{"title":"Shoreline change assessment at Arroio do Sal (Southern Brazil) using different shoreline extraction methods","authors":"Elaine B. de Oliveira, Eduardo G. Barboza","doi":"10.1016/j.rsase.2024.101303","DOIUrl":null,"url":null,"abstract":"<div><p>This research aims to compare different shoreline extraction methods in assessing shoreline variability at Arroio do Sal, Southern Brazil. The methodology included the automatic extraction of shoreline positions by CoastSat and Cassie and the manual vectorization of shorelines using two different shoreline proxies. Digital Shoreline Analysis System was used to compute the shoreline displacement for each extraction method and shoreline mission. The results were compared in terms of rates, uncertainties, and methodologies. The results show that the CoastSat lines are generally displaced towards the land, while Cassie is displaced towards the sea. To concerning shape, Cassie has a more undulating shape and a greater number of indentations, with more exaggerated features, while CoastSat has a more rectilinear line, with smoother indentations next to the washouts. The RMSE values are 8.89 m for CoastSat and 27.27 m for Cassie. Despite the variations in the coastline position between the algorithms, the analyses of the rates of change have similar trends. Both algorithms establish an erosion trend for the Sentinel lines, but with different magnitudes; for the Landsat lines, both algorithms show a stable coastline, with the same average and uncertainty. Arroio do Sal can be considered a stable coastline, with rates of change in the −0.5 m–0.5 m range. Both algorithms were able to determine this general trend.</p></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101303"},"PeriodicalIF":3.8000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938524001678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This research aims to compare different shoreline extraction methods in assessing shoreline variability at Arroio do Sal, Southern Brazil. The methodology included the automatic extraction of shoreline positions by CoastSat and Cassie and the manual vectorization of shorelines using two different shoreline proxies. Digital Shoreline Analysis System was used to compute the shoreline displacement for each extraction method and shoreline mission. The results were compared in terms of rates, uncertainties, and methodologies. The results show that the CoastSat lines are generally displaced towards the land, while Cassie is displaced towards the sea. To concerning shape, Cassie has a more undulating shape and a greater number of indentations, with more exaggerated features, while CoastSat has a more rectilinear line, with smoother indentations next to the washouts. The RMSE values are 8.89 m for CoastSat and 27.27 m for Cassie. Despite the variations in the coastline position between the algorithms, the analyses of the rates of change have similar trends. Both algorithms establish an erosion trend for the Sentinel lines, but with different magnitudes; for the Landsat lines, both algorithms show a stable coastline, with the same average and uncertainty. Arroio do Sal can be considered a stable coastline, with rates of change in the −0.5 m–0.5 m range. Both algorithms were able to determine this general trend.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems