Using GIS to Explore the Technical and Social Aspects of Site Selection for Radioactive Waste Disposal Facilities

This working paper reviews the current situation regarding radioactive waste disposal in the UK and questions the pursuance of a purely engineering approach to gaining public support. Past histories concerning the siting of nuclear industry facilities; power stations and latterly, waste repositories, are briefly discussed and used to demonstrate that more attention needs to be paid to the geographical and social science if current proposlas for a rock laboratory, and ultimately and operational repository, at Longlands Farm near Sellafield are to succeed. The usefulness of Geographical Information Systems (GIS) and associated spatial information technologies are highlighted. Suggestions are made as to how these may be made available for public use via the Internet in adopting a more open approach to public information, consultation and participation

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

BARD: Better Automated Redistricting

BARD is the first (and at time of writing, only) open source software package for general redistricting and redistricting analysis. BARD provides methods to create, display, compare, edit, automatically refine, evaluate, and profile political districting plans. BARD aims to provide a framework for scientific analysis of redistricting plans and to facilitate wider public participation in the creation of new plans. BARD facilitates map creation and refinement through command-line, graphical user interface, and automatic methods. Since redistricting is a computationally complex partitioning problem not amenable to an exact optimization solution, BARD implements a variety of selectable metaheuristics that can be used to refine existing or randomly-generated redistricting plans based on user-determined criteria. Furthermore, BARD supports automated generation of redistricting plans and profiling of plans by assigning different weights to various criteria, such as district compactness or equality of population. This functionality permits exploration of trade-offs among criteria. The intent of a redistricting authority may be explored by examining these trade-offs and inferring which reasonably observable plans were not adopted. Redistricting is a computationally-intensive problem for even modest-sized states. Performance is thus an important consideration in BARD's design and implementation. The program implements performance enhancements such as evaluation caching, explicit memory management, and distributed computing across snow clusters.

Exploring multiple viewshed analysis using terrain features and optimisation techniques

The calculation of viewsheds is a routine operation in geographic information systems and is used in a wide range of applications. Many of these involve the siting of features, such as radio masts, which are part of a network and yet the selection of sites is normally done separately for each feature. The selection of a series of locations which collectively maximise the visual coverage of an area is a combinatorial problem and as such cannot be directly solved except for trivial cases. In this paper, two strategies for tackling this problem are explored. The first is to restrict the search to key topographic points in the landscape such as peaks, pits and passes. The second is to use heuristics which have been applied to other maximal coverage spatial problems such as location-allocation. The results show that the use of these two strategies results in a reduction of the computing time necessary by two orders of magnitude, but at the cost of a loss of 10% in the area viewed. Three different heuristics were used, of which Simulated Annealing produced the best results. However the improvement over a much simpler fast-descent swap heuristic was very slight, but at the cost of greatly increased running times. © 2004 Elsevier Ltd. All rights reserved