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Assessment and Quantification of the Accuracy of Low- and High-Resolution Remote Sensing Data for Shoreline Monitoring

Division of Applied Geology and Geophysics, Department of Geology, University of Patras, 26504 Rio, Greece
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ISPRS Int. J. Geo-Inf. 2020, 9(6), 391; https://doi.org/10.3390/ijgi9060391
Received: 13 May 2020 / Revised: 10 June 2020 / Accepted: 14 June 2020 / Published: 15 June 2020
Τhe accuracy of low-resolution remote sensing data for monitoring shoreline evolution is the main issue that researchers have been trying to overcome in recent decades. The drawback of the Landsat satellite archive is its spatial resolution, which is appropriate only for low-scale mapping. The present study investigates the potentialities and limitations of remote sensing data and GIS techniques in shoreline evolution modeling, with a focus on two major aspects: (a) assessing and quantifying the accuracy of low- and high-resolution remote sensing data for shoreline mapping; and (b) calculating the divergence in the forecasting of coastline evolution based on low- and high-resolution datasets. Shorelines derived from diachronic Landsat images are compared with the corresponding shorelines derived from high-spatial-resolution airphotos or Worldview-2 images. The accuracy of each dataset is assessed, and the possibility of forecasting shoreline evolution is investigated. Two sandy beaches, named Kalamaki and Karnari, which are located in Northwestern Peloponnese, Greece, are used as test sites. It is proved that the shorelines derived from the Landsat data present a displacement error of between 6 and 11 m. The specific data are not suitable for the shoreline forecasting procedure and should not be used in related studies, as they yield less accurate results for the two study areas in comparison with the high-resolution data. View Full-Text
Keywords: Landsat; shoreline; erosion; accretion; forecast; accuracy Landsat; shoreline; erosion; accretion; forecast; accuracy
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N. Apostolopoulos, D.; G. Nikolakopoulos, K. Assessment and Quantification of the Accuracy of Low- and High-Resolution Remote Sensing Data for Shoreline Monitoring. ISPRS Int. J. Geo-Inf. 2020, 9, 391.

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