Planetary atmosphere evolution:Do other habitable planets exist and can we detect them?

The goal of this conference is to consider whether it is possible within the next few decades to detect Earth-like planets around other stars using telescopes or interferometers on the ground or in space. Implicit in the term “Earth-like” is the idea that such planets might be habitable by Earth-like organisms, or that they might actually be inhabited. Here, I shall address two questions from the standpoint of planetary atmosphere evolution. First, what are the chances that habitable planets exist around other stars? And, second, if inhabited planets exist, what would be the best way to detect them?     

Subsurface electric fields of a grounded cable of finite length for both frequency and time domain

Summary The subsurface electric fields of a current-carrying cable are examined for both steady-state and transient situations. Closed form expressions are obtained for two of the electric field components, and a numerical integration is used to obtain the third component. Waveforms for a stepfunction current excitation are displayed. The results have possible application to pulsed downlink communication in mine rescue operations.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.