An efficient protocol for accurate and massive shoreline definition from mid-resolution satellite imagery

Sánchez-García, Elena; Palomar-Vázquez, Jesús; Pardo-Pascual, Josep E.; Almonacid-Caballer, Jaime; Cabezas-Rabadán, Carlos; Gómez-Pujol, Lluı́s

doi:10.1016/j.coastaleng.2020.103732

Cited by 54 publications

(57 citation statements)

References 65 publications

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“…Working in parallel after the completion of the works in Chapter 4 of the thesis being Almonacid-Caballer, et al (2016), Pardo-Pascual et al (2018), Sánchez-García et al (2020) completed the evaluation by demonstrating with which parameters and bands or indexes of the satellite images, the algorithm (presented as SHOREX) achieved greatest accuracy. It was seen that the algorithm seemed more accurate in the final shoreline detection when working with small neighborhoods.…”

Section: Tesis Doctoralmentioning

confidence: 99%

“…Accordingly, the use of a threshold input line per image was changed -this step also slowed down the process -and a unique digitalized or available shoreline for the whole set of images was used. While the reliability of the line was still uncertain, the protocol (presented in the last work of Chapter 4, Sánchez-García et al, 2020) consists of working first with large neighborhoods and ensuring that the real shoreline was contained, and then continuing with a second iteration where smaller neighborhoods would define accurately the sub-pixel shoreline. In this case, a centered interpolation is first used and then the least squares method is used to define the land-water surface over an upsampled satellite image.…”

Section: Tesis Doctoralmentioning

confidence: 99%

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Photogrammetry and image processing techniques for beach monitoring

Sánchez-García

2020

Rev. Teledetec.

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<p>The land-water boundary varies according to the sea level and the shape of a beach profile that is continuously modelled by incident waves. Attempting to model the response of a landscape as geomorphologically volatile as beaches requires multiple precise measurements to recognize responses to the actions of various geomorphic agents. It is therefore essential to have monitoring systems capable of systematically recording the shoreline accurately and effectively. New methods and tools are required to efficiently capture, characterize, and analyze information – and so obtain geomorphologically significant indicators. This is the aim of the doctoral thesis, focusing on the development of tools and procedures for coastal monitoring using satellite images and terrestrial photographs. The work brings satellite image processing and photogrammetric solutions to scientists, engineers, and coastal managers by providing results that demonstrate the usefulness of these viable and lowcost techniques. Existing and freely accessible public information (satellite images, video-derived data, or crowdsourced photographs) can be converted into high quality data for monitoring morphological changes on beaches and thus help achieve a sustainable management of coastal resources.</p>

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Section: Tesis Doctoralmentioning

confidence: 99%

Section: Tesis Doctoralmentioning

confidence: 99%

Photogrammetry and image processing techniques for beach monitoring

Sánchez-García

2020

Rev. Teledetec.

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“…Phần lớn các nghiên cứu về biến đổi đường bờ được thực hiện trên cơ sở dữ liệu bản đồ, lập hồ sơ thực địa, khảo sát bằng ảnh hàng không hay LIDAR [11]; tuy nhiên, những kỹ thuật này gặp khó khăn về phạm vi quan trắc [12], thời gian không đảm bảo cho các đánh giá xu hướng dài hạn hay những thay đổi theo mùa [13,14]. Đối với các dữ liệu vệ tinh quang học, sự kết hợp của đặc trưng độ phân giải không gian ở mức trung bình với phạm vi bao phủ không gian lớn, và thời gian quan trắc lặp đi lặp lại thường xuyên cho phép khai thác các thông tin tại các địa điểm khó khăn trong đo đạc [15,16]. Sự phát triển của hệ thống thông tin ảnh vệ tinh trong vài thập niên qua đã cải thiện các thông số của dữ liệu miễn phí, đặc biệt là ảnh Landsat [17].…”

Section: Mở đầUunclassified

Determination of Shoreline Changes along Upstream of Se San River, Kontum Province based Multi-temporal Remote Sensing Data Analysis

Pham¹,

Hoa²,

Tích³

et al. 2020

EES

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Se San river upstream includes Poko tributary (on the right bank) and Dak Bla tributary (on the left bank), mostly located in Kon Tum province. The process of river sediment decline has dramatic shoreline changes in this area, which becomes a driving-force to modify the current socio-economic development as well as the impact on territorial planning in the future. This study aims to analyze the shoreline changes by extracting multi-temporal satellite imagery of Landsat in the period of 1990-2013 and identify its change effects on land-use. The results show that the strongest erosion rate was -2.96 m/year in Dak Bla tributary (in Kon Tum town). And in the Poko tributary, the average value of erosion rate is -1.31 m/year and the average accretion rate is 1.17 m/year. In the context of dramatic land-use change, this approach allows to support for territorial management and illustrates the accretion-erosion relationship in river basin evolution.

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“…The shoreline is defined straightforwardly as the line that overlaps the physical land-water boundary [3]. Shoreline data can be obtained from different sources, such as historical maps, aerial photography, Light Detection and Ranging (LIDAR) and differentialGlobal Positioning Systems (dGPS) surveys (e.g., [4][5][6][7][8]), video and satellite imagery (e.g., [9][10][11][12][13][14][15][16]) and recently, crowd-sourced smartphone images taken at CoastSnap stations [17]. The analysis of historical shoreline changes can combine several sources (e.g., [18][19][20][21][22]).…”

Section: Introductionmentioning

confidence: 99%

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

Lima

Fernández-Fernández

Espinoza

et al. 2021

IJGI

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This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS graphical modeler for calculating the shoreline change with the end point rate method. The EPR4Q tries to fill the gaps in user-friendly and free open-source tools for shoreline analysis in a geographic information system environment since the most used software—Digital Shoreline Analysis System (DSAS)—although being a free extension, it is created for commercial software. Additionally, the best free, open-source option to calculate EPR is called Analyzing Moving Boundaries Using R (AMBUR); since it is a robust and powerful tool, the complexity can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR with different types of shorelines found in nature, extracted from the US Geological Survey Open-File. The obtained results of each tool were compared with Pearson’s correlation coefficient. The validation results indicate that the EPR4Q tool acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, proving that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

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An efficient protocol for accurate and massive shoreline definition from mid-resolution satellite imagery

Cited by 54 publications

References 65 publications

Photogrammetry and image processing techniques for beach monitoring

Photogrammetry and image processing techniques for beach monitoring

Determination of Shoreline Changes along Upstream of Se San River, Kontum Province based Multi-temporal Remote Sensing Data Analysis

End Point Rate Tool for QGIS (EPR4Q): Validation Using DSAS and AMBUR

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