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A comprehensive workflow to analyze ensembles of globally inverted 2D electrical resistivity models
(2022)
Electrical resistivity tomography (ERT) aims at imaging the subsurface resistivity distribution and provides valuable information for different geological, engineering, and hydrological applications. To obtain a subsurface resistivity model from measured apparent resistivities, stochastic or deterministic inversion procedures may be employed. Typically, the inversion of ERT data results in non-unique solutions; i.e., an ensemble of different models explains the measured data equally well. In this study, we perform inference analysis of model ensembles generated using a well-established global inversion approach to assess uncertainties related to the nonuniqueness of the inverse problem. Our interpretation strategy starts by establishing model selection criteria based on different statistical descriptors calculated from the data residuals. Then, we perform cluster analysis considering the inverted resistivity models and the corresponding data residuals. Finally, we evaluate model uncertainties and residual distributions for each cluster. To illustrate the potential of our approach, we use a particle swarm optimization (PSO) algorithm to obtain an ensemble of 2D layer-based resistivity models from a synthetic data example and a field data set collected in Loon-Plage, France. Our strategy performs well for both synthetic and field data and allows us to extract different plausible model scenarios with their associated uncertainties and data residual distributions. Although we demonstrate our workflow using 2D ERT data and a PSObased inversion approach, the proposed strategy is general and can be adapted to analyze model ensembles generated from other kinds of geophysical data and using different global inversion approaches.
River-valley morphology preserves information on tectonic and climatic conditions that shape landscapes. Observations suggest that river discharge and valley-wall lithology are the main controls on valley width. Yet, current models based on these observations fail to explain the full range of cross-sectional valley shapes in nature, suggesting hitherto unquantified controls on valley width. In particular, current models cannot explain the existence of paired terrace sequences that form under cyclic climate forcing. Paired river terraces are staircases of abandoned floodplains on both valley sides, and hence preserve past valley widths. Their formation requires alternating phases of predominantly river incision and predominantly lateral planation, plus progressive valley narrowing. While cyclic Quaternary climate changes can explain shifts between incision and lateral erosion, the driving mechanism of valley narrowing is unknown. Here, we extract valley geometries from climatically formed, alluvial river-terrace sequences and show that across our dataset, the total cumulative terrace height (here: total valley height) explains 90%–99% of the variance in valley width at the terrace sites. This finding suggests that valley height, or a parameter that scales linearly with valley height, controls valley width in addition to river discharge and lithology. To explain this valley-width-height relationship, we reformulate existing valley-width models and suggest that, when adjusting to new boundary conditions, alluvial valleys evolve to a width at which sediment removal from valley walls matches lateral sediment supply from hillslope erosion. Such a hillslope-channel coupling is not captured in current valley-evolution models. Our model can explain the existence of paired terrace sequences under cyclic climate forcing and relates valley width to measurable field parameters. Therefore, it facilitates the reconstruction of past climatic and tectonic conditions from valley topography.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
During the last 5 Ma the Earth's ocean-atmosphere system passed through several major transitions, many of which are discussed as possible triggers for human evolution. A classic in this context is the possible influence of the closure of the Panama Strait, the intensification of Northern Hemisphere Glaciation, a stepwise increase in aridity in Africa, and the first appearance of the genus Homo about 2.5 - 2.7 Ma ago. Apart from the fact that the correlation between these events does not necessarily imply causality, many attempts to establish a relationship between climate and evolution fail due to the challenge of precisely localizing an a priori unknown number of changes potentially underlying complex climate records. The kernel-based Bayesian inference approach applied here allows inferring the location, generic shape, and temporal scale of multiple transitions in established records of Plio-Pleistocene African climate. By defining a transparent probabilistic analysis strategy, we are able to identify conjoint changes occurring across the investigated terrigenous dust records from Ocean Drilling Programme (ODP) sites in the Atlantic Ocean (ODP 659), Arabian (ODP 721/722) and Mediterranean Sea (ODP 967). The study indicates a two-step transition in the African climate proxy records at (2.35-2.10) Ma and (1.70 - 1.50) Ma, that may be associated with the reorganization of the Hadley-Walker Circulation. .
Diet analysis of bats killed at wind turbines suggests large-scale losses of trophic interactions
(2022)
Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy-producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly affect local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g., wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.
A volcanic eruption is usually preceded by seismic precursors, but their interpretation and use for forecasting the eruption onset time remain a challenge. A part of the eruptive processes in open conduits of volcanoes may be similar to those encountered in geysers. Since geysers erupt more often, they are useful sites for testing new forecasting methods. We tested the application of Permutation Entropy (PE) as a robust method to assess the complexity in seismic recordings of the Strokkur geyser, Iceland. Strokkur features several minute-long eruptive cycles, enabling us to verify in 63 recorded cycles whether PE behaves consistently from one eruption to the next one. We performed synthetic tests to understand the effect of different parameter settings in the PE calculation. Our application to Strokkur shows a distinct, repeating PE pattern consistent with previously identified phases in the eruptive cycle. We find a systematic increase in PE within the last 15 s before the eruption, indicating that an eruption will occur. We quantified the predictive power of PE, showing that PE performs better than seismic signal strength or quiescence when it comes to forecasting eruptions.
ArcticBeach v1.0
(2022)
In the Arctic, air temperatures are increasing and sea ice is declining, resulting in larger waves and a longer open water season, all of which intensify the thaw and erosion of ice-rich coasts. Climate change has been shown to increase the rate of Arctic coastal erosion, causing problems for Arctic cultural heritage, existing industrial, military, and civil infrastructure, as well as changes in nearshore biogeochemistry. Numerical models that reproduce historical and project future Arctic erosion rates are necessary to understand how further climate change will affect these problems, and no such model yet exists to simulate the physics of erosion on a pan-Arctic scale. We have coupled a bathystrophic storm surge model to a simplified physical erosion model of a permafrost coastline. This Arctic erosion model, called ArcticBeach v1.0, is a first step toward a physical parameterization of Arctic shoreline erosion for larger-scale models. It is forced by wind speed and direction, wave period and height, sea surface temperature, all of which are masked during times of sea ice cover near the coastline. Model tuning requires observed historical retreat rates (at least one value), as well as rough nearshore bathymetry. These parameters are already available on a pan-Arctic scale. The model is validated at three study sites at 1) Drew Point (DP), Alaska, 2) Mamontovy Khayata (MK), Siberia, and 3) Veslebogen Cliffs, Svalbard. Simulated cumulative retreat rates for DP and MK respectively (169 and 170 m) over the time periods studied at each site (2007-2016, and 1995-2018) are found to the same order of magnitude as observed cumulative retreat (172 and 120 m). The rocky Veslebogen cliffs have small observed cumulative retreat rates (0.05 m over 2014-2016), and our model was also able to reproduce this same order of magnitude of retreat (0.08 m). Given the large differences in geomorphology between the study sites, this study provides a proof-of-concept that ArcticBeach v1.0 can be applied on very different permafrost coastlines. ArcticBeach v1.0 provides a promising starting point to project retreat of Arctic shorelines, or to evaluate historical retreat in places that have had few observations.
The Arctic is greatly affected by climate change. Increasing air temperatures drive permafrost thaw and an increase in coastal erosion and river discharge. This results in a greater input of sediment and organic matter into nearshore waters, impacting ecosystems by reducing light transmission through the water column and altering biogeochemistry. This potentially results in impacts on the subsistence economy of local people as well as the climate due to the transformation of suspended organic matter into greenhouse gases. Even though the impacts of increased suspended sediment concentrations and turbidity in the Arctic nearshore zone are well-studied, the mechanisms underpinning this increase are largely unknown. Wave energy and tides drive the level of turbidity in the temperate and tropical parts of the world, and this is generally assumed to also be the case in the Arctic. However, the tidal range is considerably lower in the Arctic, and processes related to the occurrence of permafrost have the potential to greatly contribute to nearshore turbidity. In this study, we use high-resolution satellite imagery alongside in situ and ERA5 reanalysis data of ocean and climate variables in order to identify the drivers of nearshore turbidity, along with its seasonality in the nearshore waters of Herschel Island Qikiqtaruk, in the western Canadian Arctic. Nearshore turbidity correlates well to wind direction, wind speed, significant wave height, and wave period. Nearshore turbidity is superiorly correlated to wind speed at the Beaufort Shelf compared to in situ measurements at Herschel Island Qikiqtaruk, showing that nearshore turbidity, albeit being of limited spatial extent, is influenced by large-scale weather and ocean phenomenons. We show that, in contrast to the temperate and tropical ocean, freshly eroded material is the predominant driver of nearshore turbidity in the Arctic, rather than resuspension, which is caused by the vulnerability of permafrost coasts to thermo-erosion.
Increasing arctic coastal erosion rates imply a greater release of sediments and organic matter into the coastal zone. With 213 sediment samples taken around Herschel Island-Qikiqtaruk, Canadian Beaufort Sea, we aimed to gain new insights on sediment dynamics and geochemical properties of a shallow arctic nearshore zone. Spatial characteristics of nearshore sediment texture (moderately to poorly sorted silt) are dictated by hydrodynamic processes, but ice-related processes also play a role. We determined organic matter (OM) distribution and inferred the origin and quality of organic carbon by C/N ratios and stable carbon isotopes delta C-13. The carbon content was higher offshore and in sheltered areas (mean: 1.0 wt.%., S.D.: 0.9) and the C/N ratios also showed a similar spatial pattern (mean: 11.1, S.D.: 3.1), while the delta C-13 (mean: -26.4 parts per thousand VPDB, S.D.: 0.4) distribution was more complex. We compared the geochemical parameters of our study with terrestrial and marine samples from other studies using a bootstrap approach. Sediments of the current study contained 6.5 times and 1.8 times less total organic carbon than undisturbed and disturbed terrestrial sediments, respectively. Therefore, degradation of OM and separation of carbon pools take place on land and continue in the nearshore zone, where OM is leached, mineralized, or transported beyond the study area.
The origin of the First Bend of the Yangtze River is key to understanding the birth of the modern Yangtze River. Despite considerable efforts, the timing and mechanism of formation of the First Bend remain highly debated. Inverse river-profile modeling of three tributaries (Chongjiang, Lima, and Gudu) of the Jinsha River, integrated with regional tectonic and geomorphic interpretations, allows the onset of incision at the First Bend to be constrained to 28-20 Ma. The spatio-temporal coincidence of initial river incision and activity of Yulong Thrust Belt in southeastern Tibet highlights thrusting to be fundamental in reshaping the pre-existing stream network at the First Bend. These results enable us to reinterpret a change in sedimentary environment from a braided river to a swamp-like lake in the Jianchuan Basin south of the First Bend, recording the destruction of the hypothesized southwards-flowing paleo-Jinsha and Shuiluo Rivers at ~36-35 Ma by magmatism. During the late Oligoceneearly Miocene, the paleo-Shuiluo River was diverted to the north by focused rock uplift due to thrusting along the Yulong Thrust Belt, which also led to exhumation of the Jianchuan Basin. Diversion of the paleo-Shuiluo River can be explained by capture from a downstream river in the footwall of the Yulong Thrust Belt. Subsequent rapid headward erosion, that was caused by thrusting-induced drop of local base level, is recorded by upstream younging ages for the onset of incision and led to the formation of the First Bend. The combination of new ages for the onset of incision at 28-20 Ma at the First Bend and younger ages upstream indicates northwards expansion of the Jinsha River at a rate of 62 +/- 18 mm/yr. Our results suggest that the origin of the First Bend was likely triggered by thrusting at 28-20 Ma, after which the Yangtze River formed.
Here I present a comparison between two of the most widely used reduced-complexity models for the representation of sediment transport and deposition processes, namely the transport-limited (or TL) model and the under-capacity (or xi-q) model more recently developed by Davy and Lague (2009). Using both models, I investigate the behavior of a sedimentary continental system of length L fed by a fixed sedimentary flux from a catchment of size A(0) in a nearby active orogen through which sediments transit to a fixed base level representing a large river, a lake or an ocean. This comparison shows that the two models share the same steady-state solution, for which I derive a simple 1D analytical expression that reproduces the major features of such sedimentary systems: a steep fan that connects to a shallower alluvial plain. The resulting fan geometry obeys basic observational constraints on fan size and slope with respect to the upstream drainage area, A(0). The solution is strongly dependent on the size of the system, L, in comparison to a distance L-0, which is determined by the size of A(0), and gives rise to two fundamentally different types of sedimentary systems: a constrained system where L < L-0 and open systems where L > L-0. I derive simple expressions that show the dependence of the system response time on the system characteristics, such as its length, the size of the upstream catchment area, the amplitude of the incoming sedimentary flux and the respective rate parameters (diffusivity or erodibility) for each of the two models. I show that the xi-q model predicts longer response times. I demonstrate that although the manner in which signals propagates through the sedimentary system differs greatly between the two models, they both predict that perturbations that last longer than the response time of the system can be recorded in the stratigraphy of the sedimentary system and in particular of the fan. Interestingly, the xi-q model predicts that all perturbations in the incoming sedimentary flux will be transmitted through the system, whereas the TL model predicts that rapid perturbations cannot. I finally discuss why and under which conditions these differences are important and propose observational ways to determine which of the two models is most appropriate to represent natural systems.
The creation of building exposure models for seismic risk assessment is frequently challenging due to the lack of availability of detailed information on building structures. Different strategies have been developed in recent years to overcome this, including the use of census data, remote sensing imagery and volunteered graphic information (VGI). This paper presents the development of a building-by-building exposure model based exclusively on openly available datasets, including both VGI and census statistics, which are defined at different levels of spatial resolution and for different moments in time. The initial model stemming purely from building-level data is enriched with statistics aggregated at the neighbourhood and city level by means of a Monte Carlo simulation that enables the generation of full realisations of damage estimates when using the exposure model in the context of an earthquake scenario calculation. Though applicable to any other region of interest where analogous datasets are available, the workflow and approach followed are explained by focusing on the case of the German city of Cologne, for which a scenario earthquake is defined and the potential damage is calculated. The resulting exposure model and damage estimates are presented, and it is shown that the latter are broadly consistent with damage data from the 1978 Albstadt earthquake, notwithstanding the differences in the scenario. Through this real-world application we demonstrate the potential of VGI and open data to be used for exposure modelling for natural risk assessment, when combined with suitable knowledge on building fragility and accounting for the inherent uncertainties.
Neoarchean (similar to 2.73-2.70 Ga) accretionary history of the eastern Dharwar Craton, India
(2022)
Cratonic mid-crustal plutons may contain supracrustal enclaves that preserve evidence of an earlier growth history. The Eastern Dharwar craton records Neoarchean two-stage accretionary sequential growth (2.70 and 2.55 Ga) and a chronology of their enclaves could refine orogenic models. To test whether the metamorphic history of their enclaves was related to any of these stages, phase equilibria modelling and combined Lu-Hf and Sm-Nd geochronology on garnet were conducted on metapsammite, now preserved as garnet-orthopyroxene-cordierite gneiss. Phase equilibria modelling indicates peak metamorphic conditions, similar to 850 degrees C and similar to 8.5 kbar (M1a), were followed by near isothermal decompression to 5-6 kbar (M1b) and isobaric cooling to similar to 800 degrees C (M1c). The thermobaric gradient related to peak metamorphic conditions, similar to 30 degrees C kbar(-1), is typical of collisional orogens. Regression of the whole-rock and garnet, for sample S17b, yield Lu-Hf isochron ages of 2733 +/- 29 Ma, and for sample S18, 2724 +/- 13 Ma. A Lu-Hf weighted mean age for the porphyroblastic garnet suggests growth at 2725.5 +/- 11.9 Ma during the M1a-M1b stages. In contrast, the whole-rock sample S17b and the garnet fractions yield a Sm-Nd isochron age of 2696 +/- 10 Ma. From sample S18 the whole rock, garnet fractions, and orthopyroxene yield an isochron age of 2683 +/- 15 Ma. The garnet Sm-Nd weighted mean age at 2692.0 +/- 8.3 Ma constrains the M1b-M1c stages. We suggest that the protoliths to these supracrustal enclaves were deposited in an arc tectonic setting and underwent thickening followed by heating during peeled-back lithospheric convergence. Therefore, the earliest of the craton-forming accretionary stages is preserved as the similar to 2.73 Ga granulite-facies enclaves, marginally older than the 2.70-2.65 Ga cratonic greenstone volcanism. Tectonic exhumation of these mid-crustal granulite enclaves was in response to the late-Proterozoic (similar to 1.7 Ga) Bhopalpatnam orogeny.
Data recorded by distributed acoustic sensing (DAS) along an optical fibre sample the spatial and temporal properties of seismic wavefields at high spatial density. Often leading to massive amount of data when collected for seismic monitoring along many kilometre long cables. The spatially coherent signals from weak seismic arrivals within the data are often obscured by incoherent noise. We present a flexible and computationally efficient filtering technique, which makes use of the dense spatial and temporal sampling of the data and that can handle the large amount of data. The presented adaptive frequency-wavenumber filter suppresses the incoherent seismic noise while amplifying the coherent wavefield. We analyse the response of the filter in time and spectral domain, and we demonstrate its performance on a noisy data set that was recorded in a vertical borehole observatory showing active and passive seismic phase arrivals. Lastly, we present a performant open-source software implementation enabling real-time filtering of large DAS data sets.
The geometry of carbonate platforms reflects the interaction of several factors. However, the impact of carbonate-producing organisms has been poorly investigated so far. This study applies stratigraphic forward modelling (SFM) and sensitivity analysis to examine, referenced to the Miocene Llucmajor Platform, the effect of changes of dominant biotic production in the oligophotic and euphotic zones on platform geometry. Our results show that the complex interplay of carbonate production rates, bathymetry and variations in accommodation space control the platform geometry. The main driver of progradation is the oligophotic production of rhodalgal sediments during the lowstands. This study demonstrates that platform geometry and internal architecture varies significantly according to the interaction of the predominant carbonate-producing biotas. The input parameters for this study are based on well-understood Miocene carbonate biotas with characteristic euphotic, oligophotic and photo-independent carbonate production in which it is crucial that each carbonate-producing class is modelled explicitly within the simulation run and not averaged with a single carbonate production-depth profile. This is important in subsurface exploration studies based on stratigraphic forward models where the overall platform geometry may be approximated through calibration runs, and constrained by seismic surveys and wellbores. However, the internal architecture is likely to be oversimplified without an in-depth understanding of the target carbonate system and a transfer to forward modelling parameters.
The LArge-scale Reservoir Simulator (LARS) has been previously developed to study hydrate dissociation in hydrate-bearing systems under in-situ conditions. In the present study, a numerical framework of equations of state describing hydrate formation at equilibrium conditions has been elaborated and integrated with a numerical flow and transport simulator to investigate a multi-stage hydrate formation experiment undertaken in LARS. A verification of the implemented modeling framework has been carried out by benchmarking it against another established numerical code. Three-dimensional (3D) model calibration has been performed based on laboratory data available from temperature sensors, fluid sampling, and electrical resistivity tomography. The simulation results demonstrate that temperature profiles, spatial hydrate distribution, and bulk hydrate saturation are consistent with the observations. Furthermore, our numerical framework can be applied to calibrate geophysical measurements, optimize post-processing workflows for monitoring data, improve the design of hydrate formation experiments, and investigate the temporal evolution of sub-permafrost methane hydrate reservoirs.
The Mackenzie Delta (MD) is a permafrost-bearing region along the coasts of the Canadian Arctic which exhibits high sub-permafrost gas hydrate (GH) reserves. The GH occurring at the Mallik site in the MD is dominated by thermogenic methane (CH4), which migrated from deep conventional hydrocarbon reservoirs, very likely through the present fault systems. Therefore, it is assumed that fluid flow transports dissolved CH4 upward and out of the deeper overpressurized reservoirs via the existing polygonal fault system and then forms the GH accumulations in the Kugmallit-Mackenzie Bay Sequences. We investigate the feasibility of this mechanism with a thermo-hydraulic-chemical numerical model, representing a cross section of the Mallik site. We present the first simulations that consider permafrost formation and thawing, as well as the formation of GH accumulations sourced from the upward migrating CH4-rich formation fluid. The simulation results show that temperature distribution, as well as the thickness and base of the ice-bearing permafrost are consistent with corresponding field observations. The primary driver for the spatial GH distribution is the permeability of the host sediments. Thus, the hypothesis on GH formation by dissolved CH4 originating from deeper geological reservoirs is successfully validated. Furthermore, our results demonstrate that the permafrost has been substantially heated to 0.8-1.3 degrees C, triggered by the global temperature increase of about 0.44 degrees C and further enhanced by the Arctic Amplification effect at the Mallik site from the early 1970s to the mid-2000s.
The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen-evergreen transition zone in Central Yakutia and the tundra-taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, ). The dataset includes structure-from-motion (SfM) point clouds and red-green-blue (RGB) and red-green-near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, ). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch ( and ) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, ). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. Larix gmeliniiLarix cajanderiDataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, ). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. <br /> The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra-taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.
The new in situ geodynamic laboratory established in the framework of the ICDP Eger project aims to develop the most modern, comprehensive, multiparameter laboratory at depth for studying earthquake swarms, crustal fluid flow, mantle-derived CO2 and helium degassing, and processes of the deep biosphere. In order to reach a new level of high-frequency, near-source and multiparameter observation of earthquake swarms and related phenomena, such a laboratory comprises a set of shallow boreholes with high-frequency 3-D seismic arrays as well as modern continuous real-time fluid monitoring at depth and the study of the deep biosphere.
This laboratory is located in the western part of the Eger Rift at the border of the Czech Republic and Germany (in the West Bohemia–Vogtland geodynamic region) and comprises a set of five boreholes around the seismoactive zone. To date, all monitoring boreholes have been drilled. This includes the seismic monitoring boreholes S1, S2 and S3 in the crystalline units north and east of the major Nový Kostel seismogenic zone, borehole F3 in the Hartoušov mofette field and borehole S4 in the newly discovered Bažina maar near Libá. Supplementary borehole P1 is being prepared in the Neualbenreuth maar for paleoclimate and biological research. At each of these sites, a borehole broadband seismometer will be installed, and sites S1, S2 and S3 will also host a 3-D seismic array composed of a vertical geophone chain and surface seismic array. Seismic instrumenting has been completed in the S1 borehole and is in preparation in the remaining four monitoring boreholes. The continuous fluid monitoring site of Hartoušov includes three boreholes, F1, F2 and F3, and a pilot monitoring phase is underway. The laboratory also enables one to analyze microbial activity at CO2 mofettes and maar structures in the context of changes in habitats. The drillings into the maar volcanoes contribute to a better understanding of the Quaternary paleoclimate and volcanic activity.