A Top-Cut Model for Deposits with Heavy-Tailed Grade Distribution

In some ore deposits, the grade distribution is heavy-tailed and high values make the inference of first- and second-order statistics nonrobust. In the case of gold data, high values are usually cut and the block estimation is performed using truncated grades. With this method, a part of the deposit is omitted, resulting in a potential bias on resources figures. Ad-hoc corrections can be applied on the final figures to take into account the tail of the grade distribution, but no theoretical guidelines are available. A geostatistical model has been developed to handle high values based on the assumption that for high grade zones, the only tangible information is the geometry. The grade variable z can be split into three parts: the truncated grade ( $\operatorname{Min} (z, z_{\mathrm{e}})$ where z _e is the top-cut grade), a weighted indicator above top-cut grade (1{z≥z _e}), and a residual. Within this framework, the residual is poorly structured, and in most cases is a pure nugget-effect. Moreover, it has no spatial correlation with the truncated grade and the indicator above top-cut grade. This decomposition makes the variographic study more robust because variables (indicator and truncated grade) do not keep high grade values. The underlying hypotheses can be tested on experimental indicator variograms and the top-cut grade can be justified. Finally, the estimation is based on a truncated grade and indicator cokriging. The model is applied to blast holes from a gold deposit and on a simulated example. Both cases illustrate the benefits of keeping the high values in the estimation process via an appropriate mathematical model.     

Change of Support for Estimating Local Block Grade Distributions

An important aspect in mineral resource evaluation is the reduction of variance when post-processing the grade distributions defined on the support (volume) of the available data into distributions defined on the support of the proposed selective mining units. Although the volume-variance relationship is well understood for the estimation of global grade distributions, it is still an unsolved issue for local estimation studies based on non-parametric geostatistical methods, such as indicator kriging, for which the support correction is not inherent to the method. To clarify this relationship, the local change of support problem is examined in the scope of two parametric models (multi-Gaussian and discrete Gaussian models). It is shown that the variance reduction factor between point and block-support local distributions depends on the block being considered and is less than the global variance reduction factor. As a consequence, post-processing the local point-support grade distributions on the basis of the latter systematically understates the importance of the change of support at the local scale and makes selective mining appear more economically attractive than it really is. In the light of these results, a methodology is proposed to post-process the local point-support distributions obtained via non-parametric (indicator) methods into block-support distributions. An application to simulated data indicates that this methodology provides an accurate estimation at the block support when dealing with diffusion-type random fields.     

Evaluation of a high-resolution regional climate simulation over Greenland

A simulation of the 1991 summer has been performed over south Greenland with a coupled atmosphere–snow regional climate model (RCM) forced by the ECMWF re-analysis. The simulation is evaluated with in-situ coastal and ice-sheet atmospheric and glaciological observations. Modelled air temperature, specific humidity, wind speed and radiative fluxes are in good agreement with the available observations, although uncertainties in the radiative transfer scheme need further investigation to improve the model’s performance. In the sub-surface snow-ice model, surface albedo is calculated from the simulated snow grain shape and size, snow depth, meltwater accumulation, cloudiness and ice albedo. The use of snow metamorphism processes allows a realistic modelling of the temporal variations in the surface albedo during both melting periods and accumulation events. Concerning the surface albedo, the main finding is that an accurate albedo simulation during the melting season strongly depends on a proper initialization of the surface conditions which mainly result from winter accumulation processes. Furthermore, in a sensitivity experiment with a constant 0.8 albedo over the whole ice sheet, the average amount of melt decreased by more than 60%, which highlights the importance of a correctly simulated surface albedo. The use of this coupled atmosphere–snow RCM offers new perspectives in the study of the Greenland surface mass balance due to the represented feedback between the surface climate and the surface albedo, which is the most sensitive parameter in energy-balance-based ablation calculations.     

Fahien reconsidered: Pleistocene exploitation of wild bananas and Holocene introduction of Musa cultivars to Sri Lanka

A recent publication on the phytolith assemblage at Fahien rockshelter, Sri Lanka (Premathilake and Hunt) is argued to represent: the exploitation of wild Musa acuminata and M. balbisiana during the Late Pleistocene; the introduction of edible diploid cultivars from the Southeast Asia–New Guinea region during the early to mid‐Holocene; the generation and cultivation of triploid banana hybrids on Sri Lanka before 6194–5994 cal bp ; and the subsequent spread of derived triploid cultivars to mainland India and westward to Africa. A careful review of the archaeobotanical research presented by Premathilake and Hunt, in the context of broader multidisciplinary evidence (agronomy, archaeobotany, genetics and linguistics) for the domestication and spread of banana cultivars, indicates that three main aspects of their argument are problematic: the lack of clarity in the characterization of banana domestication in the past; the methods used to discriminate phytoliths into banana taxa; and the promotion of Sri Lanka as a source region rather than a recipient of banana cultivars. Following reconsideration, the Fahien evidence is consistent with previous interpretations for the origins of diploid and significant triploid cultivars outside of Sri Lanka and dispersal to that island. © 2019 John Wiley & Sons, Ltd.     

Rainfall intensity patterns derived from the urban network of Barcelona (NE Spain)

Theoretical and Applied Climatology - An analysis of the normalised rainfall intensity curves in Barcelona (NE Spain) has been undertaken from 41 selected rain rate episodes recorded by an urban...     

A context-sensitive correlated random walk: a new simulation model for movement

Computational Movement Analysis focuses on the characterization of the trajectory of individuals across space and time. Various analytic techniques, including but not limited to random walks, Brownian motion models, and step selection functions have been used for modeling movement. These fall under the rubric of signal models which are divided into deterministic and stochastic models. The difficulty of applying these models to the movement of dynamic objects (e.g. animals, humans, vehicles) is that the spatiotemporal signal produced by their trajectories a complex composite that is influenced by the Geography through which they move (i.e. the network or the physiography of the terrain), their behavioral state (i.e. hungry, going to work, shopping, tourism, etc.), and their interactions with other individuals. This signal reflects multiple scales of behavior from the local choices to the global objectives that drive movement. In this research, we propose a stochastic simulation model that incorporates contextual factors (i.e. environmental conditions) that affect local choices along its movement trajectory. We show how actual global positioning systems observations can be used to parameterize movement and validate movement models and argue that incorporating context is essential in modeling movement.     

Information infrastructure for Australia’s Integrated Marine Observing System

Australia’s Integrated Marine Observing System (IMOS, imos.org.au) is research infrastructure to establish an enduring observing program for Australian oceanic waters and shelf seas. The observations cover physical, biological, and chemical variables to address themes of multi-decadal ocean change, climate variability and weather extremes, boundary currents and inter-basin flows, continental shelf processes and ecosystem responses.IMOS observations are collected by national facilities based on various platform types and operated by partner institutions around the country. In this paper we describe the infrastructure and workflows developed to manage and distribute the data to the public. We highlight the existing standards and open-source software we have adopted, and the contributions we have made. To demonstrate the value of this infrastructure we provide some illustrations of use and uptake.All IMOS data are freely and openly available to the public via the Ocean Portal (https://imos.aodn.org.au). All IMOS-developed software is open-source and accessible at https://github.com/aodn.     

Towards a multi-scale approach for an Earth observation-based assessment of natural resource exploitation in conflict regions

The exploitation of resources, if not properly managed, can lead to spoiling natural habitats as well as to threatening people’s health, livelihoods and security. The paper discusses a multi-scale Earth observation-based approach to provide independent information related to exploitation activities of natural resources for countries which are experiencing armed conflict. The analyses are based on medium to very high spatial resolution optical satellite data. Object-based image analysis is used for information extraction at these different scales. On a subnational level, conflict-related land cover changes as an indication of potential hot spots for exploitation activities are classified. The regional assessment provides information about potential activity areas of resource exploitation, whereas on a local scale, a site-specific assessment of exploitation areas is performed. The study demonstrates the potential of remote sensing for supporting the monitoring and documentation of natural resource exploitation in conflict regions.