The 2010 Hans Cloos lecture : the contribution of urban geology to the development, regeneration and conservation of cities

Urban geology began to develop in the 1950s, particularly in California in relation to land-use planning, and led to Robert Legget publishing his seminal book “Cities and geology” in 1973. Urban geology has now become an important part of engineering geology. Research and practice has seen the evolution from single theme spatial datasets to multi-theme and multi-dimensional outputs for a wide range of users. In parallel to the development of these new outputs to aid urban development, regeneration and conservation, has been the growing recognition that city authorities need access to extensive databases of geo-information that are maintained in the long-term and renewed regularly. A further key advance has been the recognition that, in the urban environment, knowledge and understanding of the geology need to be integrated with those of other environmental topics (for example, biodiversity) and, increasingly, with the research of social scientists, economists and others. Despite these advances, it is suggested that the value of urban geology is not fully recognised by those charged with the management and improvement of the world’s cities. This may be because engineering geologists have failed to adequately demonstrate the benefits of urban geological applications in terms of cost and environmental improvement, have not communicated these benefits well enough and have not clearly shown the long-term contribution of geo-information to urban sustainability. Within this context future actions to improve the situation are proposed

Predictive ranking: a novel page ranking approach by estimating the web structure

Conference paperPageRank (PR) is one of the most popular ways to rank web pages. However, as the Web continues to grow in volume, it is becoming more and more difficult to crawl all the available pages. As a result, the page ranks computed by PR are only based on a subset of the whole Web. This produces inaccurate outcome because of the inherent incomplete information (dangling pages) that exist in the calculation. To overcome this incompleteness, we propose a new variant of the PageRank algorithm called, Predictive Ranking (PreR), in which different classes of dangling pages are analyzed individually so that the link structure can be predicted more accurately. We detail our proposed steps. Furthermore, experimental results show that this algorithm achieves encouraging results when compared with previous methods.Re-search Grants Councils of the HKSAR, China (CUHK4205/04E and CUHK4351/02E