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Richard Gloaguen

Richard Gloaguen
Helmholtz Institute Freiberg of Resource Technology · Exploration Technology

PhD
Looking for workforce in Machine Learning, Earth Observation and Computer Vision

About

342
Publications
162,622
Reads
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6,108
Citations
Introduction
I lead the division Exploration Technology at the Helmholtz-Institute Freiberg for Resource Technology. We now focus on (1) multiscale active or passive spectroscopy, (2) UAV based remote sensing and (3) the analysis of multisource data to improve mineral mapping. Additionally, we cover some aspects of 3D modelling and geophysics.
Additional affiliations
March 2015 - May 2020
Helmholtz Institute Freiberg of Resource Technology
Position
  • Head
January 2009 - March 2013
Technische Universität Bergakademie Freiberg
Position
  • Remote sensing based hydrological modelling
January 2007 - April 2013
Technische Universität Bergakademie Freiberg
Position
  • Group Leader
Education
October 1997 - October 2000
Université de Bretagne Occidentale
Field of study
  • Marine Geosciences

Publications

Publications (342)
Article
Full-text available
Abstract Rare earth elements (REEs) supply is important to ensure the energy transition, e-mobility and ultimately to achieve the sustainable development goals of the United Nations. Conventional exploration techniques usually rely on substantial geological field work including dense in-situ sampling with long delays until provision of analytical r...
Article
Full-text available
The widespread application of drones and associated miniaturization of imaging sensors has led to an explosion of remote sensing applications with very high spatial and spectral resolutions. The 3-D ultrahigh-resolution digital outcrop models created using drones and oblique imagery from ground-based sensors are now commonly used in the academic an...
Article
Full-text available
The digitization and automation of the raw material sector is required to attain the targets set by the Paris Agreements and support the sustainable development goals defined by the United Nations. While many aspects of the industry will be affected, most of the technological innovations will require smart imaging sensors. In this review, we assess...
Article
Full-text available
Drastic measures are required to meet the standards of the Paris Agreement and limit the increase of global average temperatures well below 2°C compared to pre-industrial levels. Mining activities are typically considered as unsustainable but, at the same time, metals such as cobalt and lithium are essential to sustain the energy transition. Severa...
Article
Full-text available
Efficient, socially acceptable and rapid methods of exploration are required to discover new deposits and enable the green energy transition. Sustainable exploration requires a combination of innovative thinking and new technologies. Hyperspectral imaging (HSI) is a rapidly developing technology and allows for fast and systematic mineral mapping, f...
Article
Full-text available
Hyperspectral imaging is an innovative technology for non-invasive mapping, with increasing applications in many sectors. As with any novel technology, robust processing workflows are required to ensure a wide use. We present an open-source hypercloud dataset capturing the complex but spectacularly well exposed geology from the Black Angel Mountain...
Article
Full-text available
Hyperspectral drill-core scanning adds value to exploration campaigns by providing continuous, high-resolution mineralogical data over the length of entire boreholes. However, multivariate mineralogical data must be transformed into lithological domains such that it is compatible with interpolation techniques and be usable for geomodeling. Manual i...
Article
Full-text available
Magnetic data can be acquired from a number of different platforms (e.g., ground, drone, helicopter) using a variety of sensors (e.g., cesium vapor‐type optically pumped magnetometers [OPM], fluxgate, superconducting quantum interference devices [SQUID]) with different flight line configurations. To detect a magnetic anomaly associated with a miner...
Preprint
Full-text available
As with any physical instrument, hyperspectral cameras induce different kinds of noise in the acquired data. Therefore, Hyperspectral denoising is a crucial step for analyzing hyperspectral images (HSIs). Conventional computational methods rarely use GPUs to improve efficiency and are not fully open-source. Alternatively, deep learning-based method...
Article
Full-text available
Mineral exploration in the West Greenland flood basalt province is attractive because of its resemblance to the magmatic sulfide-rich deposit in the Russian Norilsk region, but it is challenged by rugged topography and partly poor exposure for relevant geologic formations. On northern Disko Island, previous exploration efforts have identified rare...
Chapter
Full-text available
Multi- and hyperspectral (MS and HS) imaging are currently deployed at a wide range of spatial dimensions (“scales”), ranging from satellites observing the Earth and other planets down to lab-scale sensing for small sample spectral analysis. New techniques such as UAV-borne imaging or terrestrial scanning of vertical targets are emerging and allow...
Article
Full-text available
Ambient seismic noise tomography is a novel, low-impact method for investigating the earth's structure. Although most passive seismic studies focus on structures on crustal scales, there are only a few examples of this technique being applied in a mineral exploration context. In this study, we performed an ambient seismic experiment to ascertain th...
Article
Deep subspace clustering (DSC) has achieved remarkable performances in the unsupervised classification of hyperspectral images. However, previous models based on pixel-level self-expressiveness of data suffer from the exponential growth of computational complexity and access memory requirements with an increasing number of samples, thus leading to...
Article
Full-text available
Remote sensing hyperspectral cameras acquire high spectral-resolution data that reveal valuable composition information on the targets (e.g., for Earth observation and environmental applications). The intrinsic high dimensionality and the lack of sufficient numbers of labeled/training samples prevent efficient processing of hyperspectral images (HS...
Article
Aeromagnetic data is routinely acquired by mineral exploration programs. The objective is to obtain a raster image of the spatial variations of magnetic field intensity, these variations are associated with mineralogical variations in the subsurface. When the survey is conducted in a populated area much of the signal, however may be associated with...
Article
Full-text available
While uncrewed aerial vehicles are routinely used as platforms for hyperspectral sensors, their application is mostly confined to nadir imaging orientations. Oblique hyperspectral imaging has been impeded by the absence of robust registration and correction protocols, which are essential to extract accurate information. These corrections are especi...
Article
Full-text available
Subspace clustering methods have become a powerful tool to cluster hyperspectral imaging data (HSI) as they ensure theoretical guarantees and empirical success. However, existing methods simply explore subspace representation in the Euclidean domain, meaning that high-order structural information in HSI is ignored, which may lead to poor robustness...
Article
Full-text available
The ever-growing developments in technology to capture different types of image data (e.g., hyperspectral imaging and Light Detection and Ranging (LiDAR)-derived digital surface model (DSM)), along with new processing techniques, have led to a rising interest in imaging applications for Earth observation. However, analyzing such datasets in paralle...
Article
Full-text available
We propose a new fusion-based classification technique for optical multi-source remote sensing images called OptFus. OptFus is developed to merge and process optical imagery having different spatial and spectral resolutions. The spatial features are extracted using morphological filters from the RGB data containing high spatial resolution. A featur...
Preprint
Full-text available
Mineral exploration in the West Greenland flood basalt province is attractive because of its resemblance to the magmatic sulphide-rich deposit in the Russian Norilsk region, but it is challenged by rugged topography and partly poor exposure for relevant geologic formations. On northern Disko Island, previous exploration efforts have identified rare...
Preprint
Full-text available
Ambient seismic noise tomography is a novel, low-impact method to investigate the Earth’s structure. While most passive seismic studies focus on structures at crustal scales, there are only few examples of this technique being applied in a mineral exploration context. In this study, we performed an ambient seismic experiment to ascertain the relati...
Conference Paper
Conventional mineral exploration methods are usually based on extensive field work supported by geophysical surveying. These techniques can be restricted by field accessibility, financial status, area size and climate. Additionally, these methods can have a considerable footprint on the environment, upsetting the surrounding community and resulting...
Article
Full-text available
Drill-core analysis is paramount for the characterization of deposits in mineral exploration. Over the past years, the use of hyperspectral (HS) sensors has rapidly increased to improve the reliability and efficiency of core logging. However, scanning drill-core samples of an entire mineral deposit entails several complex challenges, from transport...
Article
Full-text available
With the recurring interest in rare earth elements (REEs), laser-induced fluorescence (LiF) may provide a powerful tool for their rapid and accurate identification at different stages along their value chain. Applications to natural materials such as minerals and rocks could complement the spectroscopy-based toolkit for innovative, non-invasive exp...
Conference Paper
Drones are getting more and more used to replace piloted platforms to reduce the costs and increase safety of activities such as monitoring, delivery or warfare. So far though, drones have barely been used as more than single-sensor platforms. In order to be used in mineral exploration we need to ensure that the data acquired by drones are versatil...
Article
Full-text available
Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and fast mapping of mineral phases and alteration patterns. The use of adapted machine learning technique...
Article
Full-text available
Enhanced digital outcrop models attributed with hyperspectral reflectance data, or hyperclouds, provide a flexible, three-dimensional medium for data-driven mapping of geological exposures, mine faces or cliffs. This approach allows the collection of spatially contiguous information on exposed mineralogy and so provides key information for understa...
Article
Full-text available
Better quality control for alloy manufacturing and sorting of post-consumer scraps relies heavily on the accurate determination of their chemical composition. In recent decades, analytical techniques, such as X-ray fluorescence spectroscopy (XRF), laser-induced breakdown spectroscopy (LIBS), and spark optical emission spectroscopy (spark-OES), foun...
Article
Full-text available
The exposure of metal sulfides to air or water, either produced naturally or due to mining activities, can result in environmentally damaging acid mine drainage (AMD). This needs to be accurately monitored and remediated. In this study, we apply high-resolution unmanned aerial system (UAS)-based hyperspectral mapping tools to provide a useful, fast...
Conference Paper
Full-text available
In this work, we present the selected results from the Innovative, Non-invasive and Fully Acceptable Exploration Technologies (INFACT) project, funded by Horizon 2020 research and innovation programme. We evaluated different geophysical data against the known geological and infrastructural challenges in two reference sites of INFACT, Sakatti (Finla...
Chapter
The field of remote sensing has recently witnessed major innovations that have been translated to Earth science applications. Before they can be used, remote sensing data must be corrected for effects originating from the sensors, the platforms on which they are deployed, atmospheric characteristics, and geometrical constraints. When the data are c...
Article
Full-text available
The increasing amount of information acquired by imaging sensors in Earth Sciences results in the availability of a multitude of complementary data (e.g., spectral, spatial, elevation) for monitoring of the Earth’s surface. Many studies were devoted to investigating the usage of multi-sensor data sets in the performance of supervised learning-based...
Article
The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral imagery has led to significant improvements in terms of classification performance. The task of spectral-spatial hyperspectral image (HSI) classification has remained challenging because of high intraclass spectrum variability and low interclass spectra...
Preprint
Full-text available
With the recurring interest on rare-earth elements (REE), laser-induced fluorescence (LiF) may provide a powerful tool for their rapid and accurate identification at different stages along their value chain. Applications to natural materials such as rocks could complement the spectroscopy-based toolkit for innovative, non-invasive exploration techn...
Preprint
Full-text available
The inclusion of spatial information into spectral classifiers for fine-resolution hyperspectral imagery has led to significant improvements in terms of classification performance. The task of spectral-spatial hyperspectral image classification has remained challenging because of high intraclass spectrum variability and low interclass spectral vari...
Article
Hyperspectral (HS) imaging holds great potential for the mapping of geological targets. Innovative acquisition modes such as drone-borne or terrestrial remote sensing open up new scales and angles of observation, which allow to analyze small-scale, vertical, or difficult-to-access outcrops. A variety of available sensors operating in different spec...
Article
Full-text available
Mapping geological outcrops is a crucial part of mineral exploration, mine planning and ore extraction. With the advent of unmanned aerial systems (UASs) for rapid spatial and spectral mapping, opportunities arise in fields where traditional ground-based approaches are established and trusted, but fail to cover sufficient area or compromise persona...
Article
Full-text available
Combining both spectral and spatial information with enhanced resolution provides not only elaborated qualitative information on surfacing mineralogy but also mineral interactions of abundance, mixture, and structure. This enhancement in the resolutions helps geomineralogic features such as small intrusions and mineralization become detectable. In...
Conference Paper
Full-text available
A multi-label classification concept is introduced for the mineral mapping task in drill-core hyperspectral data analysis. As opposed to traditional classification methods, this approach has the advantage of considering the different mineral mixtures present in each pixel. For the multi-label classification, the well-known Classifier Chain method (...
Conference Paper
Full-text available
In the past decade, hyperspectral imaging techniques have been widely used in various applications to acquire high spectral-spatial resolution images from different objects and materials. Although hyperspectral images (HSIs) are useful tools to obtain valuable information from different materials, the processing of such data is challenging due to s...
Article
Full-text available
Hyperspectral imaging techniques are becoming one of the most important tools to remotely acquire fine spectral information on different objects. However, hyperspectral images (HSIs) require dedicated processing for most applications. Therefore, several machine learning techniques were proposed in the last decades. Among the proposed machine learni...
Article
Full-text available
The analysis of drill-core samples is one of the most important steps in the mining industry for the exploration and discovery of mineral resources. Geochemical assays are a common approach to represent the abundance of different chemical elements and aid at quantifying the concentrations of the important ore accumulations. However, their acquisiti...
Article
Full-text available
In recent times, rare earth orthophosphates (LnPO 4) have shown great potential as efficient optical materials. They possess either monazite or xenotime-type structures. These light or heavy rare earth bearing orthophosphates also exhibit an extraordinary stability over geological time scale in nature, ∼10 9 years. In the present contribution, we m...