Abstract
Abstract Relief classification methodologies seek to define the parameters that determine those parts of the terrestrial surface that present homogeneous forms and elements. The rapid development of geotechnology has increasingly provided tools and methodologies that assist in studies related to relief. The present work proposes a methodology to classify the relief in three taxonomic levels, using automated processing in a GIS environment. This procedure was applied in a case study of the Santa Maria River basin, in the west of Rio Grande do Sul State, Brazil. The digital data processing employed was the Geographic Information System ArcGIS® and the data from the SRTM 3 arc-second radar (90 meters) was the basis for the Digital Elevation Model. The processing for the first taxon used the amplitude and slope data to define four forms of relief: flat areas, slightly undulating hills, undulating hills, and hills with buttes and larger hills. In the second taxonomic level, ten relief elements were identified: flat, peak, ridge, shoulder, spur, slope, hollow, footslope, valley, and pit. In the third taxonomic level, the slope forms were characterized into eight units using the slope, profile, and curvature plane parameters. It was possible to detect the three proposed levels, the relief forms, relief elements, and slope forms. GIS processing offers a fast and precise definition of the relief forms and elements, and the slope forms, as well as the relationship between the three taxonomic levels.
Highlights
Landforms are defined by the spatial arrangement of homogeneous surfaces resulting from the action of tectonic forces that provoke uplifts and relegation, and agents of the terrestrial surface that act on rocky materials, decomposing and disaggregating them over time to develop different features and forms
The development of geoprocessing methods and GIS means the terrestrial surface can be represented through digital models (DEM), which allow the topographic analysis of a zone of interest, as well as the automated calculation of a series of related variables
In Brazil, automated landform identification was developed for Paraná State (SILVEIRA, SILVEIRA, 2015), and the central region of the Serra do Mar Paranaense (SILVEIRA, SILVEIRA, 2016), which were defined from the automated crossing of slope declivity and height
Summary
Landforms are defined by the spatial arrangement of homogeneous surfaces resulting from the action of tectonic forces that provoke uplifts and relegation, and agents of the terrestrial surface that act on rocky materials, decomposing and disaggregating them over time to develop different features and forms. In Brazil, Ross (1992) has made an important contribution to landform analysis, based on Demek's proposed taxonomic classification (1967), recommending the division of the relief into six different taxa. The development of geoprocessing methods and GIS means the terrestrial surface can be represented through digital models (DEM), which allow the topographic analysis of a zone of interest, as well as the automated calculation of a series of related variables. Wood’s (1996, apud SENA-SOUZA et al, 2015) method considers a specific combination of longitudinal/transversal and minimum/maximum curvature pairs depending on the slope of the region to be classified and identifies six Terrain Forms (TFs): Plane, Channel, Ridge, Saddle, Peak, and Pit. In Brazil, automated landform identification was developed for Paraná State (SILVEIRA, SILVEIRA, 2015), and the central region of the Serra do Mar Paranaense (SILVEIRA, SILVEIRA, 2016), which were defined from the automated crossing of slope declivity and height
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