Francisco Manoel Wohnrath Tognoli

Spectral Pattern Classification in Lidar Data for Rock Identification in Outcrops

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.

An algorithm for automatic detection and orientation estimation of planar structures in LiDAR-scanned outcrops

The spatial orientation of linear and planar structures in geological fieldwork is still obtained using simple hand-held instruments such as a compass and clinometer. Despite their ease of use, the amount of data obtained in this way is normally smaller than would be considered as representative of the area available for sampling. LiDAR-based remote sensors are capable of sampling large areas and providing huge sets of digitized spatial points. However, the visual identification of planes in sets of points on geological outcrops is a difficult and time-consuming task. An automatic method for detecting and estimating the orientation of planar structures has been developed to reduce analysis and processing times, and to fit the best plane for each surface represented by a set of points and thus to increase the sampled area. The algorithm detects clusters of points that are part of the same plane based on the principal component analysis (PCA) technique. When applied to real cases, it has shown high precision in both the detection and orientation of fractures planes. HighlightsWe propose a method for plane detection and orientation in LiDAR point clouds.The method, simple and automatic, is statistical in its essence, using PCA.The whole point cloud is sequentially sub-divided until planar patches are found.It opposes other methods that search for small planer patches and expand it outwards.

Identification and quantification of kaolinite in mixtures with goethite using short-wave infrared (SWIR) reflectance spectroscopy

We investigate here the potential of the spectroscopy in the identification and quantification of mixtures of kaolinite and goethite from the Continuum Removal (CR) of the spectra in the short-wave infrared. For this purpose, spectral measurements of the kaolinite, goethite, and controlled mixtures of these minerals were systematically performed. The continuum of the results were removed, the depth of the kaolinite diagnostic absorption was calculated and compared with a spectral library. It was possible to identify the kaolinite with high determination coefficient (R2>0.95) when its proportion reaches at least 60% in the mixture. For quantification purposes, it was possible to quantify kaolinite using the diagnostic absorption feature depth in the CR with a coefficient of determination of 0.99.

Digital field book for geosciences

In this study we present a mobile application for geoscience. It refers to a digital field book for automating data collection and outcrop/core description, and optimizing the final data processing. Sensors were developed for semi-automatic data collection, real time calculations, measurements of dip angles and dip directions, geographic location, among others. Field tests were performed comparing the traditional method with the proposed digital method. The preliminary results show a good acceptance of the mobile application by geoscientists and an improvement in the time required to perform data collection. Field tests are still going on and the complete results will be used to improve the development of this important tool in geoscience field work.

An intensity recovery algorithm (IRA) for minimizing the edge effect of LIDAR data

Abstract The terrestrial laser scanner is an equipment developed for surveying applications and is also used for many other purposes due to its ability to acquire 3D data quickly. However, before intensity data can be analyzed, it must be processed in order to minimize the edge or border effect, one of the most serious problems of LIDARs intensity data. Our research has focused on characterizing the edge effect behavior as well as to develop an algorithm to minimize edge effect distortion automatically (IRA). The IRA showed to be effective recovering 35.71% of points distorted by the edge effect, providing significant improvements and promising results for the development of applications based on TLS data intensity to many studies.

Divulgação de dados ambientais e socioeconômicos na internet usando um modelo baseado no uso de ferramentas livres

Um modelo baseado no uso de ferramentas livres e apresentado, visando a publicacao de dados socioeconomicos e ambientais e divulgacao de informacoes na internet. A estrutura deste modelo permite que as informacoes sejam apresentadas sob a forma de tabelas, graficos, fotos ou mapas para a web. A escolha de um determinado formato de apresentacao da informacao e determinada de acordo com os objetivos do desenvolvedor. Como resultado do trabalho, o usuario criara um banco de dados geograficos virtual para gerar informacoes estaticas e mapas interativos para a web. As principais ferramentas utilizadas foram o sistema de informacoes geograficas Spring, banco de dados relacional MySQL, PHP script e o servidor Apache HTTP. Palavras-chave: mapeamento via Web, ferramentas livres, Spring Web, Sistema de Informacao Geografica.