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

Autor: Marco Fontana, Stefania Lanza, Francesco Gregorio, Anselme Muzirafuti, Antonio Crupi, Maria Cascio, Giovanni Barreca, Giovanni Randazzo
Přispěvatelé: Universita degli Studi di Messina, Università degli studi di Catania [Catania], Université Moulay Ismail (UMI)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Earth observation
010504 meteorology & atmospheric sciences
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
0211 other engineering and technologies
Image processing
02 engineering and technology
01 natural sciences
Digital image
remote sensing
Bathymetry
14. Life underwater
[SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology
[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Shore
geography
geography.geographical_feature_category
Pixel
[SDE.IE]Environmental Sciences/Environmental Engineering
lcsh:QE1-996.5
Atmospheric correction
Orthophoto
lcsh:Geology
13. Climate action
General Earth and Planetary Sciences
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Geology
Zdroj: Geosciences
Volume 10
Issue 5
Geosciences, MDPI, 2020, 10 (5), pp.172. ⟨10.3390/geosciences10050172⟩
Geosciences, Vol 10, Iss 172, p 172 (2020)
ISSN: 2076-3263
DOI: 10.3390/geosciences10050172
Popis: 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&rsquo
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.
Databáze: OpenAIRE