https://rbgeomorfologia.org.br/rbg/issue/feedRevista Brasileira de Geomorfologia2024-11-06T11:49:38-03:00Leonardo José Cordeiro Santossantos.ufpr@gmail.comOpen Journal Systems<p>A Revista Brasileira de Geomorfologia (RBGeomorfologia), e-ISSN 2236-5664, foi criada em 2000, com foco em pesquisas relacionadas à gênese, processos, evolução e formas de relevo. Compreende a utilização e integração de dados laboratoriais, registros geológicos, indicadores morfométricos, ferramentas de geotecnologias e modelagem aplicadas à geomorfologia. A revista aborda os impactos das mudanças ambientais na superfície terrestre, considerando fatores naturais e antrópicos, contribuindo significativamente para a produção científica e a formulação de políticas públicas.</p>https://rbgeomorfologia.org.br/rbg/article/view/2554Mapping of planation surfaces in the north-central Amazonia2024-09-06T09:33:27-03:00José Roberto Mantovanijr.mantovani.geo@gmail.comGuilherme Taitson Buenogtaitson@ufg.br<p>This study aims to identify planation surfaces and their dissected reliefs in the Amazon, starting from the highlands of the border between Brazil, Venezuela and Guiana and ending near the axis of the Amazon River. Its connection with associated surface formations (regoliths) was also evaluated. The input data for the execution of the algorithm used were generated via geoprocessing techniques, which enabled the identification of five planation surfaces: a summit surface, which was associated with the Gondwana surface, from 855 to 2,745 m; a second surface (525–854 m), associated with the Post-Gondwana surface; a third surface, from 279 to 524 m, associated with the South American surface; a fourth surface, from 114 to 278 m, associated with the Velhas I surface (Early Velhas), and a fifth surface, associated with the Velhas II surface (Late Velhas). Thin soils predominate in the first three surfaces, and their presence is attributed to the erosion of the original surface formations with exposure of rock or iron crusts. The two lower surfaces present greater diversity of soils mainly due to the heterogeneity of soil hydrological conditions. In addition to <em>Latossolos</em> (Oxisols) and <em>Argissolos</em> (Ultisols), which are dominant, there are <em>Espodossolos</em> (Spodosols), <em>Plintossolos</em> (Plinthosols), <em>Gleissolos</em> (Gleysols) and <em>Planossolos</em> (Planosols).</p>2024-12-03T00:00:00-03:00Copyright (c) 2024 https://rbgeomorfologia.org.br/rbg/article/view/2596Linear Water Erosion Incisions in the Central-West Region of Brazil: A Bibliometric Analysis2024-08-26T07:22:06-03:00Kássio Samay Ribeiro Tavareskassiosamayribeiro@gmail.comSelma Simões de Castroscastro@unicamp.br<p class="MDPI17abstract"><span lang="EN-US" style="font-size: 9.0pt;">This study presents the results of a comprehensive bibliometric analysis of research on linear water erosion incisions in the Central-West region of Brazil. A total of 91 documents, including scientific articles, dissertations and academic theses, were analyzed to map the research trends and patterns in this field. The results indicate a predominance of geospatial and geodynamic studies. A multidisciplinary methodological approach is evident in 71% of the studies that combine multiple procedures to obtain more robust results. Most studies are multifactorial, using indicators of vegetation, land use and management, and geomorphology, reflecting the complexity of the processes involved. The main research focuses include modeling, mapping, and prediction indices. The results show that multiscale approaches are essential for integrating local and regional knowledge, offering a comprehensive understanding of the challenges and solutions for the erosive phenomenon. In addition, the geographical distribution of the studies reveals a greater concentration in the states of Goiás and Mato Grosso, associated with the intense agricultural and livestock activity in these areas. It is concluded that interdisciplinary approaches and the use of advanced technologies to address the challenges of linear water erosion should be intensified to promote sustainable land use and management practices.</span></p>2024-12-03T00:00:00-03:00Copyright (c) 2024 https://rbgeomorfologia.org.br/rbg/article/view/2614Sandy soil spots in northwestern Paraná: approaches for identification and quantification2024-10-21T16:50:07-03:00Leonardo José Cordeiro Santossantos.ufpr@gmail.comJosé Guilherme Oliveirajoseguilhermegeo@gmail.comFabio Marcelo Breunigfabiobreunig@gmail.comM´árcia Regina Calegarimarciareg_calegari@hotmail.comElias Fernando Berraeliasberra@gmail.comJonez Fidalskijonezfidalski@gmail.com<p>The predominance of sandy soils in the Northwest region of the state of Paraná, associated with the removal of natural vegetation, favored the development of patches of white sand on the surface without any aggregation. These spots are associated with the different types of land use existing in the region and the process of lateral soil transformation. As they constitute material without aggregation, they can be easily transported by wind and water and deposited in water bodies, causing severe environmental impacts. Thus, using thermal infrared satellite images, the objective of the present study was to map, determine the formation process of the spots and estimate the predominant particle size fractions. The model used and validated with field and laboratory information, allowed the identification of surfaces with patches of white sand present in the study region and estimating their percentage in different classes. After filtering the samples with vegetation cover during the product calculation period, an R² of 0.78 was obtained. The removal of natural vegetation has contributed to the formation and expansion of sandy patches and erosion in the northwest region of Paraná.</p>2024-11-11T00:00:00-03:00Copyright (c) 2024 https://rbgeomorfologia.org.br/rbg/article/view/2589Lithostructural control of the relief in the eastern sector of the Parnaíba sedimentary basin (Ibiapaba Plateau), Northeast Brazil 2024-08-15T11:27:05-03:00Frederico de Holanda Bastosfred.holanda@uece.brLionel Siamesiame@cerege.frDanielle Lopes de Sousa Limadanielle.llopes@hotmail.comAbner Monteiro Nunes Cordeiroabner.cordeiro@ufrn.br<p>Cartographic updates of the geological area between the Parnaíba and Borborema Provinces made it possible to provide details in the interpretation of the lithostructural control of the Ibiapaba Plateau and surroundings. The article aims to interpret regional morphostructural aspects based on bibliographic review, fieldwork and GIS interpretations. The area is characterized by an asymmetrical plateau with a continuous glint-type escarpment (≈800 m), supported by Paleozoic sandstones overlying the Precambrian basement. In the surroundings, flat surfaces predominate (≈200m), whose morphologies vary according to the lithologies. From a structural point of view, the Transbrasilian Lineament (LT) constitutes the main regional tectonic divide, influencing the behavior of the escarpment and the reverse. In lithological terms, the sandstones and conglomerates of the Serra Grande Group stand out, responsible for maintaining the top of the plateau, the Cabeças Formation and lateritic coverings, which support small tabular plateaus within the sedimentary basin, in addition to the granitoids, quartzites and orthogneisses that support residual reliefs in the basement. Considering a regional geomorphological evolution associated with Cretaceous uplifts of rift and post-rift phases, the detailing of lithostructural aspects is fundamental to explain the relationship of differential erosion in the current regional morphology.</p>2024-11-07T00:00:00-03:00Copyright (c) 2024 https://rbgeomorfologia.org.br/rbg/article/view/2584Landslide susceptibility mapping using logistic regression, random forests, and artificial neural networks: a case study in Mariana/MG, Brazil2024-08-28T17:50:16-03:00Mateus Oliveira Xaviermateus.xavier@ufop.edu.brCésar Falcão Barellacesarbarella@ufop.edu.br<p>The landslide susceptibility mapping (LSM) plays an important role in risk management. This study evaluated the predictive capabilities of three machine learning (ML) approaches applied to LSM: logistic regression (LR), random forests (RF), and artificial neural networks (ANN). The study was conducted in a mountainous region of Mariana/MG, Brazil. Initially, a point inventory with 364 landslides and 364 stable regions was randomly partitioned in a 70% training and 30% testing ratio for the models. Nine landslide conditioning factors (LCF), ranked by information gain (IG), were considered: slope angle (IG=0.486), geomorphology (IG=0.235), topographic wetness index - TWI (IG=0.138), lithology (IG=0.077), slope orientation (IG=0.067), topographic position index - TPI (IG=0.052), distance from drainage (IG=0.032), slope curvature (IG=0.029) and the distance from roads (IG=0.024). The evaluation of the area under the curve (AUC-ROC) and the classification efficiency rates in high () and low () susceptibility were used to compare the results of the approaches. The results demonstrated that although RF (AUC-ROC=0,947, =6,808, =0,030) slightly outperformed LR (AUC-ROC=0,936, =5,695, =0,050) and ANN (AUC-ROC=0,934, =6,495, =0,060), all the approaches exhibited high predictive capability in identifying areas susceptible to landslides.</p>2024-11-05T00:00:00-03:00Copyright (c) 2024