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      Inventory of natural processes with nautical charts, real-time kinematic global navigation satellite systems (RTK-GNSS), and unmanned aerial vehicle (UAV), Trindade Island, Brazil

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          Abstract

          Abstract The volcanic Trindade Island is a remote Brazilian offshore territory in the South Atlantic, located ca. 1.140 kilometers east of the southeast coast of Brazil. The island’s permanent exposure to geological hazards requires assessment. However, the lack of erosion and landslides temporal data impedes predictive geohazard analyses. Therefore, we compiled pre-existing data from nautical charts and surveyed the surface terrain on Trindade Island to generate Digital Terrain Models (DTMs) and comparative accuracy analyses. The DTM based on pre-existing data shows the lowest accuracy (root mean square error - RMSE: 12.3 m) yet is adequate for regional studies. In contrast, the DTM developed from real-time kinematic global navigation satellite systems (RTK-GNSS) has the highest vertical accuracy (RMSE: 0.48 m), but spatial variability of ground elements was underestimated and limited to meter-sized (and larger) elements. The DTM obtained using the unmanned aerial vehicle (UAV) with ground control points (GCP), on the other hand, presented lower accuracy (RMSE: 2.37 m) than the RTK-GNSS model but still allowed observation of centimetric (and larger) ground features. For geohazard assessment on Trindade Island, models that allow fine-scale studies are needed. A UAV with GCP provides such standards and proved to be the most viable option in remote and complex sites as well. Hence, this study, the first to allow multi-temporal analysis of geohazard assessment on Trindade Island, offers a viable solution for similar analyses in other remote locations.

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            Methodological sensitivity of morphometric estimates of coarse fluvial sediment transport

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                Author and article information

                Journal
                bjgeo
                Brazilian Journal of Geology
                Braz. J. Geol.
                Sociedade Brasileira de Geologia (São Paulo, SP, Brazil )
                2317-4889
                2317-4692
                2022
                : 52
                : 4
                : e20220007
                Affiliations
                [2] São Paulo São Paulo orgnameUniversidade de São Paulo orgdiv1Escola de Engenharia de São Carlos orgdiv2Departamento de Geotecnia Brazil lazarus1@ 123456sc.usp.br
                [1] Curitiba Paraná orgnameUniversidade Federal do Paraná orgdiv1Programa de Pós-Graduação em Geologia orgdiv2Laboratório de Estudos Costeiros Brazil fernanda.avelars@ 123456gmail.com
                [5] Rio de Janeiro Rio de Janeiro orgnameUniversidade Federal do Rio de Janeiro orgdiv1Departamento de Geologia Brazil carol.almeidaf56@ 123456gmail.com
                [3] Porto Alegre Rio Grande do Sul orgnameUniversidade Federal do Rio Grande do Sul orgdiv1Instituto de Geociências orgdiv2Departamento de Geodésia Brazil luiza.camara@ 123456ufrgs.br
                [4] Curitiba Paraná orgnameUniversidade Federal do Paraná orgdiv2Departamento de Geologia Brazil adratal@ 123456gmail.com
                Article
                S2317-48892022000400306 S2317-4889(22)05200400306
                10.1590/2317-4889202220220007
                416d1a8e-e1bb-438f-89fe-eaf4b04ee6a5

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 12 January 2022
                : 05 August 2022
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 57, Pages: 0
                Product

                SciELO Brazil

                Categories
                Articles

                South Atlantic Ocean,geotechnology,geohazard assessment,digital terrain model,volcanic landscape

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