Next Article in Journal
The North Pacific Diatom Species Neodenticula seminae in the Modern and Holocene Sediments of the North Atlantic and Arctic
Previous Article in Journal
A Gas-Emission Crater in the Erkuta River Valley, Yamal Peninsula: Characteristics and Potential Formation Model
Previous Article in Special Issue
Seismic Exploration of the Deep Structure and Seismogenic Faults in the Ligurian Sea by Joint Multi Channel and Ocean Bottom Seismic Acquisitions: Preliminary Results of the SEFASILS Cruise
Open AccessArticle

Analysis of Very High Spatial Resolution Images for Automatic Shoreline Extraction and Satellite-Derived Bathymetry Mapping

1
Interreg Italia–Malta–Progetto: Pocket Beach Management & Remote Surveillance System, University of Messina, Via F. Stagno d’Alcontres, 31–98166 Messina, Italy
2
Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, Via F. Stagno d’Alcontres, 31–98166 Messina, Italy
3
GeoloGIS s.r.l. Spin Off, Via F. Stagno d’Alcontres, 31–98166 Messina, Italy
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in 2019 IMEKO TC-19 International Workshop on Metrology for the Sea; Muzirafuti, A.; Crupi, A.; Lanza, S.; Barreca, G.; Randazzo, G. Shallow water bathymetry by satellite image: A case study on the coast of San Vito Lo Capo Peninsula, Northwestern Sicily, Italy. In Proceedings of the 2019 IMEKO TC-19 International Workshop on Metrology for the Sea, Genoa, Italy, 3–5 October 2019.
Geosciences 2020, 10(5), 172; https://doi.org/10.3390/geosciences10050172
Received: 25 March 2020 / Revised: 20 April 2020 / Accepted: 5 May 2020 / Published: 8 May 2020
The amount of Earth observation images available to the public has been the main source of information, helping governments and decision-makers tackling the current world’s most pressing global challenge. However, a number of highly skilled and qualified personnel are still needed to fill the gap and help turn these data into intelligence. In addition, the accuracy of this intelligence relies on the quality of these images in times of temporal, spatial, and spectral resolution. For the purpose of contributing to the global effort aiming at monitoring natural and anthropic processes affecting coastal areas, we proposed a framework for image processing to extract the shoreline and the shallow water depth on GeoEye-1 satellite image and orthomosaic image acquired by an unmanned aerial vehicle (UAV) on the coast of San Vito Lo Capo, with image preprocessing steps involving orthorectification, atmospheric correction, pan sharpening, and binary imaging for water and non-water pixels analysis. Binary imaging analysis step was followed by automatic instantaneous shoreline extraction on a digital image and satellite-derived bathymetry (SDB) mapping on GeoEye-1 water pixels. The extraction of instantaneous shoreline was conducted automatically in ENVI software using a raster to vector (R2V) algorithm, whereas the SDB was computed in ArcGIS software using a log-band ratio method applied on the satellite image and available field data for calibration and vertical referencing. The results obtained from these very high spatial resolution images demonstrated the ability of remote sensing techniques in providing information where techniques using traditional methods present some limitations, especially due to their inability to map hard-to-reach areas and very dynamic near shoreline waters. We noticed that for the period of 5 years, the shoreline of San Vito Lo Capo sand beach migrated about 15 m inland, indicating the high dynamism of this coastal area. The bathymetric information obtained on the GeoEye-1 satellite image provided water depth until 10 m deep with R2 = 0.753. In this paper, we presented cost-effective and practical methods for automatic shoreline extraction and bathymetric mapping of shallow water, which can be adopted for the management and the monitoring of coastal areas. View Full-Text
Keywords: remote sensing; GeoEye-1; unmanned aerial vehicle (UAV); image processing; satellite-derived bathymetry (SDB); binary imaging analysis; coastal erosion; pocket beach; San Vito Lo Capo; climate change remote sensing; GeoEye-1; unmanned aerial vehicle (UAV); image processing; satellite-derived bathymetry (SDB); binary imaging analysis; coastal erosion; pocket beach; San Vito Lo Capo; climate change
Show Figures

Figure 1

MDPI and ACS Style

Randazzo, G.; Barreca, G.; Cascio, M.; Crupi, A.; Fontana, M.; Gregorio, F.; Lanza, S.; Muzirafuti, A. Analysis of Very High Spatial Resolution Images for Automatic Shoreline Extraction and Satellite-Derived Bathymetry Mapping. Geosciences 2020, 10, 172.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop