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The Scientific World Journal
Volume 2014 (2014), Article ID 539029, 10 pages
Research Article

Spectral Pattern Classification in Lidar Data for Rock Identification in Outcrops

1VIZLab, Advanced Visualization Laboratory, UNISINOS, 93022-000 São Leopoldo, RS, Brazil
2PPGEO, Graduate Program on Geology, UNISINOS, 93022-000 São Leopoldo, RS, Brazil
3PIPCA, Applied Computer Science Graduate Program, UNISINOS, 93022-000 São Leopoldo, RS, Brazil
4V3D, Studios & Ficta Mobile Technologies, 93022-000 São Leopoldo, RS, Brazil

Received 8 August 2013; Accepted 21 November 2013; Published 18 February 2014

Academic Editors: P. Fonseca, K. Nemeth, C. M. Petrone, and L. Tosi

Copyright © 2014 Leonardo Campos Inocencio et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The present study aimed to develop and implement a method for detection and classification of spectral signatures in point clouds obtained from terrestrial laser scanner in order to identify the presence of different rocks in outcrops and to generate a digital outcrop model. To achieve this objective, a software based on cluster analysis was created, named K-Clouds. This software was developed through a partnership between UNISINOS and the company V3D. This tool was designed to begin with an analysis and interpretation of a histogram from a point cloud of the outcrop and subsequently indication of a number of classes provided by the user, to process the intensity return values. This classified information can then be interpreted by geologists, to provide a better understanding and identification from the existing rocks in the outcrop. Beyond the detection of different rocks, this work was able to detect small changes in the physical-chemical characteristics of the rocks, as they were caused by weathering or compositional changes.