Near Earth Object impact simulation tool for supporting the NEO mitigation decision making process

This paper describes the development of a computer simulation tool, NEOSim, capable of modelling small NEO impacts and their effect on the global population. The development of the tool draws upon existing models for the atmospheric passage and impact processes. Simulation of the land and ocean impact effects, combined with a population density model, leads to casualty estimation at both a regional and global level. Casualty predictions are based upon the intensity of each impact effect on the local population density, with consideration given to the population inside or outside local infrastructure. Two case studies are presented. The first evaluates the potential threat to the UK, and highlights coastal locations as being at greatest risk. Locations around Cornwall demonstrate an increase in casualties above the local average. The second case study concerns the potential impact of asteroid (99942) Apophis in 2036. Propagation of the possible orbits along the line of variance leads to an extensive path of risk on the Earth. Deflection of the asteroid, by a variety of means, will move the projected impact site along this path. Results generated by NEOSim for the path indicate that South American countries such as Colombia and Venezuela are at a greatest risk with estimated casualty figures in excess of 10 million. Applications of this software to the NEO threat are discussed, along with the next stage of NEO impact simulation development.

A Proposed Model for the Measurement of Population Density

A mathematical model is proposed to measure population density using a formula called the population density index ( PDI). The population density index model includes a measure of interperson distance and is scaled for geometric area. The population density model measures population density with greater precision and flexibility than the conventional population density model. The population density index model is designed for small-scale projects involving as few as two and as many as one hundred density points. The derivation of the model is presented, along with an example of its use in a research project at the Naval Underwater Systems Center.

Spatial Aggregation in Gravity Models: 2. One-Dimensional Population Density Models

This paper, the second of four, is concerned with applying a methodology for analysing the spatial aggregation problem in gravity models outlined in the first paper. The methodology is based on a consistent framework for linking measures of pattern in interaction data to the derivation and estimation of related interaction models using spatial information theory. In this quest, a link is forged between information in data and the parameters of an associated model, and in part 1 it was suggested that if this link could be formalised then a means would be available for predicting changes in model parameters from different aggregations of the data, prior to the actual estimation of the models themselves. This relationship can be formalised for the case of the continuous one-dimensional interaction model such as the population density model, and this paper is concerned with demonstrating such an application to aggregations of zones in the Reading region. The framework is first described and two continuous models are presented. Then, the discrete model is estimated by means both of regression and of entropy techniques applied to various aggregations of the region, and the resulting parameters are related to the predicted and observed informations. Finally, the parameters approximated from observed information by use of the theoretical models are compared with the estimated parameters, and the approximation is deemed good, thus providing some confidence in the general concepts developed to handle these types of problem.