
Sandra LorenzHelmholtz-Zentrum Dresden-Rossendorf | HZDR · Institute Freiberg for Resource Technology
Sandra Lorenz
Dr. rer. nat.
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85
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Publications (85)
Unmanned Aerial Vehicles (UAVs), commonly known as drones, are omnipresent and have grown in popularity due to their wide potential use in many civilian sectors. Equipped with sophisticated sensors and communication devices, drones can potentially form a multi-UAV system, also called an autonomous swarm, in which UAVs work together with little or n...
Hyperspectral imaging is gaining widespread use in the resource sector, with applications in mineral exploration, geometallurgy and mine mapping. However, the sheer size of many hyperspectral datasets (>1 Tb) and associated correction, visualisation and analysis challenges can limit the integration of this technique into time-critical exploration a...
We argue that traditional 2D hyperspectral imaging is not adapted to many modern challenges. With the rise of high spatial resolution, hyperspectral sensors mounted on different platforms (e.g. drones, terrestrial, satellites) and innovative applications (e.g. urban mapping, mining monitoring), projections, occlusions, perspective effects and data...
Robot Operating System (ROS) has proven itself as a viable framework for developing robot-related applications. It offers features such as hardware abstraction, low-level device support, inter-process communication, and useful libraries for autonomous robot systems. Concerning aerial robots, commonly called unmanned aerial vehicles (UAV) or drones,...
The new generation of satellite hyperspectral (HS) sensors provides remarkable potential for regional-scale mineralogical mapping. However, as with any satellite sensor, mapping results are dependent on a typically complex correction procedure needed to remove atmospheric, topographic and geometric distortions before accurate reflectance spectra ca...
Addressing the critical theme of recycling electronic waste (E-waste), this contribution is dedicated to developing advanced automated data processing pipelines as a basis for decision-making and process control. Aligning with the broader goals of the circular economy and the United Nations (UN) Sustainable Development Goals (SDG), our work leverag...
Polymers represent around 25% of total waste from electronic and electric equipment. Any successful recycling process must ensure that polymer-specific functionalities are preserved, to avoid downcycling. This requires a precise characterization of particle compounds moving at high speeds on conveyor belts in processing plants. We present an invest...
Hyperspectral imaging is gaining widespread use in the resource sector, with applications in mineral exploration, geometallurgy, and mine mapping. However, the sheer size of many hyperspectral datasets (>1 Tb), and associated data correction and analysis challenges, limit the integration of this technique into time-critical exploration and mining w...
Hyperspectral data is challenging to visualise, especially when working with multiple data cubes from different sensors, acquisition times or covering different subjects (e.g., drill core or sample scanning campaigns). Existing tools are either commercial and closed-source or relatively limited in functionality, especially when working with multipl...
Considering the increasing demand for Li-ion batteries, there is a need for sophisticated recycling strategies with both high recovery rates and low costs. Applying optical sensors for automating component detection is a very promising approach because of the non-contact, real-time process monitoring and the potential for complete digitization of m...
Addressing the critical theme of recycling electronic waste (E-waste), this contribution is dedicated to developing advanced automated data processing pipelines as a basis for decision-making and process control. Aligning with the broader goals of the circular economy and the United Nations (UN) Sustainable Development Goals (SDG), our work leverag...
Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-qualit...
The increasing use of deep learning techniques has reduced interpretation time and, ideally, reduced interpreter bias by automatically deriving geological maps from digital outcrop models. However, accurate validation of these automated mapping approaches is a significant challenge due to the subjective nature of geological mapping and the difficul...
In this work, we generated a comprehensive laboratory ground truth dataset of intimately mixed mineral powders. For this, five clay powders (Kaolin, Roof clay, Red clay, mixed clay, and Calcium hydroxide) were mixed homogeneously to prepare 325 samples of 60 binary, 150 ternary, 100 quaternary, and 15 quinary mixtures. Thirteen different hyperspect...
Optical hyperspectral cameras capture the spectral reflectance of materials. Since many materials behave as heterogeneous intimate mixtures with which each photon interacts differently, the relationship between spectral reflectance and material composition is very complex. Quantitative validation of spectral unmixing algorithms requires high-qualit...
The inherent complexity of underground mining requires highly selective ore extraction and adaptive mine planning. Repeated geological face mapping and reinterpretation throughout mine life is therefore routine in underground mines. Hyperspectral imaging (HSI) has successfully been applied to enhance geological mapping in surface mining environment...
Deep learning techniques are commonly utilized to tackle various computer vision problems, including recognition, segmentation, and classification from RGB images. With the availability of a diverse range of sensors, industry-specific datasets are acquired to address specific challenges. These collected datasets have varied modalities, indicating t...
Binary sorting between ABS and PS polymers is a challenge for the recycling industry, particularly when black pigments are present. We propose the sequential application of a hyperspectral sensor in the shortwave infrared (HSI-SWIR) and a Raman sensor unit (532 nm excitation). HSI-SWIR created maps which allowed for initial spectral and spatial ass...
The increasing use of deep learning techniques has reduced interpretation time and, ideally, reduced interpreter bias by automatically deriving geological maps from digital outcrop models. However, accurate validation of these automated mapping approaches is a significant challenge due to the subjective nature of geological mapping and the difficul...
Uncrewed aerial vehicles (UAVs), also known as drones, are ubiquitous and their use cases extend today from governmental applications to civil applications such as the agricultural, medical, and transport sectors, etc. In accordance with the requirements in terms of demand, it is possible to carry out various missions involving several types of UAV...
The Storkwitz carbonatite breccia, located near Delitzsch, Germany, is one of the few European domestic rare earth elements (REE) deposits, but is relatively understudied owing to more than 100 m of Cenozoic sedimentary cover. We present the results of a petrological investigation of the recently acquired ∼700 m-deep SES 1/2012 borehole. The Storkw...
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...
The Black Angel Zn-Pb ore deposit is hosted in folded Paleoproterozoic marbles of the Mârmorilik Formation. It is exposed in the southern part of the steep and inaccessible alpine terrain of the Rinkian Orogen, in central West Greenland. Drill-core data integrated with 3D-photogeology and hyperspectral imagery of the rock face allow us to identify...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
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...
Late and postglacial reverse faults and seismically-induced landslides are characteristic features of deglaciated terrain in the northern Fennoscandia. The main focus of this study was to investigate the rupturing history of the reverse Vaalajärvi fault complex in Sodankylä, Finland, based on remote sensing, on-site geophysics and sedimentology in...
Electronic waste is the fastest growing type of scrap globally and is an important challenge due to its heterogeneity, intrinsic toxicity and potential environmental impact. With an objective of obtaining information on the composition of printed circuit boards (PCBs) through non-invasive analysis to aid in recycling and recovery of precious waste,...
Graphical abstract showing first results of the MULSEDRO Greenland field campaign 2019.
With the increasing demand for highly autonomous, efficient industrial fabrication , more sophisticated sensor-actor loops are required for process control. Automated, in-line process monitoring tools are already deployed in some high technology fields, such as semiconductor and car manufacturing. However, many industrial sectors, e.g. mining and r...
The traditional study of palaeoseismic trenches, involving logging, stratigraphic and structural interpretation, can be time consuming and affected by biases and inaccuracies. To overcome these limitations, a new workflow is presented that integrates infrared hyperspectral and photogrammetric data to support field‐based palaeoseismic observations....
We present an innovative multi-sensor system, based on non-invasive optical spectroscopy for the characterization of material streams. The novel hardware and software setups are explained in detail and first results from RGB stereoscopy and object detection are shown.
Traditional exploration techniques usually rely on extensive field work supported by geophysical ground surveying. However, this approach can be limited by several factors such as field accessibility, financial cost, area size, climate, and public disapproval. We recommend the use of multiscale hyperspectral remote sensing to mitigate the disadvant...
Hyperspectral imaging (HSI) is one of the key technologies in current non-invasive material analysis. Recent developments in sensor design and computer technology allow the acquisition and processing of high spectral and spatial resolution datasets. In contrast to active spectroscopic approaches such as X-ray fluorescence or laser-induced breakdown...
Traditional exploration techniques usually rely on extensive geological field work complemented by geophysical ground surveying. However, this approach can be limited by field accessibility, financial status, area size and climate and can be confronted with public rebuff. We recommend the use of multi-scale hyperspectral remote sensing to mitigate...
Rapid, efficient and reproducible drillcore logging is fundamental in mineral exploration. Drillcore mapping has evolved rapidly in the recent decade, especially with the advances in hyperspectral spectral imaging. A wide range of imaging sensors is now available, providing rapidly increasing spectral as well as spatial resolution and coverage. How...
Due to the rapidly increasing use of energy-efficient technologies, the need for complex materials containing rare earth elements (REEs) is steadily growing. The high demand for REEs requires the exploration of new mineral deposits of these valuable elements, as recovery by recycling is still very low. Easy-to-deploy sensor technologies featuring h...
The demand for critical raw materials, such as Rare Earth Elements (REEs), has risen over the past decade due to their increasing use in consumer electronics as well as in industry (e.g., solar panels and wind turbines). Of all the critical elements, REEs have the highest supply risk for Europe. However, both production and recycling have a high en...
New energy, transport, computer and telecommunication technologies require an increasing supply of rare earth elements (REEs). As a consequence, adequate and robust detection methods become essential for the exploration and discovery of new deposits, the improved characterization of existing deposits and the future recycling of today’s high-tech pr...
The demand for mineral and metalliferous resources needs to match the continued global rise in population and global economic growth. Rare Earth Elements (REEs), Niobium (Nb) and Tantalum (Ta) are such deposits in high demand. This global rise makes it difficult to meet the growing demand using only the currently available resources, such as recycl...
Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining mon...
Hyperspectral long-wave infrared imaging (LWIR HSI) adds a promising complement to visible, near infrared, and shortwave infrared (VNIR and SWIR) HSI data in the field of mineral mapping. It enables characterization of rock-forming minerals such as silicates and carbonates, which show no detectable or extremely weak features in VNIR and SWIR. In th...
Integration of drone-borne hyperspectral and geomagnetic data. The poster describes the idea of MULSEDRO (Multi sensor drones) and the first field test in Finland, 2017. The equipment is shown and first results are presented.