Devolution and the political representation of business interests in the UK

The devolution of political power in Scotland, Wales and Northern Ireland and the developing regional agenda in England are widely read as a significant reconfiguration of the institutions and scales of economic governance. The process is furthest developed in Scotland while Wales and Northern Ireland, in their own distinct ways, provide intermediate cases. Devolution is least developed in England where regional political identities are generally weak and the historical legacy of regional institutions is limited. Within the overall context of devolution government policy has continued to emphasize partnership forms of. governance. Accordingly, the political representation of business interests has a particular salience in the new arrangements. This paper reports on findings from a study designed to examine the relationship between devolution and changes in the political representation of business interests in the territories and regions of the UK. It highlights a number of changes in the nature and extent of business representation. While some of these are significant the evidence suggests that they fail to mark a fundamental shift in the institutional foundation for sub-national business interest representation in the UK. Indeed the political geography of business representation remains dominated by an overarching centralism that is likely to provide a significant check on the further devolution of political power and democratic authority. (c) 2004 Elsevier Ltd. All rights reserved.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Upwind solution of singular differential equations arising from steady channel flows

We study ordinary nonlinear singular differential equations which arise from steady conservation laws with source terms. An example of steady conservation laws which leads to those scalar equations is the Saint–Venant equations. The numerical solution of these scalar equations is sought by using the ideas of upwinding and discretisation of source terms. Both the Engquist–Osher scheme and the Roe scheme are used with different strategies for discretising the source terms.