In the past few decades, Mars-oriented orbiters and landers have allowed to unravel valuable knowledge about Mars’ surface and interior. With the InSight mission, seismic waves have indicated the presence of more frequent Marsquakes than assumed before the mission (Banerdt et al. 2020). Moreover, active mantle plume is considered below the Elysium Region (Broquet and Andrews-Hanna, 2023). This raises questions regarding the planet's formation and whether Mars is more geologically active than was considered.@en

NASA’s InSight mission has brought new information about the Martian lithosphere (Banerdt et al. 2020), which warrants a re-analysis of the support of the crustal and sub-crustal masses. Furthermore, the discovery of a possible mantle plume underneath the region south of Elysium Mons (Broquet et al. 2023), gives evidence for recent magmatic activity underneath the crust of Mars causing dynamic support to volcanic structures.@en

With the increasing interest in the Solar System's smaller bodies, quite a few missions have been sent to comets and asteroids, and more will be send in the near future. Due to the large distances involved, communication to command mission parameters takes a long time, which has a negative impact on operational safety. Autonomous navigation would be one of the key technologies that can make the mission more robust, safe, and cost effective. This is especially true if one considers the unknown fight environment when the spacecraft is first encountering the body. Most asteroids and comets have a very irregular shape and unknown mass distribution. Therefore, knowledge about its irregular gravity field will be directly beneficial as input to orbital corrections and manoeuvre planning. This paper addresses the estimation process of gravity-field parameters that could potentially be implemented in an autonomous navigation system. The focus is on a spherical-harmonic modelling of asteroid Eros-433, most notably outside the Brillouin sphere where the validity of the model is guaranteed. By using Kalman filtering it is shown that all degree and order coefficients up to degree 8 can be estimated with an error below 10%. This is the first step towards an autonomous navigation system that can operate in a highly-perturbed environment close to the asteroid.

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Significant land uplift and horizontal motions have been recorded with Global Navigation Satellite Systems (GNSS) in areas such as Alaska, Iceland and the Northern Antarctic Peninsula (NAP) as a result of Glacial Isostatic Adjustment (GIA) due to ice melt after the Little Ice Age. Here, analysis of horizontal displacement rates can be of extra importance, as they are more sensitive to Earth properties in shallower layers than vertical displacement rates. Proper modelling of horizontal displacement rates with dedicated GIA models requires a spherical Earth with compressible rheology. However, in these small areas, the used GIA models are often incompressible using a Cartesian geometry to ease computation and in some cases allow for lateral viscosity changes or more complex rheology. We investigate the validity of modelled horizontal displacement rates using different approximations, that is using spherical or Cartesian Earth structures, and incompressible, material compressible or compressible rheology. Although the lack of self-gravity and sphericity compensate each other in the vertical, this is less the case for the horizontal. For a disc ice sheet with a radius just over 200 km and a thickness of 1000 m, differences due to sphericity are minimal and the modelled horizontal displacement rates of compressible Cartesian models differ from those simulated by a compressible spherical model by 0.63 mm a-1. Thus, compressible Cartesian GIA models can be applied for modelling horizontal displacement rates of small ice sheets like those in Alaska, Iceland and NAP. Unfortunately, the implementation of compressibility in Abaqus that we use here cannot be extended to spherical models as gravity can not be specified for a spherical body. Other modelling approaches are recommended in such cases.

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The aim of this paper is to present the concept of a dedicated gravity field mission for the planet Mars, the Mars Quantum Gravity Mission (MaQuIs). The mission is targeted at improving the data on the gravitational field of Mars, enabling studies on planetary dynamics, seasonal changes, and subsurface water reservoirs. MaQuIs follows well known mission scenarios, currently deployed for Earth, and includes state-of-the-art quantum technologies to enhance the gained scientific signal.

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Several alternative gravity forward modelling methodologies and associated numerical codes with their own advantages and limitations are available for the solid Earth community. With upcoming state-of-the-art lithosphere density models and accurate global gravity field data sets, it is vital to understand the opportunities and limitations of the various approaches. In this paper, we discuss the four widely used techniques: global spherical harmonics (GSH), tesseroid integration (TESS), triangle integration (TRI), and hexahedral integration (HEX). A constant density shell benchmark shows that all four codes can produce similar precise gravitational potential fields. Two additional shell tests were conducted with more complicated density structures: laterally varying density structures and a crust-mantle interface density. The differences between the four codes were all below 1.5% of the modelled gravity signal suitable for reproducing satellite-acquired gravity data. TESS and GSH produced the most similar potential fields (<0.3 %). To examine the usability of the forward modelling codes for realistic geological structures, we use the global lithosphere model WINTERC-G that was constrained, among other data, by satellite gravity field data computed using a spectral forward modelling approach. This spectral code was benchmarked against the GSH, and it was confirmed that both approaches produce a similar gravity solution with negligible differences between them. In the comparison of the different WINTERC-G-based gravity solutions, again GSH and TESS performed best. Only short-wavelength noise is present between the spectral and tesseroid forward modelling approaches, likely related to the different way in which the spherical harmonic analysis of the varying boundaries of the mass layer is performed. The spherical harmonic basis functions produce small differences compared to the tesseroid elements, especially at sharp interfaces, which introduces mostly short-wavelength differences. Nevertheless, both approaches (GSH and TESS) result in accurate solutions of the potential field with reasonable computational resources. Differences below 0.5% are obtained, resulting in residuals of 0.076 mGal standard deviation at 250 km height. The biggest issue for TRI is the characteristic pattern in the residuals that is related to the grid layout. Increasing the resolution and filtering allow for the removal of most of this erroneous pattern, but at the expense of higher computational loads with respect to the other codes. The other spatial forward modelling scheme, HEX, has more difficulty in reproducing similar gravity field solutions compared to GSH and TESS. These particular approaches need to go to higher resolutions, resulting in enormous computation efforts. The hexahedron-based code performs less than optimal in the forward modelling of the gravity signature, especially with a laterally varying density interface. Care must be taken with any forward modelling software as the approximation of the geometry of the WINTERC-G model may deteriorate the gravity field solution.

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Current seismic tomography models show a complex environment underneath the crust, corroborated by high-precision satellite gravity observations. Both data sets are used to independently explore the density structure of the upper mantle. However, combining these two data sets proves to be challenging. The gravity-data has an inherent insensitivity in the radial direction and seismic tomography has a heterogeneous data acquisition, resulting in smoothed tomography models with de-correlation between different models for the mid-to-small wavelength features. Therefore, this study aims to assess and quantify the effect of regularization on a seismic tomography model by exploiting the high lateral sensitivity of gravity data. Seismic tomography models, SL2013sv, SAVANI, SMEAN2 and S40RTS are compared to a gravity-based density model of the upper mantle. In order to obtain similar density solutions compared to the seismic-derived models, the gravity-based model needs to be smoothed with a Gaussian filter. Different smoothening characteristics are observed for the variety of seismic tomography models, relating to the regularization approach in the inversions. Various S40RTS models with similar seismic data but different regularization settings show that the smoothening effect is stronger with increasing regularization. The type of regularization has a dominant effect on the final tomography solution. To reduce the effect of regularization on the tomographymodels, an enhancement procedure is proposed. This enhancement should be performed within the spectral domain of the actual resolution of the seismic tomography model. The enhanced seismic tomography models show improved spatial correlationwith each other and with the gravity-based model. The variation of the density anomalies have similar peak-to-peak magnitudes and clear correlation to geological structures. The resolvement of the spectral misalignment between tomographic models and gravity-based solutions is the first step in the improvement of multidata inversion studies of the upper mantle and benefit from the advantages in both data sets.

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Despite the ongoing advancements in low-thrust propulsion technology and the rise of all-electric satellite platforms, low-thrust spacecraft trajectory optimization remains a complex field of research. Shape-based approximations are predominant in interplanetary applications, but they are generally unsuitable for many-revolution trajectories, common in terrestrial applications. Indirect optimization methods allow for global optimization of many-revolution trajectories, but their mathematical complexity generally requires significant simplifications of the dynamical model, and they must be re-derived for any modification to the system dynamics or constraints. Conversely, direct optimization methods exhibit larger convergence radii and are flexible for application in different problems yet suffer from impractical computational times due to large design vectors. This paper presents a methodology for the optimization of low-thrust many-revolution trajectories, employing a hybrid combination of indirect and direct optimization methods. Similar hybrid approaches have been shown to be highly reliable for minimum-time trajectories. This methodology preserves similar performance while additionally enabling minimum-propellant optimization, through a mechanism that allows for coasting (non-thrusting) arcs, as well as targeting of the final geodetic-longitude. To reduce the propagation load of the methodology, we combine an orbital averaging scheme with a differential evolution algorithm, leading to a global optimization process with a practical computational effort. The analytical nature of the methodology reduces the number of optimization variables and its computational counterpart provides unmatchable flexibility for a configurable force and perturbation model as well as operational constraints fulfilment. The approach is applied to an unperturbed and a J₂-perturbed GTO-GEO transfer, revealing a 0.03% and a 0.4% error, for time- and propellant-minimization respectively, relative to the reference optimal trajectories. This proves that the method can match the performance of former hybrid approaches while additionally allowing for engine on/off switching. Moreover, the inclusion of the J₂ perturbation shows that, in contrast to indirect methods, it can accommodate modifications to the system dynamics without the need to re-derive the optimal control laws. Furthermore, a superior convergence radius of the optimization problem is demonstrated for the hybrid method, with respect to a reference indirect method, through the simultaneous optimization for minimum-propellant expenditure and final geodetic-longitude targeting. This research constitutes a significant advancement for space mission design and satellite operations, because it simultaneously harnesses the advantages of indirect and direct methods with broader flexibility than the popular indirect approaches and enhanced functionality than the former hybrid methods published in literature.

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The Barents Sea is situated on a continental margin and was home to a large ice sheet at the Last Glacial Maximum. Studying the solid Earth response to the removal of this ice sheet (glacial isostatic adjustment; GIA) can give insight into the subsurface rheology of this region. However, because the region is currently covered by ocean, uplift measurements from the center of the former ice sheet are not available. The Gravity Recovery and Climate Experiment (GRACE) gravity data have been shown to be able to constrain GIA. Here we analyze GRACE data for the period 2003-2015 in the Barents Sea and use the data to constrain GIA models for the region. We study the effect of uncertainty in non-tidal ocean mass models that are used to correct GRACE data and find that it should be taken into account when studying solid Earth signals in oceanic areas from GRACE. We compare GRACE-derived gravity disturbance rates with GIA model predictions for different ice deglaciation chronologies of the last glacial cycle and find that best-fitting models have an upper mantle viscosity equal or higher than <span classCombining double low line"inline-formula">3×1020</span>&thinsp;<span classCombining double low line"inline-formula">Pa s</span>. Following a similar procedure for Fennoscandia we find that the preferred upper mantle viscosity there is a factor 2 larger than in the Barents Sea for a range of lithospheric thickness values. This factor is shown to be consistent with the ratio of viscosities derived for both regions from global seismic models. The viscosity difference can serve as constraint for geodynamic models of the area.

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The long‐wavelength negative gravity anomaly over Hudson Bay coincides with the area depressed by the Laurentide Ice Sheet during the Last Glacial Maximum, suggesting that it is, at least partly, caused by glacial isostatic adjustment (GIA). Additional contributions to the static gravity field stem from surface dynamic topography, core‐mantle boundary (CMB) topography, and density anomalies in the subsurface. Previous estimates of the contribution of GIA to the gravity anomaly range from 25% to more than 80%. However, these estimates did not include uncertainties in all components that contribute to the gravity field. In this study, we develop a forward model for the gravity anomaly based on density models and dynamic models, investigating uncertainty in all components. We derive lithospheric densities from equilibrium constraints but extend the concept of lithospheric isostasy to a force balance that includes the dynamic models. The largest uncertainty in the predicted gravity anomaly is due to the lower mantle viscosity, uncertainties in the ice history, the crustal model, the lithosphere‐asthenosphere boundary, and the conversion from seismic velocities to density have a smaller effect. A preference for lower mantle viscosities >1022 Pa s is found, in which case at least 60% of the observed long‐wavelength gravity anomaly can be attributed to GIA. This lower bound on the lower mantle viscosity has implications for inferences based on models for mantle convection and GIA.@en

Next-generation planetary tracking methods, such as interplanetary laser ranging (ILR) and same-beam interferometry (SBI) promise an orders-of-magnitude increase in the accuracy of measurements of solar system dynamics. This requires a reconsideration of modelling strategies for the translational and rotational dynamics of natural bodies, to ensure that model errors are well below the measurement uncertainties. The influence of the gravitational interaction of the full mass distributions of celestial bodies, the so-called figure-figure effects, will need to be included for selected future missions. The mathematical formulation of this problem to arbitrary degree is often provided in an elegant and compact manner that is not trivially relatable to the formulation used in space geodesy and ephemeris generation. This complicates the robust implementation of such a model in operational software packages. We formulate the problem in a manner that is directly compatible with the implementation used in typical dynamical modelling codes: in terms of spherical harmonic coefficients and Legendre polynomials. An analytical formulation for the associated variational equations for both translational and rotational motion is derived. We apply our methodology to both Phobos and the KW4 binary asteroid system, to analyze the influence of figure-figure effects during estimation from next-generation tracking data. For the case of Phobos, omitting these effects during estimation results in relative errors of 0.42% and 0.065% for the C¯ ₂₀ and C¯ ₂₂ spherical harmonic gravity field coefficients, respectively. These values are below current uncertainties, but orders of magnitude larger than those obtained from past simulations for accurate tracking of a future Phobos lander, showing the need to apply the methodology outlined in this manuscript for selected future missions.

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In the last decade, the gravity field of the Earth has been observed with increased coverage due to dedicated satellite missions, which resulted in higher resolution and more accurate global gravity field models than were previously available. These models make it possible to study large scale processes such as solid Earth deformation after large loading events such as retreat of ice sheets or to study lateral density variation in the lithospheric part of the upper mantle. However, to use the gravity data successfully, unwanted signal needs to be removed in order to extract the information of interest. For example, with lithosphere studies the gravity signal coming from the crust and the deep mantle needs to be removed. This is commonly done by filtering out long-wavelength signals from the solution to remove deep mantle effects, and by removing the crustal signal by forward modelling seismic-derived crustal models. With improved models of crustal structure and more accurate gravity data, new information about the upper mantle and lithosphere can be obtained. Adopting the increased resolution and accuracy of the global gravity field models, I have developed new approaches that focus on spectral analysis of the gravity field, which result in new insights of the upper mantle. The forward gravity field modelling method that I improve upon in this dissertation is mostly used for topographic/isostatic mass reduction of gravity data. The methodology is able to transform density-models into gravitational potential fields using a spherical harmonic representation. I show that this methodology in the existing form is not suited to be used for density layers in lower crustal and upper mantle regions. The binomial series inherent to this methodology do not converge when applied to deep mass structures, and therefore it is not possible to truncate the series at a low degree to approximate the mass. This approximation is crucial for the computational efficiency of the methodology. I propose a correction that mitigates this erroneous behaviour, which enables this methodology to efficiently compute the potential field of deep situated masses. I benchmark the improved methodology with a tesseroid-based gravity-field modelling software, and I show that my software is accurate within ±4 mGal, when modelling the Moho density interface (with a range in signal of ±500 mGal. The improved methodology is used in the studies described in this thesis. With an efficient and accurate forward modelling methodology, I am able to use global gravity field data in studies of the solid Earth. In the central part of Fennoscandia the crust is currently uplifting, because of the delayed response of the viscous mantle to melting of the regional Late Pleistocene ice sheet. This process, called glacial isostatic adjustment (GIA), causes a negative anomaly in the present-day static gravity field as isostatic equilibrium has not been reached yet. Several studies have used this anomaly as a constraint on models of GIA, but the uncertainty in crustal and upper mantle structures had not been properly taken into account. In revisiting this problem, I show that the GIA gravity signal overlaps with mantle convection signals, such that a simple spherical harmonic truncation is not sufficient to separate these two phenomena. Furthermore, I find that, in contrast to the other studies, the effect of crustal anomalies on the gravity field cannot be effectively removed, because of the relative large uncertainties in the crustal density models. Therefore, I propose to correct the observed gravity field for GIA with numerical modelling results when constructing geophysical models that assume isostatic equilibrium. I show that correcting for GIA results in a significant vertical readjustment of the geometry of structural layers in the modelled crust of 5-10 percent. Correcting the gravity field for GIA prior to assuming isostatic equilibrium might be relevant in other areas with ongoing post-glacial rebound such as North America and the polar regions. Uncertainty in lithospheric density models is still the limiting factors in solid Earth studies and needs to be improved. Lithospheric density anomalies can, among other methods, be estimated from seismic tomography, gravity studies, or joint studies using both datasets. I compare different gravity-based density models of the lithosphere to a tomographic-derived solution and characterise the sources that introduce large uncertainties in the density models of the lithosphere. To study the uncertainty between global and regional crustal models, I select a region where the crust is explored in great measure with seismic profiles, namely the British Isles and surrounding areas, where I use three crustal models to quantify the crustal uncertainty: CRUST1.0, EUCrust-07, and a high-resolution regional P-wave velocity model of the region. The crustal models contribute to the uncertainty of the density of the lithosphere with ±110 kg/m3. Furthermore, I study various P-wave velocity-to-density conversions to quantify the uncertainty introduced by these conversion methods (±10 kg/m3. All different crustal density models are forward modelled into gravity anomalies using the improved methodology of Chapter 2 and these gravity anomalies are subsequently removed from the gravity observations. The unmodelled long-wavelength signal in the gravity field representing mass anomalies in the deep mantle are removed from the observation by spherical harmonic truncation, introducing an uncertainty of ±5 kg/m3. Also, the choice of density background model (±20 kg/m3) and lithosphere-asthenosphere boundary uncertainty (±30 kg/m3) have a small but significant effect on the estimated lithosphere densities. However, the inhomogeneous spatial distribution of profiles of controlled-source seismic exploration of the crustal thickness and density distribution proves to be the largest source of uncertainty (±110 kg/m3). The gravity-based lithospheric density solutions with a variation of ±100 kg/m3 are completely different in magnitude and spatial signature to the densities (±35 kg/m3) derived from a shear wave velocity model. This demonstrates that the tomographic model has a limited resolution, which can be related to regularisation that is used in the construction of global tomographic models. To account for this spectral imbalance, I spatially filter the gravity-based density models, resulting in similarities in spatial correlation and magnitude between that of the gravity-based and the tomographic-derived density. With the filtered gravity-based density I am able to estimate lateral varying conversion values between shear wave velocity and density for the lithosphere, which shows a correlation with major tectonic regions. This correlation shows that the independent gravity-based solutions, despite being filtered, can help in identifying different compositional domains in the lithosphere. Satellite observations also provide global data on the temporal variations of the gravity field. In the last study, I show that global gravity-change observations from the GRACE satellite mission can be used to study GIA in the Barents Sea Region. The Barents Sea is subject to ongoing postglacial uplift since the melting of the Weichselian ice sheet that covered this region. The deglaciation history is not well known because there is only data from locations close to the boundary of the former ice sheet, in Franz Joseph Land, Svalbard, and Novaya Zemlya. At these locations the magnitude of the GIA uplift is limited, reducing the signal-to-noise of the data. The GRACE mission measures the gravity-change due to GIA at the center of the Barents Sea, where the maximum uplift and ongoing gravity-change is situated. I show that the linear trend in the gravity-change derived from a decade of observations from the GRACE satellite mission can constrain the volume of the ice sheet after correcting for current ice-melt, hydrology and far-field gravitational effects. Regional ice loading models based on new geologically-inferred ice margin chronologies show a significantly better fit to the GRACE data than the global ice models ICE-5G and ICE-6G_C. The regional ice models in this study contain less ice mass during LGM in the Barents Sea than ICE-5G (5-6.3 m equivalent sea level vs. 8.5 m). Also, I show that the GRACE gravity-change is sensitive to the upper mantle viscosity underneath the Barents sea, for which I found a minimum value of 4x1020 Pas, regardless of the ice loading history. The GRACE gravity-change should be used as a constraint in any future GIA modelling of the Barents Sea, because it is the only measurement that captures the signal of maximum GIA. The high resolution and accurate global gravity field models do give new insights in the structure and density distribution of the upper mantle. The presented studies in this dissertation demonstrate that analysing the spectral signature of gravity data is very useful. Medium-to-short-scale features, like lateral density variation in the lithosphere and GIA gravity-change in the Barents Sea can be separate from other gravity-change sources by applying spectral filters. For longer wavelength signals, such as the GIA static gravity signal in Fennoscandia, this proves to be more difficult due to the overlap in the long-wavelength region by mantle convection signals and other deep mantle signals. On the whole, the global gravity field models and their spectral signature play an important part in building a global density model of the Earth, in which lithosphere, GIA, but also mantle convection and core-mantle boundary effects need to be combined to explain the gravity field. @en

The mass sources that are responsible for the longwavelength gravity field of the Earth are not yet fully understood. The biggest candidate to describe these anomalies is mantle convection, yet models that can explain the mantle convection and the gravity field are not available. Another candidate is the core-mantle boundary with a density contrast of 4500 kg/m3 between the ferrous core and the silicate mantle. Due to the high density contrast variations in the core-mantle boundary can have a great impact on the gravity field. Also, density anomalies above the core-mantle boundary are large enough to be seen in the gravity field. The geometry of these anomalies amount to hundreds of km’s with density contrast up to 100 kg/m3. Sensitivity tests using similar dimensions and density contrasts show that gravity anomalies of 10-100 mGal can be computed, which is in the same as the longwavelength part of the gravity field. We argue that the gravity signal from structures at the deepest part of the lower mantle should be part of any global analysis. During the 3D Earth project, we will use seismic models of the core-mantle region to simulate more realistic geometries and density anomalies to study their effect on the global gravity field. This presentation is part of the ESA Support To Science Element - 3D Earth – which is presented by Jörg Ebbing @en

Lithospheric density structure can be constructed from seismic tomography, gravity modelling, or using both data sets. The different approaches have their own uncertainties and limitations. This study aims to characterize and quantify some of the uncertainties in gravity modelling of lithosphere densities. To evaluate the gravity modelling we compare gravity-based and seismic velocity-based approaches to estimating lithosphere densities. In this study, we use a crustal model together with lithospheric isostasy and gravity field observations to estimate lithosphere densities. To quantify the effect of uncertainty in the crustal model, three models are implemented in this study: CRUST1.0, EuCrust-07 and a high-resolution P-wave velocity model of the British Isles and surrounding areas. Different P-wave velocity-to-density conversions are used to study the uncertainty in these conversion methods. The crustal density models are forward modelled into gravity field quantities using a method that is able to produce spherical harmonic coefficients. Deep mantle signal is assumed to be removed by removing spherical harmonic coefficients of degree 0–10 in the observed gravity field. The uncertainty in the resulting lithosphere densities due to the different crustal models is ±110 kg m−3, which is the largest uncertainty in gravity modelling. Other sources of uncertainty, such as the VP to density conversion (±10 kg m−3), long-wavelength truncation (±5 kg m−3), choice of reference model (<±20 kg m−3) and Lithosphere Asthenosphere Boundary uncertainty (±30 kg m−3), proved to be of lesser importance. The resulting lithosphere density solutions are compared to density models based on a shear wave velocity model. The comparison shows that the gravity-based models have an increased lateral resolution compared to the tomographic solutions. However, the density anomalies of the gravity-based models are three times higher. This is mainly due to the high resolution in the gravity field. To account for this, the gravity-based density models are filtered with a spatial Gaussian filter with 200 km half-width, which results in similar density estimates (±35 kg m−3) with the tomographic approach. Lastly, the gravity-based density is used to estimate laterally varying conversion factors, which correlate with major tectonic regions. The independent gravity-based solutions could help in identifying different compositional domains in the lithosphere, when compared to the tomographic solutions.@en

This article reviews a spectral forward gravity field modelling method that was initially designed for topographic/isostatic mass reduction of gravity data. The method transforms 3D spherical density models into gravitational potential fields using a spherical harmonic representation. The binomial series approximation in the approach, which is crucial for its computational efficiency, is examined and an error analysis is performed. It is shown that, this method cannot be used for density layers in crustal and upper mantle regions, because it results in large errors in the modelled potential field. Here, a correction is proposed to mitigate this erroneous behaviour. The improved method is benchmarked with a tesseroid gravity field modelling method and is shown to be accurate within ±4 mGal for a layer representing the Moho density interface, which is below other errors in gravity field studies. After the proposed adjustment the method can be used for the global gravity modelling of the complete Earth's density structure.

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In November 1934, Den Helder, The Netherlands, the start of a remarkable voyage commenced. The Hr. Ms.K-XVIII, a Dutch submarine, was about to set sail to Soerabaya, Indonesia. Onboard was a Dutch professor, Felix Andries Vening Meinesz. He was able to measure the Earth’s gravity field with similar precision as on land for the first time in history using his innovative pendulum apparatus. His ground breaking data and systematic way of working changed the way of performing scientific expeditions.@en