Geomatics and Environmental Engineering, vol. 17, no. 3

Issue

Vol. 17 No. 3 (2023): Geomatics and Environmental Engineering

Date Log

Submitted
Sep 7, 2022
Accepted
Feb 1, 2023
Published
Feb 16, 2023
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

A GIS Procedure to Assess Shoreline Changes over Time Using Multi-temporal Maps: An Analysis of a Sandy Shoreline in Southern Italy over the Last 100 Years

https://doi.org/10.7494/geom.2023.17.3.107
Massimiliano Pepe
Department of Engineering and Geology (InGeo), “G. d’Annunzio” University of Chieti-Pescara, Pescara, Italy
https://orcid.org/0000-0003-2508-5066
Domenica Costantino
Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Polytechnic of Bari
https://orcid.org/0000-0002-1909-9261
Vincenzo Saverio Alfio
Dipartimento di Ingegneria Civile, Ambientale, del Territorio, Edile e di Chimica, Polytechnic of Bari
https://orcid.org/0000-0003-4816-8913

Corresponding Author(s) : Vincenzo Saverio Alfio

vincenzosaverio.alfio@poliba.it

Geomatics and Environmental Engineering, Vol. 17 No. 3 (2023): Geomatics and Environmental Engineering

Abstract

The aim of the paper is to identify a methodology capable of assessing shoreline changes through a geomatic approach based on the use of GIS (Geographic Information System) software. The paper describes a case study that reports the evolution of a coastline over a period of more than 100 years using medium and large-scale metric maps available in different periods. In fact, the coastlines were obtained from the source maps of the Italian Cadastre (dated 1890), from numerical cartography available on the coastline and acquired in different period at scales 1:5000 and 1:2000 and, more recently, from the Google Earth Pro platform. To analyse the evolution of the coastline a new procedure has been performed which is based on the use of GIS software, in particular a plugin called DSAS that allows the evaluation of the changes in the coastline and also obtains a statistical analysis of its evolution. The results showed the ease and applicability of the method in determining the evolution of the coastline and the strong erosion of a stretch of coastline with important socio-economic consequences and repercussions was highlighted in the analysed case study.

Keywords

GIS variance georeferencing Google Earth Pro DSAS shoreline
Pepe, M., Costantino, D., & Alfio, V. S. (2023). A GIS Procedure to Assess Shoreline Changes over Time Using Multi-temporal Maps: An Analysis of a Sandy Shoreline in Southern Italy over the Last 100 Years. Geomatics and Environmental Engineering, 17(3), 107–134. https://doi.org/10.7494/geom.2023.17.3.107
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. Terefenko P., Furmańczyk K., Łapiński M.: Analiza rzeźby brzegu na podstawie numerycznego modelu terenu [Digital terrain model-based coast relief analysis]. Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol. 18b, 2008, pp. 581–588.
  2. Dudzińska-Nowak J.: Przydatność skanowania laserowego do badań strefy brzegowej południowego Bałtyku [Suitability of laser scanning in the southern Baltic coastal zone research]. Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol. 17a, 2007, pp. 179–187.
  3. Dudzińska-Nowak J.: Określenie tendencji rozwojowych brzegu na podstawie badań teledetekcyjnych [Trends in coast development as determined by remote sensing research]. Archiwum Fotogrametrii, Kartografii i Teledetekcji, vol. 18a, 2008, pp. 99–109.
  4. Paravolidakis V., Moirogiorgou K., Ragia L., Zervakis M., Synolakis C.: Coastline extraction from aerial images based on edge detection. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. III-8, 2016, pp. 153–158. https://doi.org/10.5194/isprs-annals-III-8-153-2016.
  5. Costantino D., Pepe M., Dardanelli G., Baiocchi V.: Using optical Satellite and aerial imagery for automatic coastline mapping. Geographia Technica, vol. 15(2), 2020, pp. 171–190. https://doi.org/10.21163/GT_2020.152.17.
  6. Alesheikh A.A., Ghorbanali A., Nouri N.: Coastline change detection using remote sensing. International Journal of Environmental Science & Technology, vol. 4(1), 2007, pp. 61–66. https://doi.org/10.1007/BF03325962.
  7. Wu W.: Coastline evolution monitoring and estimation – a case study in the region of Nouakchott, Mauritania. International Journal of Remote Sensing, vol. 28(24), 2007, pp. 5461–5484. https://doi.org/10.1080/01431160701227612.
  8. Pardo-Pascual J.E., Almonacid-Caballer J., Ruiz L.A., Palomar-Vázquez J.: Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment, vol. 123, 2012, pp. 1–11. https://doi.org/10.1016/j.rse.2012.02.024.
  9. Parente C., Pepe M.: Bathymetry from worldview-3 satellite data using radiometric band ratio. Acta Polytechnica, vol. 58(2), 2018, pp. 109–117. https://doi.org/10.14311/AP.2018.58.0109.
  10. Nikolakopoulos K.G., Kozarski D., Kogkas S.: Coastal areas mapping using UAV photogrammetry. [in:] Michel U., Schulz K., Nikolakopoulos K.G., Civco D. (eds.), Earth Resources and Environmental Remote Sensing/GIS Applications VIII, Proceedings of SPIE, vol. 10428, Society of Photo-Optical Instrumentation Engineers, Bellingham 2017, 104280O. https://doi.org/10.1117/12.2278121.
  11. Özcan O., Özcan O.: Multi-temporal UAV based repeat monitoring of rivers sensitive to flood. Journal of Maps, vol. 17(3), 2020, pp. 163–170. https://doi.org/10.1080/17445647.2020.1820387.
  12. Pepe M., Alfio V.S., Costantino D.: UAV platforms and the SfM-MVS approach in the 3D surveys and modelling: A review in the cultural heritage field. Applied Sciences, vol. 12(24), 2022, 12886. https://doi.org/10.3390/app122412886.
  13. Ruggiero P., Kaminsky G.M., Gelfenbaum G., Voigt B.: Seasonal to interannual morphodynamics along a high-energy dissipative litoral cell. Journal of Coastal Research, vol. 21(3), 2005, pp. 553–578. https://doi.org/10.2112/03-0029.1.
  14. Gonçalves R., Awange J., Krueger C.: GNSS-based monitoring and mapping of shoreline position in support of planning and management of Matinhos/PR (Brazil). Journal of Global Positioning Systems, vol. 11(1), 2012, pp. 156–168.
  15. Currier K.: Mapping with strings attached: Kite aerial photography of Durai Island, Anambas Islands, Indonesia. Journal of Maps, vol. 11(4), 2015, pp. 589–597. https://doi.org/10.1080/17445647.2014.925839.
  16. Costantino D., Settembrini F., Pepe M., Alfio V.S.: Develop of new tools for 4D monitoring: Case study of Cliff in Apulia Region (Italy). Remote Sensing, vol. 13(9), 2021, 1857. https://doi.org/10.3390/rs13091857.
  17. Lira C.P., Silva A.N., Taborda R., de Andrade C.F.: Coastline evolution of Portuguese low-lying sandy coast in the last 50 years: an integrated approach. Earth System Science Data, vol. 8(1), 2016, pp. 265–278. https://doi.org/10.5194/essd-8-265-2016.
  18. Yu Y., Zhang Z., Shokr M., Hui F., Cheng X., Chi Z., Heil P., Chen Z.: Automatically extracted Antarctic coastline using remotely-sensed data: an update. Remote Sensing, vol. 11(16), 2019, 1844. https://doi.org/10.3390/rs11161844.
  19. Wang K.: Evolution of Yellow River Delta coastline based on remote sensing from 1976 to 2014, China. Chinese Geographical Science, vol. 29(2), 2019, pp. 181–191. https://doi.org/10.1007/s11769-019-1023-5.
  20. Terres de Lima L., Fernández-Fernández S., de Almeida Espinoza J.M., Albuquerque M.D.G., Bernardes C.: End Point Rate tool for QGIS (EPR4Q): Validation using DSAS and AMBUR. ISPRS International Journal of GeoInformation, vol. 10(3), 2021, 162. https://doi.org/10.3390/ijgi10030162.
  21. Jackson C.W.: Quantitative Shoreline Change Analysis of an Inlet-Influenced Transgressive Barrier System; Figure Eight Island, North Carolina. University of North Carolina at Wilmington, Wilmington, NC, USA 2004 [M.Sc. thesis].
  22. Hoeke R.K., Zarillo G.A., Synder M.: A GIS-based tool for extracting shoreline positions from aerial imagery (BeachTools). https://apps.dtic.mil/sti/citations/ADA588790 [access: 3.04.2022].
  23. Himmelstoss E.: DSAS 4.0 – Installation Instructions and User Guide. [in:] Thieler E.R., Himmelstoss E., Zichichi J., Ergul A. (eds.), The Digital Shoreline Analysis System (DSAS) Version 4.0 – An ArcGIS Extension for Calculating Shoreline Change, U.S. Geological Survey Open-File Report 2008-1278, U.S. Geological Survey, Reston, Virginia 2009. https://doi.org/10.3133/ofr20081278.
  24. Ding Y., Yang X., Jin H., Wang Z., Liu Y., Liu B., Zhang J. et al.: Monitoring coastline changes of the Malay Islands based on Google Earth Engine and dense time-series remote sensing images. Remote Sensing, vol. 13(19), 2021, 3842. https://doi.org/10.3390/rs13193842.
  25. Jackson C.W., Alexander C.R., Bush D.M.: Application of the AMBUR R package for spatio-temporal analysis of shoreline change: Jekyll Island, Georgia, USA. Computers & Geosciences, vol. 41, 2012, pp. 199–207. https://doi.org/10.1016/j.cageo.2011.08.009.
  26. Song Y., Shen Y., Xie R., Li J.: A DSAS-based study of central shoreline change in Jiangsu over 45 years. Anthropocene Coasts, vol. 4(1), 2021, pp. 115–128. https://doi.org/10.1139/anc-2020-0001.
  27. Dewi R.S.: Monitoring long-term shoreline changes along the coast of Semarang. IOP Conference Series: Earth and Environmental Science, vol. 284, 2019, 012035. https://doi.org/10.1088/1755-1315/284/1/012035.
  28. Zonkouan B.R.V., Bachri I., Beda A.H.J., N’Guessan K.A.M.: Monitoring spatial and temporal scales of shoreline changes in Lahou-Kpanda (Southern Ivory Coast) using Landsat data series (TM, ETM+ and OLI). Geomatics and Environmental Engineering, vol. 16(1), 2022, pp. 145–158. https://doi.org/10.7494/geom.2022.16.1.145.
  29. Quang D.N., Ngan V.H., Tam H.S., Viet N.T., Tinh N.X., Tanaka H.: Long-term shoreline evolution using DSAS technique: A case study of Quang Nam province, Vietnam. Journal of Marine Science and Engineering, vol. 9(10), 2021, 1124. https://doi.org/10.3390/jmse9101124.
  30. Nassar K., Mahmod W.E., Fath H., Masria A., Nadaoka K., Negm A.: Shoreline change detection using DSAS technique: Case of North Sinai coast, Egypt. Marine Georesources & Geotechnology, vol. 37(1), 2019, pp. 81–95. https://doi.org/10.1080/1064119X.2018.1448912.
  31. Das S.K., Sajan B., Ojha Ch., Soren S.: Shoreline change behavior study of Jambudwip island of Indian Sundarban using DSAS model. The Egyptian Journal of Remote Sensing and Space Science, vol. 24(3), 2021, pp. 961–970. https://doi.org/10.1016/j.ejrs.2021.09.004.
  32. Kuleli T.: Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey. Environmental Monitoring and Assessment, vol. 167(1), 2010, pp. 387–397. https://doi.org/10.1007/s10661-009-1057-8.
  33. Khouakhi A., Snoussi M.: GIS-based vulnerability assessment to sea level rise of Al Hoceima Bay (Moroccan Mediterranean): towards an integrated coastal zone management (ICZM). AGU Fall Meeting Abstracts, 2013.
  34. Armenio E., De Serio F., Mossa M., Nobile B., Petrillo A.F.: Investigation on coastline evolution using long-term observations and numerical modelling. [in:] The Proceedings of the Twenty-seventh (2017) International Ocean and Polar Engineering Conference: San Francisco, California, June 25–30, 2017, International Society of Ocean and Polar Engineers (ISOPE), 2017, pp. 1556–1564.
  35. Cinque A., Guida F., Russo F., Santangelo N.: Dati cronologici e stratigrafici su alcuni depositi continentali della Piana del Sele (Campania): i «Conglomerati di Eboli». Geografia Fisica e Dinamica Quaternaria, vol. 11, 1988, pp. 39–44.
  36. Hofmann-Wellenhof B., Moritz H.: Physical Geodesy. Springer, Vienna 2006. https://doi.org/10.1007/978-3-211-33545-1.
  37. Radicioni F., Stoppini A.: Geodetic data in a multipurpose regional GIS. [in:] Mussio L., Forlani G., Crosilla F. (eds.), Data Acquisition and Analysis for Multimedia GIS, CISM International Centre for Mechanical Sciences, vol. 365, Springer, Vienna 1996, pp. 247–257. https://doi.org/10.1007/978-3-7091-2684-4_20.
  38. Luhmann T., Robson S., Kyle S., Harley I.: Close Range Photogrammetry: Principles, Techniques and Applications. Whittles Publishing, Dunbeath, Scotland 2006.
  39. Cina A., Manzino A.M., Manzino G.: Recovery of cadastral boundaries with GNSS equipment. Survey Review, vol. 48(350), 2016, pp. 338–346. https://doi.org/10.1179/1752270615Y.0000000007.
  40. Brovelli M.A., Minghini M.: Georeferencing old maps: a polynomial-based approach for Como historical cadastres. e-Perimetron, vol. 7(3), 2012, pp. 97–110.
  41. CISIS. ConveRgo, Version 2.04; CISIS: Roma, Italy, 2012. https://www.cisis.it/?page_id=3214 [access: 29.03.2022].
  42. Hu Q., Wu W., Xia T., Yu Q., Yang P., Li Z., Song Q.: Exploring the use of Google Earth imagery and object-based methods in land use/cover mapping. Remote Sensing, vol. 5(11), 2013, pp. 6026–6042. https://doi.org/10.3390/rs5116026.
  43. Maling D.H.: Coordinate Systems and Map Projections. 2nd ed. Elsevier, 2013.
  44. Gomarasca M.A.: Basics of Geomatics. Springer, Dordrecht 2009. https://doi.org/10.1007/978-1-4020-9014-1.
  45. Himmelstoss E.A., Henderson R.E., Kratzmann M.G., Farris A.S.: Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide. U.S. Geological Survey Open-File Report 2018-1179, U.S. Geological Survey, Reston, Virginia 2018. https://doi.org/10.3133/ofr20181179.
  46. Alberico I., Amato V., Aucelli P.P.C., D’Argenio B., Di Paola G., Pappone G.: Historical shoreline change of the Sele Plain (Southern Italy): The 1870–2009 time window. Journal of Coastal Research, vol. 28(6), 2012, pp. 1638–1647. https://doi.org/10.2112/JCOASTRES-D-10-00197.1.
  47. Pappone G., Aucelli P.P.C., Aberico I., Amato V., Antonioli F., Cesarano M., Pelosi N.: Relative sea-level rise and marine erosion and inundation in the Sele river coastal plain (Southern Italy): scenarios for the next century. Rendiconti Lincei, vol. 23, 2012, pp. 121–129. https://doi.org/10.1007/s12210-012-0166-4.
Read More
Author biographies is not available.
Download this PDF file
PDF
Statistic
Read Counter : 285 Download : 237

Downloads

Download data is not yet available.