Aplicação dos algoritmos GAIA-GEOROC e Discontinuity Set Extractor - DSE para detecção de descontinuidades em áreas específicas da região serrana do Rio de Janeiro.

Abstract

Obtaining discontinuity measurements in weathered and steep areas is usually a complex and dangerous activity. The importance of this study is to evaluate, in a safe way, for collecting measures of discontinuities in risk areas by indirect methods. This work presents the application of two semi-automatic methods for characterization of rock mass discontinuities that use 3D point clouds, which can be obtained through non-contact measurement techniques, such as photogrammetry and Light Detection and Ranging (LiDAR). Gaia-GeoRoc and DSE are methods that determine similar parameters, such as, orientation, trace, spacing and roughness, which are extracted semi-automatically. The Gaia-Georoc methodology is based on a visual classification of the 3D point cloud using the hue-saturation-value color scheme and a normal vector with spherical means K. DSE bases its analysis on a neighboring point coplanarity test, Kernel density estimation and density-based scanning algorithm with noise. The proposed methods were applied in a specific area of the mountainous region of Rio de Janeiro, which presents two distinct behaviors, rockfall and planar sliding, in order to compare the products with each other and with conventional mapping. The results of the application showed that the methodologies did not allow to detect discontinuities contained in the weathered part in detail, but the products are good for more well-defined outcrops or for a preliminary assessment. In conclusion, the analyzed tools have some limitations, but are efficient as preliminary forms of assessment in risk areas.