EGU26-15320, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-15320
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 05 May, 15:20–15:30 (CEST)
 
Room -2.15
Comparison Assessment of Satellite-derived Shorelines using Coastsat Environment and Remote Sensing Technique
Cherie Pribadi1, Riccardo Briganti2, and Panagiotis Psimoulis1
Cherie Pribadi et al.
  • 1Nottingham Geospatial Institute (NGI), University of Nottingham, Nottingham, United Kingdom of Great Britain – England, Scotland, Wales (panagiotis.psimoulis@nottingham.ac.uk)
  • 2Environmental Fluid Mechanics and Geoprocesses, University of Nottingham, Nottingham, United Kingdom of Great Britain – England, Scotland, Wales (riccardo.briganti@nottingham.ac.uk)

The coastal zone is one of the most dynamic and high energy systems on Earth, where wind, waves and tides cause geophysical processes such as erosion, deposition and flooding to occur. Monitoring shoreline position is crucial to manage and protect coastal region to safeguard economic and social interest as many people rely on coastal areas for tourism and their livelihoods. Satellite-derived shorelines change rate carried out the significant erosion and accretion along the beaches for assessing the long-term sustainability of coastal development and effective spatial planning. Earth observation (EO) utilisation has been provided moderate spatial resolution (10-30 m) for investigating shoreline movement at regional to global scales. In this study, we delineate the shorelines over three years period of 2022 to 2024 using two distinctive methods – coastsat environment and remote sensing techniques by applying Normalised Difference Water Index (NDWI) algorithm with Sentinel-2 satellite imagery data. Then, we assess the change rates of coastal erosion and accretion using Digital Shoreline Analysis System (DSAS) tool. The significance of shoreline extractions using coastsat environment represent the accretion patterns along the beaches with the average of change rates accounted for 2.54 m/year and 2.65 m/year for Linear Regression Rate (LRR) and End Point Rate (EPR) method, respectively. Meanwhile, the extracted shorelines using NDWI algorithm show the shoreline change rates of -0.87 m/year (LRR) and -0.46 m/year (EPR), which these rates are categorised as a coastal erosion. Moreover, the shoreline distance change rates are also different with the value of 5.27 m (coastsat) and -1.11 m (remote sensing technique), those values were calculated using Net Shoreline Movement (NSM) statistic method. This difference results in shoreline change position might be caused by different process, whereas extracting the shoreline using coastsat that implement the tidal correction and NDWI was applied without tide correction. The other limitation of optical-satellite imagery is the cloud cover can affect the shoreline results followed by its change rates.

How to cite: Pribadi, C., Briganti, R., and Psimoulis, P.: Comparison Assessment of Satellite-derived Shorelines using Coastsat Environment and Remote Sensing Technique, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15320, https://doi.org/10.5194/egusphere-egu26-15320, 2026.