Mid-long term characterisation and short term modelling of a semi-protected pocket sandy beach in the Southern Coast of Brazil

Colaço, Guilherme; Violante-Carvalho, Nelson; Arruda, Wilton Zumpichiatti; d'Ávila, Victor de Amorim; Vilhena, Helio; Filippo, Alessandro; Candella, Rogério Neder

doi:10.1016/j.rsma.2020.101593

Cited by 2 publications

(3 citation statements)

References 29 publications

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“…The breakwater closes the entrance of the cove in about 35% of its cross section and probably cause a severe geomorphological impact on the beach. It is recognized that the morphodynamic processes of the beach were altered by the breakwater and, associated with the anthropic occupations, resulted in erosion in the southern region of the beach (Savi, 2007;Colaço et al, 2021). Geographically, Arraial do Cabo is a turning point of the Brazilian coast, abruptly changing the alignment from northeast-southwest to east-west (Motta et al, 2018;Colaço et al, 2021).…”

Section: Study Areamentioning

confidence: 99%

“…It is recognized that the morphodynamic processes of the beach were altered by the breakwater and, associated with the anthropic occupations, resulted in erosion in the southern region of the beach (Savi, 2007;Colaço et al, 2021). Geographically, Arraial do Cabo is a turning point of the Brazilian coast, abruptly changing the alignment from northeast-southwest to east-west (Motta et al, 2018;Colaço et al, 2021). The region has a warm semiarid climate, considered a "phytogeographic enclave" within RJ, which has a humid tropical climate (Barbiére, 1975;Coe and Carvalho, 2013).…”

Section: Study Areamentioning

confidence: 99%

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Satellite-Derived Bathymetry Models from Sentinel-2A and 2B in the Coastal Clear Waters of Arraial do Cabo, Rio de Janeiro, Brazil

Vargas¹,

Wasserman²,

Silva

et al. 2021

Rev. Bras. Geog. Fis.

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Mapping coastal environments is a challenging task, as field surveys and favorable oceanographic conditions are required. Remote sensing offers a practical alternative for extracting depth information, obtaining a fast, repetitive and low-cost mapping over large areas to optimize and minimize field work. This study aims to generate and evaluate Satellite-Derived Bathymetric (SDB) models from Sentinel-2A and 2B images on Praia dos Anjos, Brazil. The log-transform band ratio model was applied in this study. Two images from Sentinel-2 were used, from April 6, 2019 and June 20, 2019. For calibration and validation of SDB, depths were measured in the field with an echosounder on April 4, 2019. Different intervals of depths were tested, and the red wavelength to estimate depths up to 4 m. The statistical correlation between the image and control points on April 6, was r2 = 0.927 for 1-13 m depth interval and between SDB and check points was r2 = 0.893 with a Root Mean Square Error (RMSE) = 1.095. On June 20, the correlation between image and control points was r2 = 0.938 for 1-13 m depth interval, and between SDB and check points was r2 = 0.919 with a RMSE = 0.98. This study showed that remote sensing can be applied to estimate depths on Praia dos Anjos. Bathymetric information is essential for environmental monitoring and coastal engineering works. Further tests in the area are recommended to improve the models and an assessment of the calibrated equations for future applications with new measured check points.

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Section: Study Areamentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Satellite-Derived Bathymetry Models from Sentinel-2A and 2B in the Coastal Clear Waters of Arraial do Cabo, Rio de Janeiro, Brazil

Vargas¹,

Wasserman²,

Silva

et al. 2021

Rev. Bras. Geog. Fis.

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“…Generally, research on PBs is conducted from the beach towards offshore areas [8][9][10]. Most research has focused on planview geometry and morphological characteristic analysis of PBs [11,12] or morphohydrodynamics investigations [10,13]. Studies on the land use of PBs [14][15][16] are limited and currently lacking.…”

Section: Introductionmentioning

confidence: 99%

Mapping of Sicilian Pocket Beaches Land Use/Land Cover with Sentinel-2 Imagery: A Case Study of Messina Province

Randazzo

Cascio

Fontana

et al. 2021

Land

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Pocket beaches (PBs) are among the most attractive tourist sites and economic development contributors in coastal areas; however, they are negatively impacted by the combined effects of climate change and anthropogenic activities. Generally, research on PBs is conducted from the beach towards offshore. Studies on the land use/land cover (LULC) of PBs are limited and currently lacking. Such studies deserve more investigation due to the importance of LULC in PBs’ functioning. In this study, supervised classification methods were investigated for LULC mapping of the PBs located in the province of Messina. Sentinel-2B satellite images were analyzed using maximum likelihood (MaL), minimum distance (MiD), mahalanobis distance (MaD) and spectral angle mapper (SAM) classification methods. The study was conducted mainly in order to determine which classification method would be adequate for small scale Sentinel-2 imagery analysis and provide accurate results for the LULC mapping of PBs. In addition, an occurrence-based filter algorithm in conjunction with OpenStreetMap data and Google Earth imagery was used to extract linear features within 500 m of the inland buffer zone of the PBs. The results demonstrate that information on the biophysical parameters, namely surface cover fractions, of the coastal area can be obtained by conducting LULC mapping on Sentinel-2 images.

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Mid-long term characterisation and short term modelling of a semi-protected pocket sandy beach in the Southern Coast of Brazil

Cited by 2 publications

References 29 publications

Satellite-Derived Bathymetry Models from Sentinel-2A and 2B in the Coastal Clear Waters of Arraial do Cabo, Rio de Janeiro, Brazil

Satellite-Derived Bathymetry Models from Sentinel-2A and 2B in the Coastal Clear Waters of Arraial do Cabo, Rio de Janeiro, Brazil

Mapping of Sicilian Pocket Beaches Land Use/Land Cover with Sentinel-2 Imagery: A Case Study of Messina Province

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