Geocomputation, Geodemographics and Resource Allocation for Local Policing

The field of geodemographics is one of the most fertile applications areas of geocomputation research. Geodemographic profiles of the characteristics of individuals and small areas are pivotal to tactical and strategic resource management in many areas of business, and are becoming similarly central to efficient and effective deployment of resources by public services. In this context, this paper describes research that has been developed in partnership with the Devon and Cornwall Constabulary and Institute of Criminal Justice Studies (ICJS) at the University of Portsmouth to assess the potential use of geodemographics as a policing tool. Crime, the fear of crime and the efficacy of public services are issues that have moved to the top of the UK political agenda and have long been matters of serious public concern. This paper considers the ways in which police forces might use geodemographics to better deploy resources at a variety of spatial scales in England and Wales.     

The frequency of winter Chinooks in Alberta

A study was made of winter temperatures to determine the frequency of chinook days in Alberta. The resulting pattern shows a maximum frequency along a line just east of the front range of the mountains, with the frequency decreasing slowly eastward. But a careful analysis of the Calgary‐Red Deer‐Drumheller triangle shows that the frequency is influenced by local topography and that the warm air at times overrides a pool of cold air in a valley to appear at high elevations to the east.     

Towards Real‐Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end, this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.     

A geocomputational analysis of Twitter activity around different world cities

The penetration and use of social media services differs from city to city. This paper is aimed to provide a comparison of the use of Twitter between different cities of the world. We present a temporal analysis of activity on Twitter in 15 cities. Our study consists of two parts: First, we created temporal graphs of the activity in the 15 cities, through which hours of high and low activity could be identified. Second, we created heat map visualizations of the Twitter activities during the period of 19 September 2012–25 September 2013. The heat map visualizations make the periods of intense and sparse activity apparent and provide a snapshot of the activity during the whole year.     

A Test Environment for Location-Based Services Applications

Location‐Based Services (LBS) are the delivery of information to mobile devices customised to location and context of the user. Some research has focused on data content, while other studies have emphasised the role of multimedia communication. However, very few objective tests have been carried out concerning usage and behaviour. In this paper, a conceptual model and a LBS test environment are presented which aim to study the behaviour and interaction between environments, individuals and mobile devices. The test environment was created, for this purpose, with three main components: urban VR models that allow individuals to ‘walk around’ at street level, a mobile device as information source which simulates LBS applications, and software for recording participant actions and reactions within the test environment. Multi‐source data were collected regarding movement tracking, information accessed through mobile device and participant observations using a combination of automated and semi‐automated methods. A case study on pedestrian wayfinding in urban settings is presented. This illustrates how the test environment can be used for LBS applications and how the data collected can be analysed. The research presented in this paper provides a novel approach in studying and understanding the interaction between environments, individuals and mobile devices.     

Peat extraction, conservation and the rural economy in Northern Ireland

Northern Ireland has a tradition of peat cutting; 78 per cent by area of remaining lowland bogs and 46 per cent of blanket bogs have been cut in the past. Since the early 1980s, machine peat extraction for fuel and horticulture has increased, against a background of changing economic support for agriculture, high rural unemployment and agricultural underemployment. Cutting fuel peat can reduce household fuel costs and some peat fuel is sold to gain income. Horticultural peat is cut mainly for sale. Expansion of machine extraction, with possible environmental impacts, occurred as interest in peatland conservation increased. Potential conflict arises between local economic needs and conservation. Machine cutting for fuel is widespread, but affects only 2.6 per cent of the blanket peat area; horticultural extraction is more localized and is only one-fifth of the extent of fuel extraction. Altitude, distance from roads, land ownership and rights, turbary, religious affiliation, local economic needs and the role of government departments all contribute to explaining the distribution and extent of extraction.     

Variation Of Urban Momentum Roughness Length With Land Use In The Upwind Source Area,As Observed in Two U.K. Cities

The possibility of obtaining urban roughness length from satellite-derived maps of land cover is explored, using turbulence measurements taken above the urban canopy. The upwind land cover is identified using a source-area model. Firstly, from four sets of measurements taken in Birmingham (U.K.), it is shown that in an area mainly split between the land-cover types urban and suburban, suburban cover in the upwind source area is the more important contributor to increasing measured roughness length. A smaller dataset obtained in a second U.K. city (Salford, Greater Manchester) shows a similar result. A roughness-length aggregation model is also applied to the data from both sites. This assigns values of roughness length to each of the land-cover classifications and uses the source-area model to predict the resultant roughness length based on the wind properties. The results from this are shown to agree with the earlier findings.The British Crowns right to retain a non-exclusive royalty-free license in and to any copyright is acknowledged     

The stability of geodemographic cluster assignments over an intercensal period

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.