Spectral Pattern Classification in Lidar Data for Rock Identification in Outcrops

• Main Authors: Leonardo Campos Inocencio, Mauricio Roberto Veronez, Francisco Manoel Wohnrath Tognoli, Marcelo Kehl de Souza, Reginaldo Macedônio da Silva, Luiz Gonzaga Jr, César Leonardo Blum Silveira
• Format: Article
• Language: English
• Published: Hindawi Limited 2014-01-01
• Series: The Scientific World Journal
• Online Access: http://dx.doi.org/10.1155/2014/539029
• ISSN: 2356-6140; 1537-744X

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.