Automated Coastline Extraction Using the Very High Resolution WorldView (WV) Satellite Imagery and Developed Coastline Extraction Tool (CET)
Source abstract
Abstract
The accurate extraction of a coastline is necessary for various studies of coastal processes, as well as for the management and protection of coastal areas. Very high-resolution satellite imagery has great potential for coastline extraction; however, noises in spectral data can cause significant errors. Here, we present a newly developed Coastal Extraction Tool (CET) that overcomes such errors and allows accurate and time-efficient automated coastline extraction based on a combination of WorldView-2 (WV-2) multispectral imagery and stereo-pair-derived digital surface model (DSM). Coastline extraction is performed and tested on the Iž-Rava island group, situated within the Northern Dalmatian archipelago (Croatia). Extracted coastlines were compared to (a) coastlines extracted from state topographic map (1:25,000), and (b) coastline extracted by another available tool. The accuracy of the extracted coastline was validated with centimeter accuracy reference data acquired using a UAV system (Matrice 600 Pro + MicaSense RedEdge-MX). Within the study area, two small islets were detected that have not been mapped during the earlier coastline mapping efforts. CET proved to be a highly accurate coastline mapping technique that successfully overcomes spectral-induced errors. In future research, we are planning to integrate data obtained by UAVs infrared thermography (IRT) and in situ sensors, measuring sea and land surface temperatures (SST and LST), into the CET, given that this has shown promising results. Considering its accuracy and ease of use, we suggest that CET can be applied for automated coastline extraction in other large and indented coastal areas. Additionally, we suggest that CET could be applied in longitudinal geomorphological coastal erosion studies for the automated detection of spatio-temporal coastline displacement.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Coastal and Marine Dynamics · Coastal wetland ecosystem dynamics · Maritime and Coastal Archaeology
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Geography, University of Zadar, 23000 Zadar, Croatia
Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Athens, Greece
Funding
Croatian Science Foundation · Italy-Croatia cross-border cooperation program 2014-2020
References (83)
Show source-provided references
1. International Hydrographic Organization (IHO) (1974). Hydrographic Dictionary, International Hydrographic Organisation.
2. Quantitative analysis of shoreline changes at the Mediterranean Coast in Turkey10.1007/s10661-009-1057-8 ↗
3. Resistance and Resilience: Facing the Multidimensional Challenges in Coastal Areas10.2112/SI77-001.1 ↗
4. Coasts: The high-risk areas of the world10.1007/s11069-012-0215-4 ↗
5. Coastal flood damage and adaptation costs under 21st century sea-level rise10.1073/pnas.1222469111 ↗
6. Dynamic Resilience to Climate Change Caused Natural Disasters in Coastal Megacities Quantification Framework10.9734/BJECC/2013/2504 ↗
7. Neumann, B., Vafeidis, A.T., Zimmermann, J., and Nicholls, R.J. (2015). Future coastal population growth and exposure to sea-level rise and coastal flooding-a global assessment. PloS ONE, 10.10.1371/journal.pone.0118571 ↗
8. United Nations (2017, January 5–6). Factsheet: People and Oceans. Proceedings of the Ocean Conference, New York, NY, USA.
9. Schwartz, M. (2006). Encyclopedia of Coastal Science, Springer Science & Business Media.
10. Shoreline Definition and Detection: A Review10.2112/03-0071.1 ↗
11. Spatial Modeling and Analysis for Shoreline Change Detection and Coastal Erosion Monitoring10.1080/01490410151079891 ↗
12. Sunder, S., Ramsankaran, R., and Ramakrishnan, B. (2017). Inter-comparison of remote sensing sensing-based shoreline mapping techniques at different coastal stretches of India. Environ. Monit. Assess., 189.10.1007/s10661-017-5996-1 ↗
13. Roberts, J. (2020, January 15). What’s the Difference Between Coastline and Shoreline?. Available online: https://medium.com/@jenniferroberts050_60595/whats-the-difference-between-coastline-and-shoreline-982fcebf3ada.
14. Coastline extraction using high resolution WorldView-2 satellite imagery10.5721/EuJRS20144739 ↗
15. Coastline extraction from repeat high resolution satellite imagery10.1016/j.rse.2019.04.010 ↗
16. Coastline Extraction from High-Resolution Multispectral Images by Integrating Prior Edge Information With Active Contour Model10.1109/JSTARS.2019.2939297 ↗
17. Viaña-Borja, S.P., and Ortega-Sánchez, M. (2019). Automatic Methodology to Detect the Coastline from Landsat Images with a New Water Index Assessed on Three Different Spanish Mediterranean Deltas. Remote Sens., 11.10.3390/rs11182186 ↗
18. The reliability of shoreline change measurements from aerial photographs
19. Di, K., Ma, R., and Li, R. (2004). A Comparative Study of Shoreline Mapping Techniques. Res. Monogr. GIS, 53–60.10.1201/9781420023428.ch3 ↗
20. Shaw, J.B., Wolinsky, M.A., Paola, C., and Voller, V. (2008). An image-based method for shoreline mapping on complex coasts. Geophys. Res. Lett., 35.10.1029/2008GL033963 ↗
21. A geomatics data integration technique for coastal change monitoring10.1002/esp.1165 ↗
22. Coastal dynamic and shoreline mapping: Multi-sources spatial data analysis in Semarang Indonesia10.1007/s10661-007-9929-2 ↗
23. Shoreline mapping techniques
24. Coastline change detection using remote sensing10.1007/BF03325962 ↗
25. Human-driven coastline changes in the Adra River deltaic system, southeast Spain10.1016/j.geomorph.2010.02.004 ↗
26. Wang, X., Liu, Y., Ling, F., Liu, Y., and Fang, F. (2017). Spatio-Temporal Change Detection of Ningbo Coastline Using Landsat Time-Series Images during 1976–2015. ISPRS Int. J. Geo-Inf., 6.10.3390/ijgi6030068 ↗
27. Monitoring the coastline change of Hatiya Island in Bangladesh using remote sensing techniques10.1016/j.isprsjprs.2014.12.009 ↗
28. Nikolakopoulos, K., Kyriou, A., Koukouvelas, I., Zygouri, V., and Apostolopoulos, D. (2019). Combination of Aerial, Satellite, and UAV Photogrammetry for Mapping the Diachronic Coastline Evolution: The Case of Lefkada Island. ISPRS Int. J. Geo-Inf., 8.10.3390/ijgi8110489 ↗
29. Forgiarini, A.P.P., De Figueiredo, S.A., Calliari, L.J., Goulart, E.S., Marques, W., Trombetta, T.B., Oleinik, P.H., Guimarães, R.C., Arigony-Neto, J., and Salame, C.C. (2019). Quantifying the geomorphologic and urbanization influence on coastal retreat under sea level rise. Estuar. Coast. Shelf Sci., 230.10.1016/j.ecss.2019.106437 ↗
30. Zhang, L., and Ouyang, Z. (2019). Focusing on rapid urbanization areas can control the rapid loss of migratory water bird habitats in China. Glob. Ecol. Conserv., 20.10.1016/j.gecco.2019.e00801 ↗
31. Nile Delta exhibited a spatial reversal in the rates of shoreline retreat on the Rosetta promontory comparing pre- and post-beach protection10.1016/j.geomorph.2014.08.021 ↗
32. Lymburner, L., Bunting, P., Lucas, R., Scarth, P., Alam, I., Phillips, C., Ticehurst, C., and Held, A. (2020). Mapping the multi-decadal mangrove dynamics of the Australian coastline. Remote Sens. Environ., 238.10.1016/j.rse.2019.05.004 ↗
33. Rangel-Buitrago, N., Neal, W.J., and de Jonge, V.N. (2020). Risk assessment as tool for coastal erosion management. Ocean Coast. Manag., 186.10.1016/j.ocecoaman.2020.105099 ↗
34. Di, K., Ma, R., Wang, J., and Li, R. (2003, January 18–21). Coastal mapping and change detection using high-resolution IKONOS satellite imagery. Proceedings of the 2003 Annual National Conference on Digital Government Research, Boston, MA, USA.
35. Monitoring the changing position of coastlines using aerial and satellite image data: An example from the eastern coast of Trabzon, Turkey10.1007/s10661-008-0366-7 ↗
36. Coastline change detection with satellite remote sensing for environmental management of the Pearl River Estuary, China10.1016/j.jmarsys.2010.02.005 ↗
37. Dewi, R.S., Bijker, W., Stein, A., and Marfai, M.A. (2016). Fuzzy Classification for Shoreline Change Monitoring in a Part of the Northern Coastal Area of Java, Indonesia. Remote Sens., 8.10.3390/rs8030190 ↗
38. Coastline shift analysis in data deficient regions: Exploiting the high spatio-temporal resolution Sentinel-2 products10.1016/j.catena.2019.03.023 ↗
39. Remote sensing of coastlines: Detection, extraction and monitoring10.1080/01431160902926673 ↗
40. The rising politics of sea level: Demarcating territory in a vertically relative world10.1080/21622671.2019.1632219 ↗
41. Stoa, R. (2020). The Coastline Paradox. Rutgers Univ. Law Rev., 72.10.2139/ssrn.3445756 ↗
42. Morton, R.A. (1991). Accurate shoreline mapping: Past, present, and future. Coastal Sediments, American Society of Civil Engineers.
43. Liu, Y., Wang, X., Ling, F., Xu, S., and Wang, C. (2017). Analysis of Coastline Extraction from Landsat-8 OLI Imagery. Water, 9.10.3390/w9110816 ↗
44. Shoreline change mapping using remote sensing and GIS
45. Ding, Y., Yang, X., Jin, H., Wang, Z., Liu, Y., Liu, B., Zhang, J., Liu, X., Gao, K., and Meng, D. (2021). Monitoring Coastline Changes of the Malay Islands Based on Google Earth Engine and Dense Time-Series Remote Sensing Images. Remote Sens., 13.10.3390/rs13193842 ↗
46. Paravolidakis, V., Ragia, L., Moirogiorgou, K., and Zervakis, M.E. (2018). Automatic Coastline Extraction Using Edge Detection and Optimization Procedures. Geosciences, 8.10.3390/geosciences8110407 ↗
47. Guariglia, A., Buonamassa, A., Losurdo, A., Saladino, R., Trivigno, M.L., Zaccagnino, A., and Colangelo, A. (2009). A multisource approach for coastline mapping and identification of shoreline changes. Ann. Geophys., 49.10.4401/ag-3155 ↗
48. Guo, Q., Pu, R., Zhang, B., and Gao, L. (2016, January 10–15). A comparative study of coastline changes at Tampa Bay and Xiangshan Harbor during the last 30 years. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.10.1109/IGARSS.2016.7730351 ↗
49. Zanutta, A., Lambertini, A., and Vittuari, L. (2020). UAV Photogrammetry and Ground Surveys as a Mapping Tool for Quickly Monitoring Shoreline and Beach Changes. J. Mar. Sci. Eng., 8.10.3390/jmse8010052 ↗
50. Coastline lenghts and areas of islands in the croatian part of the Adriatic Sea determined from the topographic maps at the scale of 1: 25,000
51. State Geodetic Administration of the Republic of Croatia (2020, November 14). Data Catalog (Version 1.11), Available online: https://dgu.gov.hr/UserDocsImages//dokumenti/Pristup%20informacijama/Zakoni%20i%20ostali%20propisi/Ostalo//Katalog_podataka_DGU_2018_v11.pdf.
52. Faričić, J. (2012). Geografija Sjevernodalmatinskih Otoka [Geography of North Dalmatian islands], Školska Knjiga dd, Zadar Sveučilište u Zadru.
53. Eastern Adriatic Coast (EAC): Geomorphology and coastal vulnerability of a karstic coast10.2112/JCOASTRES-D-12-00136.1 ↗
54. Digital Globe Foundation (DGF) (2019, September 18). Imagery Grant Application Process. Available online: http://www.digitalglobefoundation.org.
55. Comparison of ATCOR Atmospheric and ELM Linear Empirical Correction Models Applied to WorldView-2 Images
56. Evaluation of a WorldView-2 image for soil salinity monitoring in a moderately affected irrigated area10.1117/1.JRS.10.026025 ↗
57. Multi-phenology WorldView-2 imagery improves remote sensing of savannah tree species
58. Aguilar, M.A., Novelli, A., Nemamoui, A., Aguilar, F.J., Lorca, A.G., and González-Yebra, Ó. (2018). Optimizing Multiresolution Segmentation for Extracting Plastic Greenhouses from WorldView-3 Imagery. Proceedings of the Handbook of Deep Learning Applications, Gabler.10.1007/978-3-319-59480-4_4 ↗
59. Li, H., Jing, L., and Tang, Y. (2017). Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion. Sensors, 17.10.3390/s17010089 ↗
60. Li, X., He, M., and Zhang, L. (2013, January 19–21). Hyperspherical color transform based pansharpening method for WorldView-2 satellite images. Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA), Melbourne, Australia.
61. Cheng, P., and Chaapel, C. (2010). Pan-sharpening and Geometric Correction: WorldView-2 Satellite. GeoInformatics, 13.
62. Assessing geometric accuracy of the orthorectification process from GeoEye-1 and WorldView-2 panchromatic images
63. ESRI (2021, May 23). Overview of Georeferencing. Available online: https://pro.arcgis.com/en/pro-app/help/data/imagery/overview-of-georeferencing.htm.
64. Using rational polynomial coefficients (RPC) to generate digital elevation models—A comparative study
65. Limitations of high resolution satellite stereo imagery for estimating canopy height in Australian tropical savannas
66. Domazetović, F., Šiljeg, A., Marić, I., and Jurišić, M. (2020, January 7–9). Assessing the Vertical Accuracy of Worldview-3 Stereo-extracted Digital Surface Model over Olive Groves. Proceedings of the 6th International Conference on Geographical Information Systems Theory, Applications and Management, Prague, Czech Republic.10.5220/0009471002460253 ↗
67. DJI (2020, November 15). MATRICE 600 PROSpecs. Available online: https://www.dji.com/hr/matrice600-pro/info#specs.
68. MicaSense (2020, November 15). RedEdge MX—The Sensor That Doesn’t Compromise. Available online: https://micasense.com/rededge-mx/.
69. Guidelines on the use of structure-from-motion photogrammetry in geomorphic research10.1002/esp.4637 ↗
70. Hexagon (2020, March 05). Extract Coastline from WorldView-2 & -3 Satellite Imagery. Available online: https://community.hexagongeospatial.com/t5/Spatial-Modeler-Tutorials/Extract-Coastline-from-WorldView-2-amp-3-satellite-imagery/ta-p/27448.
71. Himmelstoss, E.A., Henderson, R.E., Kratzmann, M.G., and Farris, A.S. (2018). Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide, USGS. Open-File Report 2018-1179.10.3133/ofr20181179 ↗
72. Combining series of multi-source high spatial resolution remote sensing datasets for the detection of shoreline displacement rates and the effectiveness of coastal zone protection measures10.1007/s11852-018-0591-3 ↗
73. Heiselberg, H. (2019). Aircraft and Ship Velocity Determination in Sentinel-2 Multispectral Images. Sensors, 19.10.3390/s19132873 ↗
74. UAS based 3D shoreline change detection of Jupiter Inlet Lighthouse ONA after Hurricane Irma10.1080/01431161.2019.1569792 ↗
75. A complete processing chain for ship detection using optical satellite imagery10.1080/01431161.2010.512310 ↗
76. Gianinetto, M., Aiello, M., Marchesi, A., Topputo, F., Massari, M., Lombardi, R., Banda, F., and Tebaldini, S. (2016, January 10–15). OBIA ship detection with multispectral and SAR images: A simulation for Copernicus security applications. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.10.1109/IGARSS.2016.7729311 ↗
77. Detecting migrant vessels in the Mediterranean Sea: Using Sentinel-2 images to aid humanitarian actions10.1016/j.actaastro.2018.11.012 ↗
78. Kurekin, A.A., Loveday, B.R., Clements, O., Quartly, G.D., Miller, P.I., Wiafe, G., and Agyekum, K.A. (2019). Operational Monitoring of Illegal Fishing in Ghana through Exploitation of Satellite Earth Observation and AIS Data. Remote Sens., 11.10.3390/rs11030293 ↗
79. Maxar (2020, November 12). Worldview-2. Datasheet. Available online: https://www.maxar.com/constellation.
80. Thermal Infrared Remote Sensing of Water Temperature in Riverine Landscapes10.1002/9781119940791.ch5 ↗
81. Extracting Shoreline from Satellite Imagery for GIS Analysis
82. Aerial infrared thermography in the surface waters contamination monitoring10.5004/dwt.2010.1988 ↗
83. DJI (2021, January 19). Zenmuse XT2—User Manual 1.0. Available online: https://www.dji.com/hr/downloads/products/zenmuse-xt2.