Selected Challenges From Spatial Statistics For Spatial Econometricians

Griffith and Paelinck (2011) present selected non-standard spatial statistics and spatial econometrics topics that address issues associated with spatial econometric methodology. This paper addresses the following challenges posed by spatial autocorrelation alluded to and/or derived from the spatial statistics topics of this book: the Gaussian random variable Jacobian term for massive datasets; topological features of georeferenced data; eigenvector spatial filtering-based georeferenced data generating mechanisms; and, interpreting random effects.Artykuł prezentuje wybrane, niestandardowe statystyki przestrzenne oraz zagadnienia ekonometrii przestrzennej. Rozważania teoretyczne koncentrują się na wyzwaniach wynikających z autokorelacji przestrzennej, nawiązując do pojęć Gaussowskiej zmiennej losowej, topologicznych cech danych georeferencyjnych, wektorów własnych, filtrów przestrzennych, georeferencyjnych mechanizmów generowania danych oraz interpretacji efektów losowych

Emergency Management Training for Transportation Agencies

State transportation agencies have a variety of responsibilities related to emergency management. Field personnel manage events--from day-to-day emergencies to disasters--using the Incident Command System (ICS) as their organizational basis. At the headquarters level, the Emergency Operations Center (EOC) coordinates the use of resources across the department and its districts, with other state departments and agencies, and through the federal Emergency Support Function 1. District-level EOCs coordinate with the department. In extreme events, the transportation department may only be able to deliver limited essential services in austere conditions, so a continuity of operations/ continuity of government plan (COOP/COG) is essential. This research applied the principles of andragogy to deliver ICS field level training, EOC training and COOP/COG training to state transportation agency’s staff in all districts and at headquarters. The data supports the need for adult-oriented methods in emergency management training

Modeling Spatial Autocorrelation in Spatial Interaction Data: A Comparison of Spatial Econometric and Spatial Filtering Specifications

The need to account for spatial autocorrelation is well known in spatial analysis. Many spatial statistics and spatial econometric texts detail the way spatial autocorrelation can be identified and modelled in the case of object and field data. The literature on spatial autocorrelation is much less developed in the case of spatial interaction data. The focus of interest in this paper is on the problem of spatial autocorrelation in a spatial interaction context. The paper aims to illustrate that eigenfunction-based spatial filtering offers a powerful methodology that can efficiently account for spatial autocorrelation effects within a Poisson spatial interaction model context that serves the purpose to identify and measure spatial separation effects to interregional knowledge spillovers as captured by patent citations among high-technology-firms in Europe.

Nanoparticle-stabilized natural gas liquid emulsions for heavy oil recovery

The transport of nanoparticle-stabilized emulsions through porous media and its effects on enhanced oil recovery are only marginally understood. This thesis explores the characteristics of nanoparticle-stabilized emulsion flow in porous media, especially in respect to its residual oil recovery capabilities. Widely available, low-cost natural gas liquids were emulsified in brines using polyethylene glycol-coated silica nanoparticles. Emulsions with various aqueous nanoparticle phases and oil phases were generated via beadpack co-injection or sonication at varying salinities for observations of emulsion characteristics. In general it was found that high-salinity emulsions generated via sonication were more robust: statically and dynamically more stable than their lower salinity counterparts. Emulsions generated via beadpack co-injection displayed non-Newtonian shear-thinning rheology and larger droplet sizes. Emulsions generated via sonication displayed Newtonian rheology and much smaller droplet sizes. Coreflood experiments were conducted to assess the effects of different emulsion properties on residual oil recovery of heavy oils, effective permeability reduction capabilities (i.e. conformance control), and in-situ emulsion stability. During low salinity emulsion floods, no emulsion was produced in the effluent. However, by increasing the salinity, emulsion was produced in the effluent and up to 89% residual mineral oil was recovered at low injection rates (~16 ft/day). Increases in residual oil recovery during high salinity floods can be explained by DLVO and Filtration theory. By increasing the ionic concentration, the magnitude of repulsive electrostatic double layer forces are decreased, leading to increased droplet interception on grain surfaces. This results in more efficient droplet-pore throat blockage, therefore, redirecting displacing fluids into less permeable zones. Increasing the magnitude of the zeta-potential of injected emulsions resulted in marginal increases in oil recovery, significant reductions in effective permeability, and in-situ emulsion stability. It was concluded that at high zeta-potentials, emulsion droplets are likely repulsed via electrostatic repulsive forces rather than through mechanical bridging of aggregates between droplets, as observed in high salinity emulsions. The increase in permeability reduction in the high zeta-potential case occurs due to the droplets’ increased resistance to flow through a pore throat, a product of increased repulsive forces between droplets and grains encountered at tight constrictionsPetroleum and Geosystems Engineerin

A comparison of six analytical disease mapping techniques as applied to West Nile Virus in the coterminous United States

West Nile Virus has quickly become a serious problem in the United States (US). Its extremely rapid diffusion throughout the country argues for a better understanding of its geographic dimensions. Both 2003 and 2004 percentages of deaths by numbers of reported human cases, for the 48 coterminous US states, are analyzed with a range of spatial statistical models, seeking to furnish a fuller appreciation of the variety of models available to researchers interested in analytical disease mapping. Comparative results indicate that no single spatial statistical model specification furnishes a preferred description of these data, although normal approximations appear to furnish some questionable implications. Findings also suggest several possible future research topics

On the eigenvalue distribution of adjacency matrices for connected planar graphs

This paper describes the previously unknown statistical distribution of adjacency matrix spectra for planar graphs, also known as spatial weights matrices, in terms of the following three readily available eigenvalue properties: extremes, rank orderings, and sums of powers. This distribution is governed by at most six parameters that, once known, allow accurate approximations of eigenvalues to be computed without resorting to numerical matrix methods applied on a case-by-case basis. Parameter estimates for illustrative real-world examples are obtained using nonlinear least squares regression techniques. Three conjectures are proposed, and graphical and trend results are reported for a diverse set of planar graph-based matrices