Coastline Extraction Using Dual-Polarimetric COSMO-SkyMed PingPong Mode SAR Data

Nunziata, Ferdinando; Migliaccio, M.; Li, Xiaofeng; Ding, Xuhui

doi:10.1109/lgrs.2013.2247561

Cited by 66 publications

(40 citation statements)

References 21 publications

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“…Digital photogrammetry with aerial and satellite imagery have been widely used for the monitoring of shorelines/coastlines, and detecting their temporal and spatial changes in several locations around the world [1][2][3][4][5][6][7][8][9][10][11][12][13]. Besides the optical imagery based approach, the synthetic aperture radar (SAR) based multi-polarization and multi-incidence data have also been used by many researchers for water monitoring and mapping purposes [14][15][16][17]. Not only detection and mapping of the shorelines and water cover, but validation of the satellite based estimates are equally important.…”

Section: Introductionmentioning

confidence: 99%

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

et al. 2015

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Abstract:Monitoring of water cover and shorelines at a global scale is essential for better understanding climate change consequences and modern human disturbances. The level and turbidity of the surface water, and the background objects in which they interact with, vary significantly at a global scale. The existing water indices applicable to detection and extraction of water cover at local and regional scales cannot work efficiently everywhere in the globe. In this research, a new water index called Superfine Water Index (SWI) was developed for robust detection and discrimination of the surface water at a global scale using MODIS based multispectral data. The SWI was designed in such a way that it provides high contrast between the water and non-water areas. Achieving high contrast is vital for discriminating the surface water mixed with a variety of objects. The sensitivity analysis of the SWI demonstrated its high sensitivity to the surface water compared to the existing water indices. One single-layered global mosaic of a 90-percentile SWI image was used as a master image for global water cover mapping by reducing the large volume of MODIS data available between 2012 and 2014 globally. The random walker algorithm was applied in the SWI image with the support of reference training data for the extraction and mapping of water cover. This research produced an up-to-date global water cover map of the year 2013. OPEN ACCESSRemote Sens. 2015, 7 13808The performance of a new map was evaluated with a number of case studies and compared with existing maps. The supremacy of the SWI over the existing water indices, and high performance of the SWI based water map confirmed the reliability of the new water mapping methodology developed. We expect that this methodology can contribute to seasonal and annual change analysis of the global water cover as well.

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Section: Introductionmentioning

confidence: 99%

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

et al. 2015

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“…The camera was calibrated every time that it was removed from the waterproof housing (i.e., when profiler was operating). The calibration procedure consists of determining the relative position of a minimum of four points ("targets") in order to find the initial location and orientation of the camera relative to the calibration frame, as described by [63][64][65][66][67]. Since the position of instruments (captured in the video records) was known, eight "target" points were used, enhancing the quality of analysis.…”

Section: Influence On Swash Hydrodynamicsmentioning

confidence: 99%

Low Frequency Waves Detected in a Large Wave Flume under Irregular Waves with Different Grouping Factor and Combination of Regular Waves

Riefolo

Contestabile

Dentale

et al. 2018

Water

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This paper describes a set of experiments undertaken at Universitat Politècnica de Catalunya in the large wave flume of the Maritime Engineering Laboratory. The purpose of this study is to highlight the effects of wave grouping and long-wave short-wave combinations regimes on low frequency generations. An eigen-value decomposition has been performed to discriminate low frequencies. In particular, measured eigen modes, determined through the spectral analysis, have been compared with calculated modes by means of eigen analysis. The low frequencies detection appears to confirm the dependence on groupiness of the modal amplitudes generated in the wave flume. Some evidence of the influence of low frequency waves on runup and transport patterns are shown. In particular, the generation and evolution of secondary bedforms are consistent with energy transferred between the standing wave modes.

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“…The evolution of winds, waves and wind-driven sea circulation is of great applicative relevance for the observation of oceanographic phenomena (Bidlot et al, 2002). The offshore wind-wave simulations are accomplished by observations obtained by satellite images by active satellite-based microwave Synthetic Aperture Radar (SAR) (Benassai et al, 2012b(Benassai et al, , a, 2013, while the coastline monitoring can be surveyed by remote sensing acquisition (Nunziata et al, 2016(Nunziata et al, , 2014 or, on a shorter timescale, by RPAS (remotely piloted aircraft systems) and video monitoring systems (Casella et al, 2014). A possible feedback between wave-driven circulation, sediment processes and beach morphology is the occurrence of rip currents.…”

Section: Introductionmentioning

confidence: 99%

Rip current evidence by hydrodynamic simulations, bathymetric surveys and UAV observation

Benassai

Aucelli

Budillon

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The prediction of the formation, spacing and location of rip currents is a scientific challenge that can be achieved by means of different complementary methods. In this paper the analysis of numerical and experimental data, including RPAS (remotely piloted aircraft systems) observations, allowed us to detect the presence of rip currents and rip channels at the mouth of Sele River, in the Gulf of Salerno, southern Italy. The dataset used to analyze these phenomena consisted of two different bathymetric surveys, a detailed sediment analysis and a set of high-resolution wave numerical simulations, completed with Google Earth ™ images and RPAS observations. The grain size trend analysis and the numerical simulations allowed us to identify the rip current occurrence, forced by topographically constrained channels incised on the seabed, which were compared with observations.

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Coastline Extraction Using Dual-Polarimetric COSMO-SkyMed PingPong Mode SAR Data

Cited by 66 publications

References 21 publications

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

Low Frequency Waves Detected in a Large Wave Flume under Irregular Waves with Different Grouping Factor and Combination of Regular Waves

Rip current evidence by hydrodynamic simulations, bathymetric surveys and UAV observation

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