22 research outputs found
Técnicas de fotogrametría y tratamiento de imágenes para a monitorización de playas
[EN] 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.[ES] El límite tierra-agua varía en función de la posición del nivel del mar y de la forma del perfil de playa que continuamente queda modelado por las olas incidentes. Intentar modelizar la respuesta de un paisaje tan voluble geomorfológicamente como las playas requiere disponer de múltiples medidas registradas con suficiente precisión para poder reconocer su respuesta frente a la acción de los distintos agentes geomórficos. Para ello resulta esencial disponer de diferentes sistemas de monitorización capaces de registrar de forma sistemática la línea de costa con exactitud y efectividad. Se requieren nuevos métodos y herramientas informáticas que permitan capturar, caracterizar y analizar eficientemente la información con el objeto de obtener indicadores con significación geomorfológica de calidad. En esto radica el objetivo de la presente tesis doctoral, centrándose en el desarrollo de herramientas y procedimientos eficientes para la monitorización costera mediante el uso de imágenes satelitales y fotografías terrestres. El trabajo aporta soluciones de procesamiento de imágenes de satélite y fotogramétricas a científicos, ingenieros y gestores costeros, proporcionando resultados que evidencian la gran utilidad de estas técnicas viables y de bajo coste para la monitorización costera. Mediante ellas se puede convertir información pública existente y de libre acceso (imágenes satelitales, datos de video cámaras o fotografías de la ciudadanía) en datos de alta calidad para el monitoreo de los cambios morfológicos de las playas, y lograr así una consiguiente gestión sostenible de los recursos costeros.This study was supported by the grant of E. Sánchez-García (FPU13/ 05877) from the Spanish Ministry of Education, Culture and Sports, as
well as the project RESETOCOAST (CGL 2015-69906-R) from the Spanish Ministry of Economy and Competitiveness.Sánchez-García, E.; Balaguer-Beser, Á.; Pardo-Pascual, JE. (2020). Photogrammetry and image processing techniques for beach monitoring. https://doi.org/10.4995/raet.2020.14107OJ
C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint
[EN] This paper describes a methodological protocol to project a terrestrial photograph of a coastal area or whatever indicator is contained on it in a georeferenced plane taking advantage of the terrestrial horizon as a geometric key. This feature, which appears in many beach photos, helps in camera repositioning and as a constraint in collinearity adjustment. This procedure is implemented in a tool called Coastal Projector (C-Pro) that is based on Matlab and adapts its methodology in accordance with the input data and the available parameters of the acquisition system. The method is tested in three coastal areas to assess the influence that the horizon constraint presents in the results. The proposed methodology increases the reliability and efficient use of existing recreational cameras (with non-optimal requirements, unknown image calibration, and at elevations lower than 7 m) to provide quantitative coastal data.This study is part of the PhD dissertation of the first author, which is supported by a grant from the Spanish Ministry of Education, Culture and Sports (I+D+i 2013–2016). Two other projects participated: one from the Spanish Ministry of Economy and Competitiveness (CGL2015-69906-R) and the other from the Valencia Regional Government (AICO/2015/098). The Department of Geology, Faculty of Science of the University of Lisbon provided Magoito data thanks to a PhD stay of the first author under the supervision of Dr. Rui Taborda. The authors gratefully acknowledge the constructive comments provided by Dr. Jaime Almonacid.Sánchez García, E.; Balaguer-Beser, Á.; Pardo Pascual, JE. (2017). C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint. ISPRS Journal of Photogrammetry and Remote Sensing. 128:255-273. https://doi.org/10.1016/j.isprsjprs.2017.03.023S25527312
Evaluating Fourier Cross-Correlation Sub-Pixel Registration in Landsat Images
[EN] Multi-temporal analysis is one of the main applications of remote sensing, and Landsat imagery has been one of the main resources for many years. However, the moderate spatial resolution (30 m) restricts their use for high precision applications. In this paper, we simulate Landsat scenes to evaluate, by means of an exhaustive number of tests, a subpixel registration process based on phase correlation and the upsampling of the Fourier transform. From a high resolution image (0.5 m), two sets of 121 synthetic images of fixed translations are created to simulate Landsat scenes (30 m). In this sense, the use of the point spread function (PSF) of the Landsat TM (Thematic Mapper) sensor in the downsampling process improves the results compared to those obtained by simple averaging. In the process of obtaining sub-pixel accuracy by upsampling the cross correlation matrix by a certain factor, the limit of improvement is achieved at 0.1 pixels. We show that image size affects the cross correlation results, but for images equal or larger than 100 x 100 pixels similar accuracies are expected. The large dataset used in the tests allows us to describe the intra-pixel distribution of the errors obtained in the registration process and how they follow a waveform instead of random/stochastic behavior. The amplitude of this waveform, representing the highest expected error, is estimated at 1.88 m. Finally, a validation test is performed over a set of sub-pixel shorelines obtained from actual Landsat-5 TM, Landsat-7 ETM+ (Enhanced Thematic Mapper Plus) and Landsat-8 OLI (Operation Land Imager) scenes. The evaluation of the shoreline accuracy with respect to permanent seawalls, before and after the registration, shows the importance of the registering process and serves as a non-synthetic validation test that reinforce previous results.This study has been supported by a research project from the Spanish Ministry of Economy and Competitiveness (CGL2015-69906-R).Almonacid Caballer, J.; Pardo Pascual, JE.; Ruiz Fernández, LÁ. (2017). Evaluating Fourier Cross-Correlation Sub-Pixel Registration in Landsat Images. Remote Sensing. 9(10). https://doi.org/10.3390/rs9101051S91
Detecting problematic beach widths for the recreational function along the Gulf of Valencia (Spain) from Landsat 8 subpixel shorelines
[EN] This work shows a continuous and regional monitoring of the beach width and how to link it with the recreational function of these spaces. Shorelines automatically derived from Landsat 8 satellite were employed for this purpose, covering up to 83 dates (2013¿2016) and 150¿km of beaches. The study included the microtidal beaches of the Gulf of Valencia, a strongly developed coast with intensive use in the Western Mediterranean. Beach widths were defined in alongshore coastal segments of 80-m length. Annual mean width and annual percentiles appeared as representative statistics of the beach state and the most unfavorable widths occurred throughout the year. Considering these statistical descriptors, beach segments were classified according to their adequacy to sustain a recreational function. The integration of descriptors of the beach width and use of the beach data on a regional scale offers a holistic approach to identify potentially problematic segments, crucial information for coastal managers.This study integrates findings and results obtained within the framework of the FPU15/04501 granted by the Spanish Ministry of Education, Culture and Sports to Carlos Cabezas Rabadan, and by the funds of the research project RESETOCOAST (CGL2015-69906-R) supported by the Ministry of Economy, Industry, and Competitiveness. Authors acknowledge the USGS for providing free access to the Landsat imagery.Cabezas-Rabadán, C.; Pardo Pascual, JE.; Almonacid-Caballer, J.; Rodilla, M. (2019). Detecting problematic beach widths for the recreational function along the Gulf of Valencia (Spain) from Landsat 8 subpixel shorelines. Applied Geography. 110:1-13. https://doi.org/10.1016/j.apgeog.2019.102047S11311
Assessing users expectations and perceptions on different beach types and the need for diverse management frameworks along the Western Mediterranean
[EN] Beach management follows a homogeneous and rigid decision-making process that tries to fulfill expectations assumed from mass tourism without really getting to know the real users' perception. Decisions are usually taken without considering the diversity of values of the beaches, causing high environmental, economic and recreational impacts. In this study, users' profiles, expectations and perceptions have been defined on six Valencian beaches with both different degree of artificialization and sediment type. This has allowed a comparison between semi-natural and urban beaches, and between pebbly and sandy beaches. Differences between beach types have been observed, and a critical analysis of the current management framework and practices has been carried out. Therefore, decision-making should take greater account of users, and actions should be adapted to the diversity of beaches and their particularities, leading to a differential beach management.This study integrates findings and results obtained within the framework of the FPU15/04501 granted by the Ministry of Education, Culture and Sports to C. Cabezas-Rabadan, and by the funds of the research project RESETOCOAST (CGL2015-69906-R) supported by the Ministry of Economy, Industry and Competitiveness.Cabezas-Rabadán, C.; Rodilla, M.; Pardo Pascual, JE.; Herrera-Racionero, P. (2019). Assessing users expectations and perceptions on different beach types and the need for diverse management frameworks along the Western Mediterranean. Land Use Policy. 81:219-231. https://doi.org/10.1016/j.landusepol.2018.10.027S2192318
Characterizing beach changes using high-frequency Sentinel-2 derived shorelines on the Valencian coast (Spanish Mediterranean)
[EN] Shoreline position can be efficiently extracted with subpixel accuracy frommid-resolution satellite imagery using tools as SHOREX. However, it is necessary to develop procedures for deriving descriptors of the beach morphology and its changes in order to become truly useful data for characterizing the coastal dynamism.
A new approach is proposed based on a spatiotemporal model of the beach widths. Divided into 80 m analysis segments, it offers a robust and detailed characterization of the beach state along large micro-tidal regions, with continuous information through time and space. Geographical and temporal differences can be recognized andmeasured, making it possible to study the beach response both to general factors (as wave conditions) and to punctual anthropic actions (as small sand nourishments).
Widths were defined throughout two and a half years from 60 shorelines (3.04 m RMSE) covering 50 km of the Gulf of Valencia. Important width contrasts appeared along the study site associated with sediment imbalances motivated by sediment traps and other anthropic actions. Segments too narrow for maintaining the recreational function were located and mapped (16% narrower than 30 m). Short-term width changes appeared linked to storm events, with fast retreatments and slow recoveries. Punctually, even small-magnitude nourishments created perceptible changes in width (12,830 m(3) were associated with a 4 m increase).
This novel description of the beach state and its changes from Satellite-Derived Shorelines is useful for coastal management, especially considering the global coverage of these free satellite images. It may improve the comprehension of coastal processes as well as monitor human interventions on the coast, helping in the decision making. (c) 2019 Elsevier B.V. All rights reserved.This study is supported by the contract of C. Cabezas-Rabadan (FPU15/04501) from the Spanish Ministry of Education, Culture and Sports, and by the project RESETOCOAST (CGL2015-69906-R) from the Spanish Ministry of Economy and Competitiveness.Cabezas-Rabadán, C.; Pardo Pascual, JE.; Palomar-Vázquez, J.; Fernández-Sarría, A. (2019). Characterizing beach changes using high-frequency Sentinel-2 derived shorelines on the Valencian coast (Spanish Mediterranean). The Science of The Total Environment. 691:216-231. https://doi.org/10.1016/j.scitotenv.2019.07.084S21623169
Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy
[EN] SAET (Shoreline Analysis and Extraction Tool) is a novel open-source tool to enable the completely automatic detection of shoreline position changes using the optical imagery acquired by the Sentinel-2 and Landsat 8 and 9 satellites. SAET has been developed within the ECFAS (European Coastal Flood Awareness System) project, which is intended to be the first European service for coastal flood forecasting, management, and recovery analysis. The tool is developed to characterise the shoreline response associated with punctual events such as coastal storms as well as any other phenomenon. For a given beach segment, SAET facilitates the selection of the satellite images closest in time to the analysed events that offer an adequate cloud coverage level for analysing the shoreline change. Subsequently, the tool automatically downloads the images from their official repositories, pre-processes them and extracts the shoreline position with sub-pixel accuracy. In order to do so, an initial approximate definition of the shoreline is carried out at the pixel level using a water index thresholding, followed by an accurate extraction operating on the shortwave infrared bands to produce a sub-pixel line in vector formats (points and lines). The tool offers different settings to be adapted to the different coastal environments and beach typologies. Its main advantages refer to its autonomy, its efficiency in extracting complete satellite scenes, its flexibility in adapting to different environments and conditions, and its high subpixel accuracy. This work presents an accuracy assessment on a long Mediterranean sandy beach of SDSs extracted from L8 and S2 imagery against coincident alongshore reference lines, showing an accuracy of about 3 m RMSE. At the same time, the work shows an example of the usage of SAET for characterising the response to Storm Gloria (January 2020) on the beaches of Valencia (E Spain). SAET provides an efficient and completely automatic workflow that leads to accurate SDSs while only relying on publicly available information. The tool appears to be a useful extraction tool for beach monitoring, both for public administrations and individual users.The ECFAS (European Coastal Flood Awareness System) project (https://www.ecfas.eu/) has received funding from the EU H2020 research and innovation programme under Grant Agreement No. 101004211. This research is also supported by the projects MONOBESAT (PID2019-111435RB-I00)
funded by the Spanish Ministry of Science, Innovation and Universities, and the Margarita Salas contract within the Re-qualification programme by the Ministry of Universities financed by the European Union¿NextGenerationEU and the grant Primeros Proyectos de Investigación (PAID-06-22),
Vicerrectorado de Investigación de la Universitat Politècnica de València (UPV) associated with the corresponding author.Palomar-Vázquez, J.; Pardo Pascual, JE.; Almonacid-Caballer, J.; Cabezas-Rabadán, C. (2023). Shoreline Analysis and Extraction Tool (SAET): A New Tool for the Automatic Extraction of Satellite-Derived Shorelines with Subpixel Accuracy. Remote Sensing. 15(12). https://doi.org/10.3390/rs15123198151
Diseño de una solución cartográfica para móviles en zonas de montaña. Aplicación para el Parque Natural del Montseny
En este artículo se describe el diseño y la implementación de una aplicación de visualización y consulta de la cartografía del Parc Natural del Montseny (Girona) optimizada para dispositivos móviles, para ser utilizada tanto en modo on-line como en modo off-line. El sistema permite la visualización de varios niveles de detalle, así como la consulta de la información cartográfica. Para el diseño de la aplicación se han tenido en cuenta diferentes aspectos y requerimientos: permite la conexión on-line a la cartografía o la descarga directa para un funcionamiento autónomo; permite la utilización de geolocalización vía GPS o también QR-Code (para zonas sin cobertura); y finalmente incorpora un sistema de almacenamiento de los atributos basado en la codificación de los mismos en la propia imagen. La aplicación ha sido implementada en J2ME y tiene en cuenta la resolución y el tamaño de pantalla del dispositivo móvil.Palomar-Vázquez, J.; Pardo Pascual, JE.; Peiró Simó, MJ. (2012). Diseño de una solución cartográfica para móviles en zonas de montaña. Aplicación para el Parque Natural del Montseny. Mapping. (154):16-24. http://hdl.handle.net/10251/35331S162415
A New Adaptive Image Interpolation Method to Define the Shoreline at Sub-Pixel Level
[EN] This paper presents a new methodological process for detecting the instantaneous land-water border at sub-pixel level from mid-resolution satellite images (30 m/pixel) that are freely available worldwide. The new method is based on using an iterative procedure to compute Laplacian roots of a polynomial surface that represents the radiometric response of a set of pixels. The method uses a first approximation of the shoreline at pixel level (initial pixels) and selects a set of neighbouring pixels to be part of the analysis window. This adaptive window collects those stencils in which the maximum radiometric variations are found by using the information given by divided differences. Therefore, the land-water surface is computed by a piecewise interpolating polynomial that models the strong radiometric changes between both interfaces. The assessment is tested on two coastal areas to analyse how their inherent differences may affect the method. A total of 17 Landsat 7 and 8 images (L7 and L8) were used to extract the shorelines and compare them against other highly accurate lines that act as references. Accurate quantitative coastal data from the satellite images is obtained with a mean horizontal error of 4.38 +/- 5.66 m and 1.79 +/- 2.78 m, respectively, for L7 and L8. Prior methodologies to reach the sub-pixel shoreline are analysed and the results verify the solvency of the one proposed.This study is part of the PhD dissertation of E. Sanchez-Garcia, which was supported by a grant from the Spanish Ministry of Education, Culture and Sports (I + D + i 2013-2016). The authors also appreciate the financial support provided by the Spanish Ministry of Economy and Competitiveness (CGL2015-69906-R)Sánchez-García, E.; Balaguer-Beser, Á.; Almonacid-Caballer, J.; Pardo Pascual, JE. (2019). A New Adaptive Image Interpolation Method to Define the Shoreline at Sub-Pixel Level. Remote Sensing. 11(16):1-28. https://doi.org/10.3390/rs11161880S1281116Szmytkiewicz, M., Biegowski, J., Kaczmarek, L. M., Okrój, T., Ostrowski, R., Pruszak, Z., … Skaja, M. (2000). Coastline changes nearby harbour structures: comparative analysis of one-line models versus field data. Coastal Engineering, 40(2), 119-139. doi:10.1016/s0378-3839(00)00008-9Furmańczyk, K., Andrzejewski, P., Benedyczak, R., Bugajny, N., Cieszyński, Ł., Dudzińska-Nowak, J., … Zawiślak, T. (2014). Recording of selected effects and hazards caused by current and expected storm events in the Baltic Sea coastal zone. Journal of Coastal Research, 70, 338-342. doi:10.2112/si70-057.1Deng, J., Harff, J., Zhang, W., Schneider, R., Dudzińska-Nowak, J., Giza, A., … Furmańczyk, K. (2017). The Dynamic Equilibrium Shore Model for the Reconstruction and Future Projection of Coastal Morphodynamics. Coastal Research Library, 87-106. doi:10.1007/978-3-319-49894-2_6Paprotny, D., Andrzejewski, P., Terefenko, P., & Furmańczyk, K. (2014). Application of Empirical Wave Run-Up Formulas to the Polish Baltic Sea Coast. PLoS ONE, 9(8), e105437. doi:10.1371/journal.pone.0105437Roelvink, D., Reniers, A., van Dongeren, A., van Thiel de Vries, J., McCall, R., & Lescinski, J. (2009). Modelling storm impacts on beaches, dunes and barrier islands. Coastal Engineering, 56(11-12), 1133-1152. doi:10.1016/j.coastaleng.2009.08.006Kostrzewski, A., Zwoliński, Z., Winowski, M., Tylkowski, J., & Samołyk, M. (2015). Cliff top recession rate and cliff hazards for the sea coast of Wolin Island (Southern Baltic). Baltica, 28(2), 109-120. doi:10.5200/baltica.2015.28.10Terefenko, P., Zelaya Wziątek, D., Dalyot, S., Boski, T., & Pinheiro Lima-Filho, F. (2018). A High-Precision LiDAR-Based Method for Surveying and Classifying Coastal Notches. ISPRS International Journal of Geo-Information, 7(8), 295. doi:10.3390/ijgi7080295Terefenko, P., Paprotny, D., Giza, A., Morales-Nápoles, O., Kubicki, A., & Walczakiewicz, S. (2019). Monitoring Cliff Erosion with LiDAR Surveys and Bayesian Network-based Data Analysis. Remote Sensing, 11(7), 843. doi:10.3390/rs11070843Kolander, R., Morche, D., & Bimböse, M. (2013). Quantification of moraine cliff coast erosion on Wolin Island (Baltic Sea, northwest Poland). Baltica, 26(1), 37-44. doi:10.5200/baltica.2013.26.04Moore, L. J., Ruggiero, P., & List, J. H. (2006). Comparing Mean High Water and High Water Line Shorelines: Should Proxy-Datum Offsets be Incorporated into Shoreline Change Analysis? Journal of Coastal Research, 224, 894-905. doi:10.2112/04-0401.1Davidson, M., Van Koningsveld, M., de Kruif, A., Rawson, J., Holman, R., Lamberti, A., … Aarninkhof, S. (2007). The CoastView project: Developing video-derived Coastal State Indicators in support of coastal zone management. Coastal Engineering, 54(6-7), 463-475. doi:10.1016/j.coastaleng.2007.01.007Aarninkhof, S. G. ., Turner, I. L., Dronkers, T. D. ., Caljouw, M., & Nipius, L. (2003). A video-based technique for mapping intertidal beach bathymetry. Coastal Engineering, 49(4), 275-289. doi:10.1016/s0378-3839(03)00064-4Andriolo, U., Sánchez-García, E., & Taborda, R. (2019). Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies. Remote Sensing, 11(1), 78. doi:10.3390/rs11010078Sánchez-García, E., Balaguer-Beser, A., & Pardo-Pascual, J. E. (2017). C-Pro: A coastal projector monitoring system using terrestrial photogrammetry with a geometric horizon constraint. ISPRS Journal of Photogrammetry and Remote Sensing, 128, 255-273. doi:10.1016/j.isprsjprs.2017.03.023Holman, R. A., & Stanley, J. (2007). The history and technical capabilities of Argus. Coastal Engineering, 54(6-7), 477-491. doi:10.1016/j.coastaleng.2007.01.003Sagar, S., Roberts, D., Bala, B., & Lymburner, L. (2017). Extracting the intertidal extent and topography of the Australian coastline from a 28 year time series of Landsat observations. Remote Sensing of Environment, 195, 153-169. doi:10.1016/j.rse.2017.04.009Luijendijk, A., Hagenaars, G., Ranasinghe, R., Baart, F., Donchyts, G., & Aarninkhof, S. (2018). The State of the World’s Beaches. Scientific Reports, 8(1). doi:10.1038/s41598-018-24630-6Li, J., & Roy, D. (2017). A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring. Remote Sensing, 9(9), 902. doi:10.3390/rs9090902Boak, E. H., & Turner, I. L. (2005). Shoreline Definition and Detection: A Review. Journal of Coastal Research, 214, 688-703. doi:10.2112/03-0071.1Gens, R. (2010). Remote sensing of coastlines: detection, extraction and monitoring. International Journal of Remote Sensing, 31(7), 1819-1836. doi:10.1080/01431160902926673Liu, H., Wang, L., Sherman, D. J., Wu, Q., & Su, H. (2011). Algorithmic Foundation and Software Tools for Extracting Shoreline Features from Remote Sensing Imagery and LiDAR Data. Journal of Geographic Information System, 03(02), 99-119. doi:10.4236/jgis.2011.32007Pardo-Pascual, J. E., Almonacid-Caballer, J., Ruiz, L. A., & Palomar-Vázquez, J. (2012). Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment, 123, 1-11. doi:10.1016/j.rse.2012.02.024Pardo-Pascual, J. E., Almonacid-Caballer, J., Ruiz, L. A., Palomar-Vázquez, J., & Rodrigo-Alemany, R. (2014). Evaluation of storm impact on sandy beaches of the Gulf of Valencia using Landsat imagery series. Geomorphology, 214, 388-401. doi:10.1016/j.geomorph.2014.02.020Almonacid-Caballer, J., Sánchez-García, E., Pardo-Pascual, J. E., Balaguer-Beser, A. A., & Palomar-Vázquez, J. (2016). Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid-term coastal evolution indicator. Marine Geology, 372, 79-88. doi:10.1016/j.margeo.2015.12.015Sánchez-García, E., Pardo-Pascual, J. E., Balaguer-Beser, A., & Almonacid-Caballer, J. (2015). ANALYSIS OF THE SHORELINE POSITION EXTRACTED FROM LANDSAT TM AND ETM+ IMAGERY. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-7/W3, 991-998. doi:10.5194/isprsarchives-xl-7-w3-991-2015Pardo-Pascual, J., Sánchez-García, E., Almonacid-Caballer, J., Palomar-Vázquez, J., Priego de los Santos, E., Fernández-Sarría, A., & Balaguer-Beser, Á. (2018). Assessing the Accuracy of Automatically Extracted Shorelines on Microtidal Beaches from Landsat 7, Landsat 8 and Sentinel-2 Imagery. Remote Sensing, 10(2), 326. doi:10.3390/rs10020326Almonacid-Caballer, J., Pardo-Pascual, J., & Ruiz, L. (2017). Evaluating Fourier Cross-Correlation Sub-Pixel Registration in Landsat Images. Remote Sensing, 9(10), 1051. doi:10.3390/rs9101051Liu, Q., Trinder, J., & Turner, I. (2016). A COMPARISON OF SUB-PIXEL MAPPING METHODS FOR COASTAL AREAS. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, III-7, 67-74. doi:10.5194/isprsannals-iii-7-67-2016Liu, Y., Wang, X., Ling, F., Xu, S., & Wang, C. (2017). Analysis of Coastline Extraction from Landsat-8 OLI Imagery. Water, 9(11), 816. doi:10.3390/w9110816Liu, Q., Trinder, J., & Turner, I. L. (2017). Automatic super-resolution shoreline change monitoring using Landsat archival data: a case study at Narrabeen–Collaroy Beach, Australia. Journal of Applied Remote Sensing, 11(1), 016036. doi:10.1117/1.jrs.11.016036Cipolletti, M. P., Delrieux, C. A., Perillo, G. M. E., & Cintia Piccolo, M. (2012). Superresolution border segmentation and measurement in remote sensing images. Computers & Geosciences, 40, 87-96. doi:10.1016/j.cageo.2011.07.015Liu, H., & Jezek, K. C. (2004). Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods. International Journal of Remote Sensing, 25(5), 937-958. doi:10.1080/0143116031000139890Hermosilla, T., Bermejo, E., Balaguer, A., & Ruiz, L. A. (2008). Non-linear fourth-order image interpolation for subpixel edge detection and localization. Image and Vision Computing, 26(9), 1240-1248. doi:10.1016/j.imavis.2008.02.012Harten, A., Engquist, B., Osher, S., & Chakravarthy, S. R. (1987). Uniformly high order accurate essentially non-oscillatory schemes, III. Journal of Computational Physics, 71(2), 231-303. doi:10.1016/0021-9991(87)90031-3Shu, C.-W., & Osher, S. (1988). Efficient implementation of essentially non-oscillatory shock-capturing schemes. Journal of Computational Physics, 77(2), 439-471. doi:10.1016/0021-9991(88)90177-5Capilla, M. T., & Balaguer-Beser, A. (2013). A new well-balanced non-oscillatory central scheme for the shallow water equations on rectangular meshes. Journal of Computational and Applied Mathematics, 252, 62-74. doi:10.1016/j.cam.2013.01.014Balaguer, Á., & Conde, C. (2005). Fourth-Order Nonoscillatory Upwind and Central Schemes for Hyperbolic Conservation Laws. SIAM Journal on Numerical Analysis, 43(2), 455-473. doi:10.1137/s0036142903437106Xu, N. (2018). Detecting Coastline Change with All Available Landsat Data over 1986–2015: A Case Study for the State of Texas, USA. Atmosphere, 9(3), 107. doi:10.3390/atmos9030107Balaguer, A., Conde, C., López, J. A., & Martínez, V. (2001). A finite volume method with a modified ENO scheme using a Hermite interpolation to solve advection diffusion equations. International Journal for Numerical Methods in Engineering, 50(10), 2339-2371. doi:10.1002/nme.123Press, W. H., & Teukolsky, S. A. (1990). Savitzky-Golay Smoothing Filters. Computers in Physics, 4(6), 669. doi:10.1063/1.482296
Analysis of the shoreline position extracted from Landsat TM and ETM+ imagery
[EN] A statistical analysis of the results obtained by the tool SELI (Shoreline Extraction from Landsat Imagery) is made in order to characterise the medium and long term period changes occurring on beaches. The analysis is based on the hypothesis that intra-annual shifts of coastline positions hover around an average position, which would be significant when trying to set these medium and long term trends. Fluctuations around this average are understood as the effect of short-term changes -variations related to sea level, wave run-up, and the immediate morphological beach profile settings of the incident waves- whilst the alterations of the average position will obey changes relating to the global sedimentary harmony of the analysed beach segment. The goal of this study is to assess the validity of extracted Landsat shorelines knowing whether the intrinsic error could alter the position of the computed mean annual shoreline or if it is balanced out between the successive averaged images. Two periods are stablished for the temporal analysis in the area according to the availability of other data taken from high precision sources. Statistical tests performed to compare samples (Landsat versus high accuracy) indicate that the two sources of data provide similar information regarding annual means; coastal behaviour and dynamics, thereby verifying Landsat shorelines as useful data for evolutionary studies.This work is part of the PhD of the first author which is supported by the “Ministerio de Educación, Cultura y Deporte” of Spain (state program in I+D+i 2013-2016)Sánchez García, E.; Pardo Pascual, JE.; Balaguer Beser, ÁA.; Almonacid Caballer, J. (2015). Analysis of the shoreline position extracted from Landsat TM and ETM+ imagery. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XL-7/W3:991-998. doi:10.5194/isprsarchives-XL-7-W3-991-2015S991998XL-7/W