S U M M A R YThe paper presents a three-dimensional (3-D) density model of the crust of southern and central Finland. The large SVEKALAPKO seismic array experiment was carried out in this area during 1998-1999. One of the intermediate objectives of the experiment was compilation of a 3-D P-wave velocity model (V p model) of the crust to provide crustal corrections for teleseismic P-wave traveltimes. The model was constructed from the results of previous controlled-source seismic (CSS) experiments in the area and was composed of two main crustal layers, an upper crust and a high-velocity lower crust with V p > 7.0 km s −1 . The thickness of the crust in the model varies from 64 to 38 km and includes three pronounced troughs. We used this model and the results of petrophysical studies of bedrock density in Finland as a priori information to construct a 3-D density model of the crust in the SVEKALAPKO area. The initial results of gravity modelling demonstrated, however, that the model lacks information about lateral velocity variations in the upper and middle crust. To improve the fit of the model to the observed Bouguer anomaly, the model was corrected by introducing two additional layers, called the lower crust and the middle crust, with 6.8 < Vp < 7.0 km s −1 and 6.4 < Vp < 6.8 km s −1 , respectively. The depth to the upper boundaries of these layers was retrieved from the results of previous seismic profiles in the area and the values of density and velocity in the upper crust were constrained using the information on bedrock densities in Finland, the Bouguer anomaly and new data about the velocity distribution within the upper crust obtained from local event studies of the SVEKALAPKO seismic experiment. The corrected model was used as a starting model for inversion of the observed Bouguer anomaly. The resulting 3-D density model agrees well with the observed Bouguer anomaly and explains the sources of largescale Bouguer anomalies in the region. The model demonstrates that there is no correlation between the observed Bouguer anomaly and Moho depth. Rather, the Moho depressions in the region mark the boundaries of crustal blocks with different types of density distribution and are associated with the presence of additional compensating masses within the crust. The high-velocity lower crust of density 3.1-3.25 × 10 3 kg m −3 does not completely compensate the Moho depressions and the compensation is mostly a result of the presence of additional dense material in the upper and middle crust. Thus, the Moho depressions in central and southern Finland are fully compensated, or even overcompensated. On the other hand, the Moho depression in the area of the Gulf of Bothnia is compensated only in its southern part, resulting in a regional-scale minimum of the Bouguer anomaly in the northern part of the depression. The varying degree of compensation may result from variation in the origin and age of the present-day Moho boundary in the region.

The technical evolution of unmanned aerial systems (UAS) for mineral exploration advances rapidly. Recent sensor developments and improved UAS performance open new fields for research and applications in geological and geophysical exploration among others. In this study, we introduce an integrated acquisition and processing strategy for droneborne multisensor surveys combining optical remote sensing and magnetic data. We deploy both fixedwing and multicopter UAS to characterize an outcrop of the Otanmäki FeTiV deposit in central Finland. The lithology consists mainly of gabbro intrusions hosting ore bodies of magnetiteilmenite. Large areas of the outcrop are covered by lichen and low vegetation. We use two droneborne multi and hyperspectral cameras operating in the visible to nearinfrared parts of the electromagnetic spectrum to identify dominant geological features and the extents of ore bodies via ironindicating proxy minerals. We apply band ratios and unsupervised and supervised image classifications on the spectral data, from which we can map surficial ironbearing zones. We use two setups with threeaxis fluxgate magnetometers deployed both by a fixedwing and a multicopter UAS to measure the magnetic field at various flight altitudes (15 m, 40 m, 65 m). The total magnetic intensity (TMI) computed from the individual components is used for further interpretation of ore distribution. We compare to traditional magnetic groundbased survey data to evaluate the UASbased results. The measured anomalies and spectral data are validated and assigned to the outcropping geology and ore mineralization by performing surface spectroscopy, portable Xray fluorescence (pXRF), magnetic susceptibility, and traditional geologic mapping. Locations of mineral zones and magnetic anomalies correlate with the established geologic map. The integrated survey strategy allowed a straightforward mapping of ore occurrences. We highlight the efficiency, spatial resolution, and reliability of UAS surveys. Acquisition time of magnetic UAS surveying surpassed ground surveying by a factor of 20 with a comparable resolution. The proposed workflow possibly facilitates surveying, particularly in areas with complicated terrain and of limited accessibility, but highlights the remaining challenges in UAS mapping.

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 personal safety. Multi-sensor UAS are a technology that change geoscientific research, but they are still not routinely used for geological mapping in exploration and mining due to lack of trust in their added value and missing expertise and guidance in the selection and combination of drones and sensors. To address these limitations and highlight the potential of using UAS in exploration settings, we present an UAS multi-sensor mapping approach based on the integration of drone-borne photography, multi- and hyperspectral imaging and magnetics. Data are processed with conventional methods as well as innovative machine learning algorithms and validated by geological field mapping, yielding a comprehensive and geologically interpretable product. As a case study, we chose the northern extension of the Siilinjärvi apatite mine in Finland, in a brownfield exploration setting with plenty of ground truth data available and a survey area that is partly covered by vegetation. We conducted rapid UAS surveys from which we created a multi-layered data set to investigate properties of the ore-bearing carbonatite-glimmerite body. Our resulting geologic map discriminates between the principal lithologic units and distinguishes ore-bearing from waste rocks. Structural orientations and lithological units are deduced based on high-resolution, hyperspectral image-enhanced point clouds. UAS-based magnetic data allow an insight into their subsurface geometry through modeling based on magnetic interpretation. We validate our results via ground survey including rock specimen sampling, geochemical and mineralogical analysis and spectroscopic point measurements. We are convinced that the presented non-invasive, data-driven mapping approach can complement traditional workflows in mineral exploration as a flexible tool. Mapping products based on UAS data increase efficiency and maximize safety of the resource extraction process, and reduce expenses and incidental wastes.

M. 2019: Developing multi-sensor drones for geological mapping and mineral exploration: setup and first results from the MULE-DRO project. Geological Survey of Denmark and Greenland Bulletin 43, e2019430302.