Post-doctoral research projects develop innovative new skills, expertise and applications of Copernicus data and services for the raw materials sector.

Integration of space-borne remote sensing data with geophysical and geological data for exploration of IOCG mineralizations

Integration of space-borne remote sensing data with geophysical and geological data for exploration of IOCG mineralizations (IOCG-SENSE) is hosted and carried out under the auspices of Luleå Technical University in cooperation with the Geological Survey of Denmark and Greenland (GEUS), Birla Institute of Technology Mesra, India and Helvetica Exploration Services GmbH, Switzerland.

Researcher: Mehdi Abdolmaleki

Supervisor: Professor Thorkild M. Rasmussen

Project Summary:

IOCG-SENSE aims at establishing optimum procedures for integrating space-borne remote sensing Sentinel-2 data with other geoscientific data and information for Iron Oxide Copper Gold (IOCG) exploration. The focus of this project is Sentinel-2 data from the high Arctic, where problems of interpreting remote sensing data due to vegetation cover in general is at a minimum and where geological exposures are excellent. The developed procedures shall be verified and evaluated based on data from Greenland. Areas selected are (1) Inglefield Land in Northwest Greenland and (2) South Greenland.

Data integration is in general acknowledged as a key parameter for successful and optimised mineral exploration, and IOCG-SENSE shall ensure that procedures for extracting and utilization of information from remote sensing data are developed. The fact that Sentinel data has no depth penetration furthermore emphasises the importance of performing joint interpretation with data providing information at depth. Airborne geophysical data and geochemical data from stream sediments and rock exposures will be utilized in an integrated approach for IOCG exploration.

The objectives of the project are:

  1. Assessment of the potential of combined Sentinel 2 and other sources of geoscientific data for IOCG targeting
  2. Investigate which and in particular which combinations of data features are indicative of mineralization and how these features can help in the structural interpretation and target identification
  3. Development and test of classification tools
  4. Develop a combined data driven and knowledge driven approach for IOCG exploration

 

 

 

View of IOCG exposure in Inglefield Land 

 

 

 


Airborne geophysical data

 

 

 

 

 

 

 

 

Selected areas in Greenland for verification of methodology

Copernicus for contamination monitoring and decision support in active mining and rehabilitation 

CoCoMo is carried out and supervised by the Institute for Mine Surveying and Geodesy at the TU Bergakademie Freiberg. Support is provided by the EIT RawMaterials partner EFTAS and associated partners from the mining industry.

Postdoctoral Researcher: Dr. Christian Köhler

Supervisor: Prof. Dr.-Ing. Jörg Benndorf

Project Summary:

Mining activities strongly influence the environment, e.g. by causing ground movements or producing contaminated waste dumps and water entities during the active operation and rehabilitation phases. Thus monitoring and managing the contamination is essential, as it reduces environmental impact and therefore increases social acceptance.

CoCoMo aims at the development of a contamination monitoring and decision support/early warning system for active and closed mining facilities. The project focuses on the vicinity of media pipelines of gas and oil storage caverns and waste dumps of active and abandoned mines. We target the integration and exploitation of multi-scale spatio-temporal data originating from Copernicus Sentinel satellites, unmanned aerial vehicles (UAVs) and ground based in-situ measurements.

This Remote Sensing (Sentinel, UAV) approach for environmental monitoring and early-warning systems, supported by ground based in-situ data, delivers spatially and temporally dense information. That, in turn, renders automatisation of the contamination analysis feasible, opening an avenue for cost effective and nearly real-time monitoring products.

Mine operators face the request of legal authorities for monitoring solutions as prerequisite for issuing operation permits. The primarily manual, terrestrial monitoring commonly in use today is costly in terms of money, time and man power, potentially dangerous for personal safety and, in addition, limited to small spatial areas and long measurement intervals. Thus, cost effective remote sensing-based monitoring solutions that deliver comprehensive data are highly desired by mine operators, engineering companies (offering monitoring and consulting services) or after care associations.

The public’s increased interest in mining related environmental impacts requires reassesment and readjustment of social acceptance – a considerable business risk in the mining sector. CoCoMo‘s open-source project results and publically-available Copernicus data increase transparency in communication between mining companies and public stakeholders (social and environmental initiatives, governmental bodies). Together with the education of future players in the mining industry through dissemination of results in the scientific community, this reduces environmental impact, increases social acceptance and ensures save and effective operation.

The objectives of the project are:

  1. Integrate multi-scale (Copernicus Sentinel, UAV, ground-based), multi- and hyperspectral spatio-temporal data into one comprehensive data product.
  2. Assess the potential of multidimensional spatio-temporal data for environmental contamination monitoring
  3. Development of workflows and algorithms for early, nearly real-time identification of potentially contaminated areas

Image 1: Redness Index (ri) as exemplary multi-spectral index in a region where contamination occurred. Characteristic changes in the temporal evolution of ri indicate potential contamination.

Image 2: Time series of the Redness Index (ri) as exemplary multi-spectral index in a region where contamination occurred. ‚Contaminated region‘ refers to the right red rectangle, ‚not contaminated region‘ to the left red rectangle in the figure above. Characteristic changes in the temporal evolution of ri indicate potential contamination.

Sampling optimization in stockpiles/tailings, for grade mapping of raw materials using geostatistical analysis and Earth Observation data

The project is hosted and carried out under the auspices of University of Bologna (UNIBO) (Georesources Engineering Group) with the support of the “Geomatics” and “Geology” groups. The Universities and Research partners of the EIT RawMaterials community, namely DELFT, ENEA and NTUA are providing case studies and Lab facilities for the project. Additional case study is provided by DANU.

Researcher: Dr. Sara Kasmaee
Supervisors: Prof. Dr. Roberto Bruno and Prof. Dr. Stefano Bonduà, University of Bologna

Project Summary:

The mine industry produces millions of tons of waste with low grade contents of minerals, usually referred to as stockpiles/tailings (secondary raw material resources). New technologies enable the recovery of valuable materials from these stockpiles/tailings coupling economic and environmental benefits. To obtain grade maps of stockpiles/tailings, survey sampling is necessary. Sampling can be an expensive and time-consuming phase and, in general, the higher the number of samples available, the greater the accuracy of the maps that can be provided. Hence, design of an optimum sampling plan is essential. On the other hand, Earth Observation (EO) data like that available from Copernicus Land Services can be an additional source of information about tailings. The Copernicus data needs to be integrated with in situ data in order to improve the map accuracy.

Geostatistical methods, using data coming from in situ sampling and EO images will lead to innovative methods to produce improved accuracy grade maps. Since reducing the number of samples, even by one, has an outstanding costs advantage; the final achievements of the research can provide important benefits not only for governmental/industrial sectors to acquire new precious sources of Critical Raw Materials (CRMs), but also to monitor and validate the Copernicus data and maps by reducing the more expensive in situ sampling methods.

Figure 1: Interaction of geostatistical models (a) and EO data (b) for sample optimization (c)

The objectives of the project are:

  • Adapting innovative geostatistical methods on sampling optimization and use of EO data;
  • Using high resolution stereo-images (Copernicus data) for initial assessments of stockpiles and tailings;
  • Performing the research framework on a real case study;
  • Monitoring and validating Copernicus maps;
  • Supporting governmental/industrial sectors involved into CRMs prospecting.

Integration of Copernicus data in a multi-scale and multi-source exploration scheme

The project is hosted and carried out under the auspices of Helmholtz-Zentrum Dresden Rossendorf, Helmholtz Institute Freiberg for Resource Technology with support from the two other partners of the EIT RawMaterials community, Geological Survey of Finland (GTK), and Geological Survey of Denmark and Greenland (GEUS).

Researcher: Dr. Louis Andreani

Supervisor: Dr. Richard Gloaguen & Dr. Moritz Kirsch, Helmholtz Institute Freiberg for Resource Technology

Project Summary:

Mineral exploration needs time-saving, cost effective, and,

particularly in Europe, environmentally friendly and socially acceptable techniques to ensure sustainable access to raw materials in the EU. The objective of this research project is to develop an efficient and integrated exploration workflow with the inclusion of multi-source remote sensing data at satellite to near-field scale. Geological remote sensing offers a cost- effective way of exploring mineral resources but its full synergetic potential remains to be demonstrated. So far, a variety of multi- and hyperspectral, SAR, air- and satellite-based sensors are usually used individually to obtain qualitative and (semi-)quantitative information on the composition or structure of the surface. However, new methods are needed for geological applications as a consequence of the limitations of space-borne sensors with respect to their spatial and/or spectral resolution. We propose to overcome these problems by integrating satellite data, drone-borne data, geomorphic analyses and ground campaigns into new and adapted concepts for ground monitoring methods.

The objectives of the project are:

  1. To test the integration of multispectral (Sentinel2 and ASTER), SAR (Sentinel1) and DEM-based geomorphic analyses for mineral exploration
  2. To create new and adapted concepts for a combined use of satellite- and drone-based multi-sensor observations and ground monitoring methods
  3. To test the suitability of different Machine Learning algorithms in order to define classification schemes adapted to mineral exploration
  4. To create approaches that have high-performance in terms of environmental impact and cost

For more information contact info@rawmatcop.training

Spatiotemporal mapping of dust dispersion around mining sites using remote sensing

The project is hosted and carried out under the auspices of University of Liège, GeMMe – Georesources & Geoimaging Lab with the support of the “Remote Sensing for Mineral Mapping” group at CSIRO (Perth, Australia) and industrial partners of the EIT RawMaterials community, namely ERAMET and ArcelorMittal.

Researcher: Dr. Elsy Ibrahim

Supervisor: Prof. Dr. Ir. Eric Pirard, University of Liège

Project Summary:

MINeoDUST aims to explore the potential of Copernicus data in mine site monitoring and especially in mapping dust dispersion patterns around active sites. Previous studies of similar problems in Australia and in Europe have been performed with airborne hyperspectral data (HyMap) or discontinued spaceborne data (ASTER) offering both higher spatial and spectral resolutions. Nevertheless, the proven potential of Sentinel 2 for mapping iron oxides and the use of the most recent multi-sensor fusion/classification techniques open a window of opportunities to serve the raw materials community. This project also considers the high revisiting time of the Sentinel 2 programme as another very interesting asset when it comes to mapping the dynamic of dust dispersion around extractive sites, but also transportation (rail, road) and loading sites (ports). MINeoDUST will be hosted by the University of Liège and more specifically the GeMMe – Georesources & Geoimaging Lab. This lab is a member of EARSEL and has a team made up of both field geologists and digital imaging specialists. ULiège also hosts the famous CSL (Centre Spatial de Liège), one of ESA’s four test sites for satellites with specialization in optics and imaging, offering a unique opportunity for this project to also come up with recommendations for future missions. The project builds on a close partnership with the “Remote Sensing for Mineral Mapping” group at CSIRO in Perth (Dr Ramanaidou – Commodity Research Leader Fe and Lateritic Ni). This group is currently collecting field data on test sites in New Caledonia. Two major mining companies, Eramet, and ArcelorMittal, have already provided letters of support to the project, and confirming that other EIT RawMaterials industrial partners with test sites in iron, manganese, bauxite and Ni-laterite mining will be involved.

The objectives of the project are:

  1. Assessment of the potential of combined Sentinel 2 and other sources of remotely sensed data like LANDSAT to evaluate the spatiotemporal distribution of iron oxides containing dust particles
  2. Development of fusion and classification methodologies to take full advantage of the combined Sentinel 2 and other sources of remote sensing data
  3. Definition of future specifications for spaceborne missions to address the needs of environmental monitoring of mining sites, mineral transportation sites (railway, ports, etc.) and storage sites
  4. To explore the potential for sharing remote sensing data with all stakeholders of a mining project through open data platforms (Map-X a joint UNEP-WorldBank initiative for the extractive industry)

For more information contact info@rawmatcop.training

Earth’s Critical Zone Early Warning System by integrating SAR and seismic data in a mining context

The project is hosted and carried out under the auspices of Institute of Geosciences (IGEO), Spanish National Research Council (CSIC) with support from the companies, DARES (remote sensing) and Atalaya Mining (site owner).

Researcher: Dr. Ignacio Marzán

Supervisor: Dr. José Fernández Torres, Institute of Geosciences (IGEO), Spanish National Research Council (CSIC)

Summary

No doubt mining activities strongly impact the Earth’s Critical Zone (CZ), the near surface environment where rock meets life. As a consequence, public perception of the mining industry is usually negative. Our project aims to improve mining viability/security by guaranteeing ground/underground CZ integrity. Our strategy approaches the target from two sides, from above with satellite data, and from below with seismic data. Our main outcome will be a CZ Early Warning System (CZ-EWS) protocol affordable for the mining industry, combining satellite and geophysical monitoring techniques. The pilot site is located in Minas de Riotinto; characterizing and monitoring this site is of special interest for the long registry of mining activities as well as for SAR data availability, since 1992 (ERS-1). Apart from the PostDoc fellow, the team is formed of three CSIC specialists (in remote sensing, seismic and mining ) and two companies: DARES (SAR software developers) and Atalaya Mining (host site).

The objectives of the project are:

Overall objective: To reduce the hazards of mining activities affecting the soil/subsoil mechanical integrity developing a monitoring system that combines SAR and passive seismic data.

Specific objective 1: To correlate ground deformation and historical mining events in Riotinto mine

Specific objective 2: To evaluate resolution of Sentinel-1 vs commercial satellites at mining scale

Specific objective 3: To elaborate a 3D velocity model for Riotinto mine

Specific objective 4: To identified instability zones around Riotinto mine

Specific objective 5: To design a low cost monitoring program for mining activities integrating passive seismic and SAR

For more information contact info@rawmatcop.training