Detailed Geographic Data Research Articles

Land-use Model based on Observed Land Price and Detailed Geographical Data

Land-use Model based on Observed Land Price and Detailed Geographical Data

A Comparative Evaluation of Approaches to Urban Crime Pattern Analysis

The increased availability of digital data and the increased scrutiny of public expenditure are opening new opportunities for detailed spatial analysis of social behaviour and policy initiatives to target resources where they are most needed. Two such policy areas in which the use of GIS combined with spatial analysis tools has made significant progress are health and police services, which are at the top of the political agenda due to increasing 'demand' and spiralling costs. Against this background, this paper presents the results of a collaborative research project carried out in Sheffield on the use of GIS for crime pattern analysis. The research described is significant in a number of respects: it is based on high-quality detailed crime data and geographical data for the whole of Sheffield; it compares two different methodologies for crime pattern analysis, one developed specifically for crime, the other for health research; and it demonstrates the policy value of this transfer of methodologies across disciplines.

A Facility Location Analysis Considering Spatial Patterns of Distributed Users

Facility location and area-marketing analysis by Geographical Information System(GIS) frequently require distance from facility to user and aggregated user population in areas of concem. This is usually based on estimating the user distribution from the aggregated population data for each area consisting of unit areas which is assumed that the user distributes evenly. However, for the spread of much more detailed geographical data available for certain urban areas, we do not estimate only the user distribution incorporating aggregated data approximately but also estimate it as points data of individual buildings in the area. In this paper we confirm the effectiveness of this latest approach by comparing its result to that produced by the convertional method of data aggregation.