From Beats to Tracts

In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.

Environmental factors and incidence of dengue fever and dengue haemorrhagic fever in an urban area, Southern Thailand

SUMMARYUsing the enumeration district (ED) block level this study looked at the incidence of dengue fever and dengue haemorrhagic fever (DF/DHF) within the Songkhla municipality in Thailand. Each of the 146 blocks in this area were considered as study units and surveyed for their environmental characteristics. A total of 287 cases of DH/DHF occurring in the year 1998 were selected for this study and the location of their homes mapped. Clustering analysis showed point clustering of the homes (P<0·0001) which was probably due to high density habitation, without any actual prevalence of case clustering. There was no evidence of clustering of the ED blocks with an incidence of DF/DHF (P=0·32). DF/DHF incidence for each block was strongly associated with the percentages of shop-houses, brick-made houses and houses with poor garbage disposal (all P<0·01). DF/DHF control should be emphasized for the areas which have a predominance of these housing types.

The Estimation of Population Microdata by Using Data from Small Area Statistics and Samples of Anonymised Records

Census data can be represented both as lists and as tabulations of household/individual attributes. List representation of Census data offers greater flexibility, as the exploration of interrelationships between population characteristics is limited only by the quality and scope of the data collected. Unfortunately, the released lists of household/individual attributes (Samples of Anonymised Records, SARs) are spatially referenced only to areas (single or merged districts) with populations of 120 000 or more, whereas released tabulations are available for units as small as single enumeration districts (Small Area Statistics, SAS). Intuitively, it should be possible to derive list-based estimates of enumeration district populations by combining information contained in the SAR and the SAS. In this paper we explore the range of solutions that could be adapted to this problem which, ultimately, is presented as a complex combinatorial optimisation problem. Various techniques of combinatorial optimisation are tested, and preliminary results from the best performing algorithm are evaluated. Through this process, the lack of suitable test statistics for the comparison of observed and expected tabulations of population data is highlighted.

Constructing an Urban Deprivation Index: A Way of Meeting the Need for Flexibility

Key issues in constructing an urban deprivation index are discussed, with special reference to the need for flexibility. Governments use such an index for many purposes and for policies targeted at different spatial scales. The technical decisions and the criteria for the selection of indicators are discussed. A single index is rejected in favour of a matrix of results which captures the complex geography of deprivation. The matrix of districts includes measures of the degree of deprivation, its spatial extent, its intensity, and the spatial distribution of deprivation at the enumeration district scale. The profiles of various districts are discussed to illustrate the use of the matrix.

The Mapping of Small-Area Census Data—A Consideration of the Role of Enumeration District Boundaries

Census enumeration districts (EDs) are not ‘natural’ areal units, and a strong presumption exists against their use for cartographic or analytical purposes. There is, however, some reason to suppose that their boundaries may coincide with divisions in the underlying social geography of an area, and that they therefore contain information which should not be lost in processing. A study of Newcastle upon Tyne EDs shows that ED boundaries do not, in fact, mark the boundaries of distinct areas. The presumption against the use of ED boundaries for cartographic representation is reinforced.