Tagging-the-triangle algorithm for partitioning features with inconsistent boundaries

In spatial data sets, gaps or overlaps among features are frequently found in spatial tessellations due to the non-abutting edges with adjacent features. These non-abutting edges in loose tessellations are also called inconsistent boundaries or slivers; polygons containing at least one inconsistent boundary are called inconsistent polygons or sliver polygons. The existing algorithms to solve topological inconsistencies in sliver polygons suffer from one or more of three major issues, namely determination of tolerances, excessive CPU processing time for large data sets and loss of vertex history. In this article, we introduce a new algorithm that mitigates these three issues. Our algorithm efficiently searches the features with inconsistent polygons in a given spatial data set and logically partitions them among adjacent features. The proposed algorithm employs the constrained Delaunay triangulation technique to generate labelled triangles from which inconsistent polygons with gaps and overlaps are identified using label counts. These inconsistent polygons are then partitioned using the straight skeleton method. Moreover, each of these partitioned gaps or overlaps is distributed among the adjacent features to improve the topological consistency of the spatial data sets. We experimentally verified our algorithm using the real land cadastre data set. The comparison results show that the proposed algorithm is four times faster than the existing algorithm for data sets with 200,000 edges.     

The effects of frequency-dependent quasar variability on the celestial reference frame

We examine the relationship between source position stability and astrophysical properties of radio-loud quasars making up the International Celestial Reference Frame (ICRF2). Understanding this relationship is important for improving quasar selection and analysis strategies, and therefore reference frame stability. We construct flux density time series, known as light curves, for 95 of the most frequently observed ICRF2 quasars at both the 2.3 and 8.4 GHz geodetic very long baseline interferometry (VLBI) observing bands. Because the appearance of new quasar components corresponds to an increase in quasar flux density, these light curves alert us about potential changes in source structure before they appear in VLBI images. We test how source position stability depends on three astrophysical parameters: (1) flux density variability at X band; (2) time lag between flares in S and X bands; (3) spectral index root-mean-square (rms), defined as the variability in the ratio between S and X band flux densities. We find that the time lag between S and X band light curves provides a good indicator of position stability: sources with time lags $<$ 0.06 years are significantly more stable ( $>$ 20 % improvement in weighted rms) than sources with larger time lags. A similar improvement is obtained by observing sources with low $(<$ 0.12) spectral index variability. On the other hand, there is no strong dependence of source position stability on flux density variability in a single frequency band. These findings can be understood by interpreting the time lag between S and X band light curves as a measure of the size of the source structure. Monitoring of source flux density at multiple frequencies therefore appears to provide a useful probe of quasar structure on scales important to geodesy. The observed astrometric position of the brightest quasar component (the core) is known to depend on observing frequency. We show how multi-frequency flux density monitoring may allow the dependence on frequency of the relative core positions along the jet to be elucidated. Knowledge of the position–frequency relation has important implications for current and future geodetic VLBI programs, as well as the alignment between the radio and optical celestial reference frames.     

Geophysical exploration on the subsurface geology of La Garrotxa monogenetic volcanic field (NE Iberian Peninsula)

We applied self-potential (SP) and electrical resistivity tomography (ERT) to the exploration of the uppermost part of the substrate geology and shallow structure of La Garrotxa monogenetic volcanic field, part of the European Neogene–Quaternary volcanic province. The aim of the study was to improve knowledge of the shallowest part of the feeding system of these monogenetic volcanoes and of its relationship with the subsurface geology. This study complements previous geophysical studies carried out at a less detailed scale and aimed at identifying deeper structures, and together will constitute the basis to establish volcanic susceptibility in La Garrotxa. SP study complemented previous smaller-scale studies and targeted key areas where ERT could be conducted. The main new results include the generation of resistivity models identifying dykes and faults associated with several monogenetic cones. The combined results confirm that shallow tectonics controlling the distribution of the foci of eruptive activity in this volcanic zone mainly correspond to NNW–SSE and accessorily by NNE–SSW Neogene extensional fissures and faults and concretely show the associated magmatic intrusions. These structures coincide with the deeper ones identified in previous studies, and show that previous Alpine tectonic structures played no apparent role in controlling the loci of this volcanism. Moreover, the results obtained show that the changes in eruption dynamics occurring at different vents located at relatively short distances in this volcanic area are controlled by shallow stratigraphical, structural and hydrogeological differences underneath these monogenetic volcanoes.     

Can a Training Image Be a Substitute for a Random Field Model?

In most multiple-point simulation algorithms, all statistical features are provided by one or several training images (TI) that serve as a substitute for a random field model. However, because in practice the TI is always of finite size, the stochastic nature of multiple-point simulation is questionable. This issue is addressed by considering the case of a sequential simulation algorithm applied to a binary TI that is a genuine realization of an underlying random field. At each step, the algorithm uses templates containing the current target point as well as all previously simulated points. The simulation is validated by checking that all statistical features of the random field (supported by the simulation domain) are retrieved as an average over a large number of outcomes. The results are as follows. It is demonstrated that multiple-point simulation performs well whenever the TI is a complete (infinitely large) realization of a stationary, ergodic random field. As soon as the TI is restricted to a limited domain, the statistical features cannot be obtained exactly, but integral range techniques make it possible to predict how much the TI should be extended to approximate them up to a prespecified precision. Moreover, one can take advantage of extending the TI to reduce the number of disruptions in the execution of the algorithm, which arise when no conditioning template can be found in the TI.     

The tripole: A new coherent vortex structure of incompressible two-dimensional flows

Abstract

Using a contour dynamical algorithm, we have found rotating tripolar V-state solutions for the inviscid Euler equations in two-dimensions. We have studied their geometry as a function of their physical parameters. Their stability was investigated with the aid of contour surgery, and most of the states were found to be stable. Under finite-amplitude perturbations, tripoles are shown to either fission into two asymmetric dipoles or to evolve into a shielded axisymmetric vortex, demonstrating the existence of two new ‘‘reversible transitions'’ between topologically distinct coherent vortex structures. These dynamical results are confirmed by pseudo-spectral simulations, with which we also show how continuous tripolar long-lived coherent vortex structures can be generated in a variety of ways.     

Numerical Studies of Fluid Flow in Microgravity Conditions for Confined Crystal Growth

We study the convective flow induced by residual accelerations in microgravity conditions for different geometric arrangements which are relevant to crystal growth experiments. We consider both constantand oscillating acceleration and focus mostly on the transient relaxation dynamics. Results are relevant to estimate impact of more realistic residual accelerations in crystal growth experiments.     

Continual long-term monitoring of methane in wells above the Utica Shale using total dissolved gas pressure probes

Hydrogeology Journal - Monitoring of dissolved methane concentrations in groundwater is required to identify impacts from oil and gas development and to understand temporal variability under...     

New Validity Conditions for the Multivariate Matérn Coregionalization Model,with an Application to Exploration Geochemistry

Mathematical Geosciences - This paper addresses the problem of finding parametric constraints that ensure the validity of the multivariate Matérn covariance for modeling the spatial...     

Construction of Structural Geological Model Using Monte Carlo Simulation

Geotechnical and Geological Engineering - To optimize the prediction of structural geological conditions in the underground as of data collected at the surface, due to the usual great uncertainties...     

Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.