Drone-based Integration of Hyperspectral Imaging and Magnetics for Mineral Exploration

The advent of unoccupied aerial systems (UAS) as disruptive technology has a lasting impact on remote sensing, geophysics and most geosciences. Small, lightweight, and low-cost UAS enable researchers and surveyors to acquire earth observation data in higher spatial and spectral resolution as compared to airborne and satellite data. UAS-based applications range from rapid topographic mapping using photogrammetric techniques to hyperspectral and geophysical measurements of surface and subsurface geology. UAS surveys contribute to identifying metal deposits, monitoring of mine sites and can reveal arising environmental issues associated with mining. Further, affordable UAS technology will boost exploration data availability and expertise in the global south. This thesis investigates the application of UAS-based multi-sensor data for mineral exploration, in particular the integration of hyperspectral imagers, magnetometers and digital cameras (covering the visible red, green, blue light spectrum). UAS-based research is maturing, however the aforementioned methods are not unified effectively. RGB-based photogrammetry is used to investigate topography and surface texture. Image spectrometers measure mineral-specific surface signatures. Magnetometers detect geomagnetic field changes caused by magnetic minerals at surface and depth. The integration of such UAS sensor-based methods in this thesis augments exploration potential with non-invasive, high-resolution, safe, rapid and practical survey methods. UAS-based surveying acquired, processed and integrated data from three distinct test sites. The sites are located in Finland (Fe-Ti-V at Otanmäki; apatite at Siilinjärvi) and Greenland (Ni-Cu-PGE at Qullissat, Disko Island) and were chosen as geologically diverse areas in subarctic to arctic environments. Restricted accessibility, unfavourable atmospheric conditions, dark rocks, debris and vegetation cover and low solar illumination were common features. While the topography in Finland was moderately flat, a steep landscape challenged the Greenland field work. These restraints meant that acquisitions varied from site to site and how data was integrated and interpreted is dependent on the commodity of interest. Iron-based spectral absorption and magnetic mineral response were detected using hyperspectral and magnetic surveying in Otanmäki. Multi-sensor-based image feature detection and classification combined with magnetic forward modelling enabled seamless geologic mapping in Siilinjärvi. Detailed magnetic inversion and multispectral photogrammetry led to the construction of a comprehensive 3D model of magmatic exploration targets in Greenland. Ground truth at different intensity was employed to verify UAS-based data interpretations during all case studies. Laboratory analysis was applied when deemed necessary to acquire geologic-mineralogic validation (e.g., X-ray diffraction and optical microscopy for mineral identification to establish lithologic domains, magnetic susceptibility measurements for subsurface modelling), for example for trace amounts of magnetite in carbonatite (Siilinjärvi) and native iron occurrence in basalt (Qullissat). Technical achievements were the integration of a multicopter-based prototype fluxgate-magnetometer data from different survey altitudes with ground truth, and a feasibility study with a high-speed multispectral image system for fixed-wing UAS. The employed case studies transfer the experiences made towards general recommendations for UAS application-based multi-sensor integration. This thesis highlights the feasibility of UAS-based surveying at target scale (1–50 km2) and solidifies versatile survey approaches for multi-sensor integration.Ziel dieser Arbeit war es, das Potenzial einer Drohnen-basierten Mineralexploration mit Multisensor-Datenintegration unter Verwendung optisch-spektroskopischer und magnetischer Methoden zu untersuchen, um u. a. übertragbare Arbeitsabläufe zu erstellen. Die untersuchte Literatur legt nahe, dass Drohnen-basierte Bildspektroskopie und magnetische Sensoren ein ausgereiftes technologisches Niveau erreichen und erhebliches Potenzial für die Anwendungsentwicklung bieten, aber es noch keine ausreichende Synergie von hyperspektralen und magnetischen Methoden gibt. Diese Arbeit umfasste drei Fallstudien, bei denen die Drohnengestützte Vermessung von geologischen Zielen in subarktischen bis arktischen Regionen angewendet wurde. Eine Kombination von Drohnen-Technologie mit RGB, Multi- und Hyperspektralkameras und Magnetometern ist vorteilhaft und schuf die Grundlage für eine integrierte Modellierung in den Fallstudien. Die Untersuchungen wurden in einem Gelände mit flacher und zerklüfteter Topografie, verdeckten Zielen und unter oft schlechten Lichtverhältnissen durchgeführt. Unter diesen Bedingungen war es das Ziel, die Anwendbarkeit von Drohnen-basierten Multisensordaten in verschiedenen Explorationsumgebungen zu bewerten. Hochauflösende Oberflächenbilder und Untergrundinformationen aus der Magnetik wurden fusioniert und gemeinsam interpretiert, dabei war eine selektive Gesteinsprobennahme und Analyse ein wesentlicher Bestandteil dieser Arbeit und für die Validierung notwendig. Für eine Eisenerzlagerstätte wurde eine einfache Ressourcenschätzung durchgeführt, indem Magnetik, bildspektroskopisch-basierte Indizes und 2D-Strukturinterpretation integriert wurden. Fotogrammetrische 3D-Modellierung, magnetisches forward-modelling und hyperspektrale Klassifizierungen wurden für eine Karbonatit-Intrusion angewendet, um einen kompletten Explorationsabschnitt zu erfassen. Eine Vektorinversion von magnetischen Daten von Disko Island, Grönland, wurden genutzt, um großräumige 3D-Modelle von undifferenzierten Erdrutschblöcken zu erstellen, sowie diese zu identifizieren und zu vermessen. Die integrierte spektrale und magnetische Kartierung in komplexen Gebieten verbesserte die Erkennungsrate und räumliche Auflösung von Erkundungszielen und reduzierte Zeit, Aufwand und benötigtes Probenmaterial für eine komplexe Interpretation. Der Prototyp einer Multispektralkamera, gebaut für eine Starrflügler-Drohne für die schnelle Vermessung, wurde entwickelt, erfolgreich getestet und zum Teil ausgewertet. Die vorgelegte Arbeit zeigt die Vorteile und Potenziale von Multisensor-Drohnen als praktisches, leichtes, sicheres, schnelles und komfortabel einsetzbares geowissenschaftliches Werkzeug, um digitale Modelle für präzise Rohstofferkundung und geologische Kartierung zu erstellen

Risk factors for chemotherapy-induced neutropenia occurrence in breast cancer patients: data from the INC-EU Prospective Observational European Neutropenia Study

Background: Chemotherapy-induced neutropenia (CIN) places patients at risk of life-threatening infections. While reduction of chemotherapy dose or delay of the subsequent treatment cycle and, consequently, reduction of relative dose intensity (RDI) may limit myelotoxicity, these actions can also impact adversely on treatment outcome and should be avoided in adjuvant settings. Patients and methods: Based on data from 444 breast cancer patients in the INC-EU Prospective Observational European Neutropenia Study, we have evaluated patient-specific and treatment-specific factors that impact on the incidence of grade 4 CIN (absolute neutrophil count <0.5 × 109/L), either during the first or in any cycle of (neo)adjuvant chemotherapy, across a range of regimens and doses. Results: Using multivariate logistic regression analysis, risk factors for grade 4 CIN were identified as older age, lower weight, higher planned dose intensity of doxorubicin, epirubicin, or docetaxel, higher number of planned cycles, vascular comorbidity, lower baseline white blood cell count, and higher baseline bilirubin. Use of colony-stimulating factor before a neutropenic event occurred, dose delays, and dose reductions were protective against grade 4 CIN. Conclusions: By identifying risk factors for grade 4 CIN, CSF prophylaxis may be appropriately targeted to prevent low RDI in patients treated with curative inten

Neutropenic event risk and impaired chemotherapy delivery in six European audits of breast cancer treatment

Goals of work: The aims of this study were to assess chemotherapy treatment characteristics, neutropenic event (NE) occurrence and related risk factors in breast cancer patients in Western Europe. Materials and methods: Six retrospective audits of breast cancer chemotherapy were combined into a dataset of 2,860 individuals. NEs were defined as neutropenia-related hospitalisation, dose reduction ≥15% or dose delay ≥7days. Summation dose intensity (SDI) was calculated to compare different types of chemotherapy regimens on a single scale. Risk factors of NE occurrence and of low relative dose intensity (RDI) ≤85% were identified by multiple logistic regression. Main results: Patient populations were comparable between audits. Until 1998, cyclophosphamide, methotrexate and fluorouracil regimens were most frequently used, but thereafter, anthracycline-based regimens were most common. NEs occurred in 20% of the patients and low RDI in 16%. NE occurrence predicted low RDI and was associated with higher age, bigger body surface area, lower body mass index, regimen type, more chemotherapy cycles planned, normal to high SDI, concomitant radiotherapy and year of treatment. First cycle NE occurrence predicted NEs from cycle 2 onwards. A risk score using age, SDI, number of planned chemotherapy cycles and concomitant radiotherapy differentiated patients with increasing NE risk (9-37%). An alternative score version not using concomitant radiotherapy performed moderately less well. Conclusions: NEs occurred frequently in this combined dataset and they affected treatment delivery. Identifying patients at high NE risk enables targeted prophylaxis and may avoid dose limitation

Component Decomposition-Based Hyperspectral Resolution Enhancement for Mineral Mapping

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 this paper, we investigate the potential of the resolution enhancement of hyperspectral images (HSIs) with the guidance of RGB images for mineral mapping. In more detail, a novel resolution enhancement method is proposed based on component decomposition. Inspired by the principle of the intrinsic image decomposition (IID) model, the HSI is viewed as the combination of a reflectance component and an illumination component. Based on this idea, the proposed method is comprised of several steps. First, the RGB image is transformed into the luminance component, blue-difference and red-difference chroma components (YCbCr), and the luminance channel is considered as the illumination component of the HSI with an ideal high spatial resolution. Then, the reflectance component of the ideal HSI is estimated with the downsampled HSI image and the downsampled luminance channel. Finally, the HSI with high resolution can be reconstructed by utilizing the obtained illumination and the reflectance components. Experimental results verify that the fused results can successfully achieve mineral mapping, producing better results qualitatively and quantitatively over single sensor data

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials

Background Neoadjuvant chemotherapy (NACT) for early breast cancer can make breast-conserving surgery more feasible and might be more likely to eradicate micrometastatic disease than might the same chemotherapy given after surgery. We investigated the long-term benefits and risks of NACT and the influence of tumour characteristics on outcome with a collaborative meta-analysis of individual patient data from relevant randomised trials. Methods We obtained information about prerandomisation tumour characteristics, clinical tumour response, surgery, recurrence, and mortality for 4756 women in ten randomised trials in early breast cancer that began before 2005 and compared NACT with the same chemotherapy given postoperatively. Primary outcomes were tumour response, extent of local therapy, local and distant recurrence, breast cancer death, and overall mortality. Analyses by intention-to-treat used standard regression (for response and frequency of breast-conserving therapy) and log-rank methods (for recurrence and mortality). Findings Patients entered the trials from 1983 to 2002 and median follow-up was 9 years (IQR 5–14), with the last follow-up in 2013. Most chemotherapy was anthracycline based (3838 [81%] of 4756 women). More than two thirds (1349 [69%] of 1947) of women allocated NACT had a complete or partial clinical response. Patients allocated NACT had an increased frequency of breast-conserving therapy (1504 [65%] of 2320 treated with NACT vs 1135 [49%] of 2318 treated with adjuvant chemotherapy). NACT was associated with more frequent local recurrence than was adjuvant chemotherapy: the 15 year local recurrence was 21·4% for NACT versus 15·9% for adjuvant chemotherapy (5·5% increase [95% CI 2·4–8·6]; rate ratio 1·37 [95% CI 1·17–1·61]; p=0·0001). No significant difference between NACT and adjuvant chemotherapy was noted for distant recurrence (15 year risk 38·2% for NACT vs 38·0% for adjuvant chemotherapy; rate ratio 1·02 [95% CI 0·92–1·14]; p=0·66), breast cancer mortality (34·4% vs 33·7%; 1·06 [0·95–1·18]; p=0·31), or death from any cause (40·9% vs 41·2%; 1·04 [0·94–1·15]; p=0·45). Interpretation Tumours downsized by NACT might have higher local recurrence after breast-conserving therapy than might tumours of the same dimensions in women who have not received NACT. Strategies to mitigate the increased local recurrence after breast-conserving therapy in tumours downsized by NACT should be considered—eg, careful tumour localisation, detailed pathological assessment, and appropriate radiotherapy

UAV-based multispectral image data of a tree nursery, Eberswalde, Brandenburg, 2023 (Orthomosaics, DEMs, point clouds)

&lt;p&gt;This data set contains three multispectral surveys conducted with an unoccupied aerial vehicle (UAV DJI M300 RTK) of an oak tree nursery experiment&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Date of&nbsp;acquisition: 16.08.2023&lt;/li&gt; &lt;li&gt;Location: Tree nursery, Eberswalde, Brandenburg, Germany&lt;/li&gt; &lt;li&gt;UAV: DJI M300 RTK with active SAPOS connection&lt;/li&gt; &lt;li&gt;Flight altitude above ground level: 30 m, 40 m, 60 m&lt;/li&gt; &lt;li&gt;Image Overlap forward/side: 80 % / 80 %&lt;/li&gt; &lt;li&gt;Camera: MicaSense Altum multispectral&lt;/li&gt; &lt;li&gt;EPSG: 32632&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;Data products:&nbsp;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Orthomosaic multispectral (Resolution: 1.35 cm, 1.79 cm, 2.65 cm)&lt;/li&gt; &lt;li&gt;Orthomosaic RGB&lt;/li&gt; &lt;li&gt;Orthomosaic thermal LWIR in pseudo&nbsp;&deg;C according to &lt;a href="https://support.micasense.com/hc/en-us/articles/360022446473-Converting-Altum-Thermal-to-degrees-C-after-processing-in-Agisoft-or-Pix4D"&gt;Micasense&lt;/a&gt;&nbsp;empirical formula&lt;/li&gt; &lt;li&gt;DEM&lt;/li&gt; &lt;li&gt;Dense point cloud RGB&lt;/li&gt; &lt;li&gt;Spectral indices calculated: NDVI, NDRE&lt;/li&gt; &lt;li&gt;Agisoft Report&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Acknowledgment:&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Frank Becker&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Landesbetrieb Forst Brandenburg&lt;/p&gt; &lt;p&gt;Landeskompetenzzentrum Forst Eberswalde (LFE)&lt;/p&gt

Drone-Borne Hyperspectral Monitoring of Acid Mine Drainage: An Example from the Sokolov Lignite District

This contribution explores the potential of unmanned aerial systems (UAS) to monitor areas affected by acid mine drainage (AMD). AMD is an environmental phenomenon that usually develops in the vicinity of mining operations or in post-mining landscapes. The investigated area covers a re-cultivated tailing in the Sokolov lignite district of the Czech Republic. A high abundance of AMD minerals occurs in a confined space of the selected test site and illustrates potential environmental issues. The mine waste material contains pyrite and its consecutive weathering products, mainly iron hydroxides and oxides. These affect the natural pH values of the Earth’s surface. Prior research done in this area relies on satellite and airborne data, and our approach focuses on lightweight drone systems that enables rapid deployment for field campaigns and consequently-repeated surveys. High spatial image resolutions and precise target determination are additional advantages. Four field and flight campaigns were conducted from April to September 2016. For validation, the waste heap was probed in situ for pH, X-ray fluorescence (XRF), and reflectance spectrometry. Ground truth was achieved by collecting samples that were characterized for pH, X-ray diffraction, and XRF in laboratory conditions. Hyperspectral data were processed and corrected for atmospheric, topographic, and illumination effects using accurate digital elevation models (DEMs). High-resolution point clouds and DEMs were built from drone-borne RGB data using structure-from-motion multi-view-stereo photogrammetry. The supervised classification of hyperspectral image (HSI) data suggests the presence of jarosite and goethite minerals associated with the acidic environmental conditions (pH range 2.3–2.8 in situ). We identified specific iron absorption bands in the UAS-HSI data. These features were confirmed by ground-truth spectroscopy. The distribution of in situ pH data validates the UAS-based mineral classification results. Evaluation of the applied methods demonstrates that drone surveying is a fast, non-invasive, inexpensive technique for multi-temporal environmental monitoring of post-mining landscapes

UAS-Based Hyperspectral Environmental Monitoring of Acid Mine Drainage Affected Waters

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, and non-invasive method for the monitoring aspect. Specifically, we propose a machine learning framework to integrate visible to near-infrared (VNIR) hyperspectral data with physicochemical field data from water and sediments, together with laboratory analyses to precisely map the extent of acid mine drainage in the Tintillo River (Spain). This river collects the drainage from the western part of the Rio Tinto massive sulfide deposit and discharges large quantities of acidic water with significant amounts of dissolved metals (Fe, Al, Cu, Zn, amongst others) into the Odiel River. At the confluence of these rivers, different geochemical and mineralogical processes occur due to the interaction of very acidic water (pH 2.5–3.0) with neutral water (pH 7.0–8.0). This complexity makes the area an ideal test site for the application of hyperspectral mapping to characterize both rivers and better evaluate contaminated water bodies with remote sensing imagery. Our approach makes use of a supervised random forest (RF) regression for the extended mapping of water properties, using the samples collected in the field as ground-truth and training data. The resulting maps successfully estimate the concentration of dissolved metals and related physicochemical properties in water, and trace associated iron species (e.g., jarosite, goethite) within sediments. These results highlight the capabilities of UAS-based hyperspectral data to monitor water bodies in mining environments, by mapping their hydrogeochemical properties, using few field samples. Hence, we have demonstrated that our workflow allows the rapid discrimination and mapping of AMD contamination in water, providing an essential basis for monitoring and subsequent remediation