The Estimation and Evaluation of Shoreline Locations, Shoreline-Change Rates, and Coastal Volume Changes Derived from Landsat Images

Do, A.T.K.; de Vries, S., and Stive, M.J.F., 2019. The estimation and evaluation of shoreline locations, shoreline-change rates, and coastal volume changes derived from Landsat images. Journal of Coastal Research, 35(1), 56–71. Coconut Creek (Florida), ISSN 0749-0208. Shoreline-change data are of primary importance for understanding coastal erosion and deposition as well as for studying coastal morphodynamics. Shoreline extraction from satellite images has been used as a low-cost alternative and as an addition to traditional methods. In this work, satellite-derived shorelines and corresponding shoreline-change rates and changes in volumes of coastal sediments have been estimated and evaluated for the case of the data-rich North-Holland coast. This coast is globally unique for its long in situ monitoring record and provides a perfect case to evaluate the potential of shoreline mapping techniques. A total of 13 Landsat images and 233 observed cross-shore profiles (from the JAaRlijkse KUStmeting [JARKUS] database) between 1985 and 2010 have been used in this study. Satellite-derived shorelines are found to be biased in seaward direction relative to the JARKUS-derived shorelines, with an average ranging 8 m to 9 m over 25 years. Shoreline-change rates have been estimated using time series of satellite-derived shorelines and applying linear regression. The satellite-derived shoreline-change rates show a high correlation coefficient (R2 > 0.78) when compared with the JARKUS-derived shoreline-change rates over a period of 20 and 25 years. Volume changes were calculated from the satellite-derived shoreline-change rates using assumptions defining a closure depth. Satellite-derived volume changes also show a good agreement with JARKUS-based values. Satellite-derived shorelines compare better with in situ data on beaches that have intertidal zone widths ranging from one- to two-pixel sizes (30 m–60 m). The results show that the use of Landsat images for deriving shorelines, shoreline-change rates, and volume changes have accuracies comparable to observed JARKUS-based values when considering decadal scales of measurements. This shows the potential of applying Landsat images to monitor shoreline change and coastal volume change over decades.

[1]  Ad Reniers,et al.  On the accuracy of automated shoreline detection derived from satellite imagery: A case study of the sand motor mega-scale nourishment , 2018 .

[2]  Alfonso Fernández-Sarría,et al.  Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery , 2018, Remote. Sens..

[3]  Ana Cláudia Teodoro,et al.  Optical Satellite Remote Sensing of the Coastal Zone Environment — An Overview , 2016 .

[4]  Jesús Palomar-Vázquez,et al.  Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid-term coastal evolution indicator , 2016 .

[5]  Ángel Balaguer-Beser,et al.  Analysis of the shoreline position extracted from Landsat TM and ETM+ imagery , 2015 .

[6]  R. Holman,et al.  Shoreline variability from days to decades: Results of long‐term video imaging , 2015 .

[7]  Ali Selamat,et al.  Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery , 2014, Remote. Sens..

[8]  L. Ruiz,et al.  Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision , 2012 .

[9]  Wanglin Yan,et al.  Long-term coastal changes detection system based on remote sensing and image processing around an island , 2012, 2012 20th International Conference on Geoinformatics.

[10]  Fevzi Karsli,et al.  Automatic detection of shoreline change on coastal Ramsar wetlands of Turkey , 2011 .

[11]  Qiusheng Wu,et al.  Algorithmic Foundation and Software Tools for Extracting Shoreline Features from Remote Sensing Imagery and LiDAR Data , 2011, J. Geogr. Inf. Syst..

[12]  Jie Zhang,et al.  Coastline interpretation from multispectral remote sensing images using an association rule algorithm , 2010 .

[13]  Li Shen,et al.  Water body extraction from Landsat ETM+ imagery using adaboost algorithm , 2010, 2010 18th International Conference on Geoinformatics.

[14]  R. Gens Remote sensing of coastlines: detection, extraction and monitoring , 2010 .

[15]  Hsien-Kuo Chang,et al.  Estimation of shoreline position and change from satellite images considering tidal variation , 2009 .

[16]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[17]  K. S. Jayappa,et al.  Long and short-term shoreline changes along Mangalore Coast, India. , 2009 .

[18]  A. Bhattacharya,et al.  Shoreline change analysis and its application to prediction: A remote sensing and statistics based approach , 2009 .

[19]  Elena Ojeda,et al.  Shoreline and nearshore bar morphodynamics of beaches affected by artificial nourishment , 2008 .

[20]  Girish Gopinath,et al.  Change Detection Studies of Sagar Island, India, using Indian Remote Sensing Satellite 1C Linear Imaging Self-Scan Sensor III Data , 2007 .

[21]  Ian L Turner,et al.  The Performance of Shoreline Detection Models Applied to Video Imagery , 2007 .

[22]  S. Ekerci̇n,et al.  Coastline Change Assessment at the Aegean Sea Coasts in Turkey Using Multitemporal Landsat Imagery , 2007 .

[23]  Qihao Weng,et al.  A survey of image classification methods and techniques for improving classification performance , 2007 .

[24]  R. Saladino,et al.  A multisource approach for coastline mapping and identification of shoreline changes , 2006 .

[25]  Hanqiu Xu Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[26]  Giles M. Foody,et al.  Localized soft classification for super‐resolution mapping of the shoreline , 2006 .

[27]  Nitin K. Tripathi,et al.  Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data , 2005 .

[28]  Brian Voigt,et al.  Seasonal to Interannual Morphodynamics along a High-Energy Dissipative Littoral Cell , 2005 .

[29]  H. Liu,et al.  Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods , 2004 .

[30]  Giles M. Foody,et al.  Super-resolution mapping of the shoreline through soft classification analyses , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[31]  Michele Capobianco,et al.  Variability of shore and shoreline evolution , 2002 .

[32]  K. Wijnberg Environmental controls on decadal morphologic behaviour of the Holland coast , 2002 .

[33]  S. Sader,et al.  Detection of forest harvest type using multiple dates of Landsat TM imagery , 2002 .

[34]  S. Leatherman,et al.  The High Water Line as Shoreline Indicator , 2002 .

[35]  Stuart R. Phinn,et al.  Optimizing Remotely Sensed Solutions for Monitoring, Modeling, and Managing Coastal Environments , 2000 .

[36]  J. Rosati,et al.  Formulation of Sediment Budgets at Inlets , 1999 .

[37]  K. White,et al.  Monitoring changing position of coastlines using Thematic Mapper imagery, an example from the Nile Delta , 1999 .

[38]  Mark B. Gravens,et al.  Regional Sediment Budget for Fire Island to Montauk Point, New York, USA , 1999 .

[39]  Robert J. Nicholls,et al.  SPATIAL AND TEMPORTAL BEHAVIOR OF DEPTH OF CLOSURE ALONG THE HOLLAND COAST , 1999 .

[40]  J. Rosati,et al.  Estimation of Uncertainty in Coastal-Sediment Budgets at Inlets , 1998 .

[41]  I. J. Davenport,et al.  Interpolation of an intertidal digital elevation model from heighted shorelines: a case study in the Western Wash , 1997 .

[42]  L. Rijn Sediment transport and budget of the central coastal zone of Holland , 1997 .

[43]  S. K. McFeeters The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[44]  F.A.J. Minneboo Jaarlijkse kustmetingen: Richtlijnen voor de inwinning, bewerking, en opslag van gegevens van jaarlijkse kustmetingen , 1995 .

[45]  P. Lawrence Natural hazards of shoreline bluff erosion: a case study of Horizon View, Lake Huron , 1994 .

[46]  B. Bauer,et al.  Coastal geomorphology through the looking glass , 1993 .

[47]  Patrick T. Taylor,et al.  Shoreline changes along the Rosetta-Nile Promontory: Monitoring with satellite observations , 1991 .

[48]  R. Hallermeier USES FOR A CALCULATED LIMIT DEPTH TO BEACH EROSION , 1978 .

[49]  E. Reis,et al.  Remote sensing technologies for the assessment of marine and coastal ecosystems , 2016 .

[50]  Paul Russell,et al.  Evaluating shoreline identification using optical satellite images , 2015 .

[51]  Rasmus Fensholt,et al.  Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery , 2014 .

[52]  Zhiqiang Du,et al.  Estimating surface water area changes using time-series Landsat data in the Qingjiang River Basin, China , 2012 .

[53]  Fevzi Karsli,et al.  Spatio-temporal shoreline changes along the southern Black Sea coastal zone , 2011 .

[54]  U. Bhosle,et al.  Atmospheric Correction of Remotely Sensed Images in Spatial and Transform Domain , 2011 .

[55]  E. Robert Thieler,et al.  The Digital Shoreline Analysis System (DSAS) Version 4.0 - An ArcGIS extension for calculating shoreline change , 2009 .

[56]  U. S. Army Concepts in Sediment Budgets , 2008 .

[57]  M. Noernberg Spatial-temporal Monitoring of the Paranaguá Bay Inlet Margins Using Multispectral Landsat-TM Images , 2003 .

[58]  Robert B. Nairn,et al.  SPATIAL AND TEMPORAL CONSIDERATION FOR CALCULATING SHORELINE CHANGE RATES IN THE GREAT LAKES BASIN , 2003 .

[59]  K. Kingston,et al.  Applications of complex adaptive systems approaches to coastal systems , 2003 .

[60]  C. Fletcher,et al.  Waikiki: Historical analysis of an engineered shoreline , 2003 .

[61]  P. Frazier,et al.  Water body detection and delineation with Landsat TM data. , 2000 .

[62]  D. Knoester De morfologie van de Hollandse kustzone (analyse van het Jarkusbestand 1964-1986) , 1990 .

[63]  J. A. Schell,et al.  Monitoring vegetation systems in the great plains with ERTS , 1973 .