Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

With an increasing demand for raw materials, predictive models that support successful mineral exploration targeting are of great importance. We evaluated different machine learning techniques with an emphasis on boosting algorithms and implemented them in an ArcGIS toolbox. Performance was tested on an exploration dataset from the Iberian Pyrite Belt (IPB) with respect to accuracy, performance, stability, and robustness. Boosting algorithms are ensemble methods used in supervised learning for regression and classification. They combine weak classifiers, i.e., classifiers that perform slightly better than random guessing to obtain robust classifiers. Each time a weak learner is added; the learning set is reweighted to give more importance to misclassified samples. Our test area, the IPB, is one of the oldest mining districts in the world and hosts giant volcanic-hosted massive sulfide (VMS) deposits. The spatial density of ore deposits, as well as the size and tonnage, makes the area unique, and due to the high data availability and number of known deposits, well-suited for testing machine learning algorithms. We combined several geophysical datasets, as well as layers derived from geological maps as predictors of the presence or absence of VMS deposits. Boosting algorithms such as BrownBoost and Adaboost were tested and compared to Logistic Regression (LR), Random Forests (RF) and Support Vector machines (SVM) in several experiments. We found performance results relatively similar, especially to BrownBoost, which slightly outperformed LR and SVM with respective accuracies of 0.96 compared to 0.89 and 0.93. Data augmentation by perturbing deposit location led to a 7% improvement in results. Variations in the split ratio of training and test data led to a reduction in the accuracy of the prediction result with relative stability occurring at a critical point at around 26 training samples out of 130 total samples. When lower numbers of training data were introduced accuracy dropped significantly. In comparison with other machine learning methods, Adaboost is user-friendly due to relatively short training and prediction times, the low likelihood of overfitting and the reduced number of hyperparameters for optimization. Boosting algorithms gave high predictive accuracies, making them a potential data-driven alternative for regional scale and/or brownfields mineral exploration.

     

Updated Characterization of Dorowa Phosphate Rock Mined in Zimbabwe

Natural Resources Research - The physical and chemical characteristics of mined phosphate rock will vary temporally as the location and nature of the ore body changes and as the type of equipment...     

雪宝顶区块流域钙华形成的生物作用研究

钙华不仅具有重要的景观旅游价值,而且对确定区内碳酸盐沉积特征、环境演化规律及同期环境生物的作用与贡献有重要的研究意义.本文在对比国内外典型钙华特征的基础上,以黄龙和九寨沟为例,对雪宝顶区块流域内钙华的沉积特征、环境化学与生物作用进行阐述,指出了雪宝顶区块流域冷水型钙华的形成与演化是化学沉积-溶解作用、生物沉积与溶蚀作用...     

Reduced Hamiltonian formalism for general-relativistic adiabatic fluids and applications

For the dynamics of general-relativistic adiabatic fluids a reduced Hamiltonian formalism is presented. For slowly moving fluids an approximation scheme is defined. The first steps of the scheme are worked out explicitly. Radiation damping and emission, and backscattering are discussed. The usefulness of the formalism for numerical relativity is pointed out.     

Time to talk knowledge

As part of the secondary school qualification repackaging, the Ministry of Education has requested the geography education community define what constitutes their “critical body of knowledge.” In this article, I discuss three knowledge‐oriented themes focused on: (a) recent assessment trends in geography; (b) the predictive value of NCEA Level 3 geography with 100‐level success and (c) the nature of knowledge as expressed by the New Zealand Curriculum and assessment. Taken together, these themes suggest a need for a serious conversation about knowledge in school geography, as a pre‐cursor to the re‐design of the geography standards matrix.     

Representation of Uncertainty and Integration of PGIS-based Grazing Intensity Maps Using Evidential Belief Functions

In a project to classify livestock grazing intensity using participatory geographic information systems (PGIS), we encountered the problem of how to synthesize PGIS-based maps of livestock grazing intensity that were prepared separately by local experts. We investigated the utility of evidential belief functions (EBFs) and Dempster's rule of combination to represent classification uncertainty and integrate the PGIS-based grazing intensity maps. These maps were used as individual sets of evidence in the application of EBFs to evaluate the proposition that " This area or pixel belongs to the high, medium, or low grazing intensity class because the local expert(s) says (say) so ". The class-area-weighted averages of EBFs based on each of the PGIS-based maps show that the lowest degree of classification uncertainty is associated with maps in which "vegetation species" was used as the mapping criterion. This criterion, together with local landscape attributes of livestock use may be considered as an appropriate standard measure for grazing intensity. The maps of integrated EBFs of grazing intensity show that classification uncertainty is high when the local experts apply at least two mapping criteria together. This study demonstrates the usefulness of EBFs to represent classification uncertainty and the possibility to use the EBF values in identifying and using criteria for PGIS-based mapping of livestock grazing intensity.     

Phase center modeling for LEO GPS receiver antennas and its impact on precise orbit determination

Most satellites in a low-Earth orbit (LEO) with demanding requirements on precise orbit determination (POD) are equipped with on-board receivers to collect the observations from Global Navigation Satellite systems (GNSS), such as the Global Positioning System (GPS). Limiting factors for LEO POD are nowadays mainly encountered with the modeling of the carrier phase observations, where a precise knowledge of the phase center location of the GNSS antennas is a prerequisite for high-precision orbit analyses. Since 5 November 2006 (GPS week 1400), absolute instead of relative values for the phase center location of GNSS receiver and transmitter antennas are adopted in the processing standards of the International GNSS Service (IGS). The absolute phase center modeling is based on robot calibrations for a number of terrestrial receiver antennas, whereas compatible antenna models were subsequently derived for the remaining terrestrial receiver antennas by conversion (from relative corrections), and for the GNSS transmitter antennas by estimation. However, consistent receiver antenna models for space missions such as GRACE and TerraSAR-X, which are equipped with non-geodetic receiver antennas, are only available since a short time from robot calibrations. We use GPS data of the aforementioned LEOs of the year 2007 together with the absolute antenna modeling to assess the presently achieved accuracy from state-of-the-art reduced-dynamic LEO POD strategies for absolute and relative navigation. Near-field multipath and cross-talk with active GPS occultation antennas turn out to be important and significant sources for systematic carrier phase measurement errors that are encountered in the actual spacecraft environments. We assess different methodologies for the in-flight determination of empirical phase pattern corrections for LEO receiver antennas and discuss their impact on POD. By means of independent K-band measurements, we show that zero-difference GRACE orbits can be significantly improved from about 10 to 6 mm K-band standard deviation when taking empirical phase corrections into account, and assess the impact of the corrections on precise baseline estimates and further applications such as gravity field recovery from kinematic LEO positions.     

Equilibrium erosion of soft rock shores with a shallow or absent beach under increased sea level rise

A process-based numerical model was used to explore the response of soft rock shores with low volume beaches to variable rates of sea level rise. Equilibrium recession rates were simulated for ranges of wave height and period, tidal amplitude, rock strength, beach volume and rate of sea level rise. Equilibrium shore profiles were found to be steeper with higher rates of sea level rise. Beaches were represented as protective surfaces yet were found to cause no significant reduction in equilibrium recession rate when their volumes were below a critical threshold. Reduced equilibrium recession rates were found with beaches that extended sufficiently far below low tide level. The model results imply that, given several constraints, a very simple relationship exists between increased rates of sea level rise and the response of eroding composite soft rock/low volume beach shores.     

Sediment resuspension events induced by the wake wash of deep-draft vessels

Hydrodynamics and sediment resuspension events, induced at the shoreline by a deep-draft vessel passing nearby, are described. Measurements (pressure, currents and turbidity) were obtained at 4 Hz, on a lower beach ~50 m from a channel where large car ferries operate in Wootton Creek, Isle of Wight. The study focuses on a representative 8-min 32-s-long record, during which two large vessels passed the channel section. At the shore, the passage of each vessel induced a long-period water-level drawdown, followed by a water-level oscillation (seiche) of similar period, and the short-period waves of the wake. Both drawdowns were the main constituents of the prevailing wave pattern. The second drawdown was the largest in amplitude, in response to a higher speed of the ferry, and the influence of the seiche which had been activated during the preceding event. Two successive peaks of turbidity were observed shortly after this drawdown. Analyses of current velocity and direction indicate that the sediments resuspended originated from the shallower upper beach. Anthropogenically induced erosion of the foreshore is predicted at Wootton Creek.     

The curse of physiology—challenges and opportunities in the interpretation of geochemical data from mollusk shells

Physiology corrupts geochemical records of mollusk shells in many ways, e.g., by actively controlling the incorporation of trace elements in the skeleton. However, the effects of variable biomineralization rates and growth cessation have largely remained unconsidered. Mediated by endogenous timekeeping mechanisms, mollusks stop growing skeletal material on a regular basis ranging from ultradian to annual timescales. During growth cessation, the shells do not record environmental conditions. Shell growth also stops when environmental conditions are beyond the physiological tolerance of the organism, e.g., above and below genetically determined, species-specific thermal extremes where shell growth slows and eventually ceases. Such growth disruptions can occur at non-periodic time intervals. Due to growth retardations and halts, proxy records of mollusk shells are thus incomplete, and reconstructed environmental amplitudes prone to truncation. Furthermore, environmental records are biased toward the physiological optimum of the animal. Favorable environmental conditions increase shell growth, whereas adverse environmental conditions result in reduced shell production and lowered overall metabolism. Not least, the duration of the growing season and overall growth rate decrease as the mollusk grows older. Mathematical modeling approaches can significantly improve proxy records obtained from mollusk shells. For example, if the duration of growth cessation is known, it may be possible to model the missing environmental record. It is also fairly easy to account for age-related growth trends, or variable time-averaging in different portions of the shell. However, a major premise for a reliable interpretation of proxy records from a mollusk shell or other organisms secreting biogenic hard parts is a proper understanding of the physiology, and of course, a high-resolution record of the many different environmental factors that may influence physiology and shell growth. The present paper reviews examples from the literature, and unpublished data on how physiology influences geochemical proxy records from mollusk shells, and presents methods how to eliminate such adverse effects.