as the frequency at which new data becomes available, satellite earth observations can resolve both short-term (e.g., individual storms) to seasonal scales as well as annual to inter-annual variability. This type of analysis provides decadal coastline response datasets (10-30+ years and growing), giving a spatial and temporal coverage that manual surveys could only dream of achieving and provide valuable information for present and future coastal management decisions and planning.
Further, analysis of coastline response correlated with historical wave climates can be used tp maximize the effectiveness of the labor-intensive manual surveys by identifying and planning when and where manual surveys should be undertaken.
Satellite coastline monitoring has been undertaken for Australia’s coastlines to produce Digital Earth Australia Coastlines (see further information here and Bishop-Taylor et al., 2021), and now MetOcean Solutions has developed the same capabilities for New Zealand’s coastline, with the ability to have this service available for any location around New Zealand, or internationally.
Figure 2. Example of extracted shorelines over the period 2016-2021 at Raglan Beach, New Zealand. The extraction was undertaken using methods and tools by Vos et al., 2019 using open-access Sentinel-2 imagery.
Contact us at enquiries@metocean.co.nz for more information.
References
Abdelhady, H.U., Troy, C.D., Habib, A.F., & Manish, R. (2022). A Simple, Fully Automated Shoreline Detection Algorithm for High-Resolution Multi-Spectral Imagery. Remote. Sens., 14, 557.
Bishop-Taylor, R., Nanson, R.A., Sagar, S., & Lymburner, L. (2021). Mapping Australia's dynamic coastline at mean sea level using three decades of Landsat imagery. Remote Sensing of Environment. Available: https://doi.org/10.1016/j.rse.2021.112734
Bishop-Taylor, R., Sagar, S., Lymburner, L., Alam, I., & Sixsmith, J. (2019). Sub-Pixel Waterline Extraction: Characterising Accuracy and Sensitivity to Indices and Spectra. Remote. Sens., 11, 2984. Available: https://www.mdpi.com/2072-4292/11/24/2984
Vos, K., Harley, M.D., Splinter, K.D., Simmons, J.A., & Turner, I.L. (2019). Sub-annual to multi-decadal shoreline variability from publicly available satellite imagery. Coastal Engineering.
Vos, K., Splinter, K.D., Harley, M.D., Simmons, J.A., & Turner, I.L. (2019). CoastSat: A Google Earth Engin -enabled Python toolkit to extract shorelines from publicly available satellite imagery. Environ. Model. Softw., 122.
Vos, K., Harley, M.D., Splinter, K.D., Walker, A., & Turner, I.L. (2020). Beach Slopes From Satellite‐Derived Shorelines. Geophysical Research Letters, 47.