Visualization of uncertainty and analysis of geographical data

A team of five worked on this challenge to identify a possible criminal strucutre within the Flitter social network. Initially we worked on the problem individually, deliberately not sharing any data, results or conclusions. This maximised the chances of spotting any blunders, unjustified assumptions or inferences and allowed us to triangulate any common conclusions. After an agreed period we shared our results demonstrating the visualization applications we had built and the reasoning behind our conclusions. This sharing of assumptions encouraged us to incorporate uncertainty in our visualization approaches as it became clear that there was a number of possible interpretations of the rules and assumptions governing the challenge. This summary of the work emphasises one of those applications detailing the geographic analysis and uncertainty handling of the network data. ©2009 IEEE

Towards a geographical information system for European economic community regional data

The study proposes the development of a geographical information system for European Economic Community (EEC) regional data. The features of geographical information systems and some related issues are discussed. An outline is given of likely user requirements and attempts by various European organisations to make provision for these. The practical work involves the application of three selected data analysis, manipulation and mapping packages, and operating system facilities to tasks which users of the data might wish to undertake. For this purpose, EEC "Level II" region boundaries were digitised, and selected socio-economic attributes for 1977 organised in disc files. Ten choropleth maps of the Level II regions (eight original variabels and two composite variables) are displayed. Although there is a lack of certain, more specialised features in the software system used, it is considered that there exists the imprtant basic requirements of data analysis, manipulation and mapping in package form, upon which to build the proposed geographical information system

From buildings to cities: techniques for the multi-scale analysis of urban form and function

The built environment is a significant factor in many urban processes, yet direct measures of built form are seldom used in geographical studies. Representation and analysis of urban form and function could provide new insights and improve the evidence base for research. So far progress has been slow due to limited data availability, computational demands, and a lack of methods to integrate built environment data with aggregate geographical analysis. Spatial data and computational improvements are overcoming some of these problems, but there remains a need for techniques to process and aggregate urban form data. Here we develop a Built Environment Model of urban function and dwelling type classifications for Greater London, based on detailed topographic and address-based data (sourced from Ordnance Survey MasterMap). The multi-scale approach allows the Built Environment Model to be viewed at fine-scales for local planning contexts, and at city-wide scales for aggregate geographical analysis, allowing an improved understanding of urban processes. This flexibility is illustrated in the two examples, that of urban function and residential type analysis, where both local-scale urban clustering and city-wide trends in density and agglomeration are shown. While we demonstrate the multi-scale Built Environment Model to be a viable approach, a number of accuracy issues are identified, including the limitations of 2D data, inaccuracies in commercial function data and problems with temporal attribution. These limitations currently restrict the more advanced applications of the Built Environment Model

Anatomy of the Third-Party Web Tracking Ecosystem

The presence of third-party tracking on websites has become customary. However, our understanding of the third-party ecosystem is still very rudimentary. We examine third-party trackers from a geographical perspective, observing the third-party tracking ecosystem from 29 countries across the globe. When examining the data by region (North America, South America, Europe, East Asia, Middle East, and Oceania), we observe significant geographical variation between regions and countries within regions. We find trackers that focus on specific regions and countries, and some that are hosted in countries outside their expected target tracking domain. Given the differences in regulatory regimes between jurisdictions, we believe this analysis sheds light on the geographical properties of this ecosystem and on the problems that these may pose to our ability to track and manage the different data silos that now store personal data about us all

Microeconomic foundations of geographical variations in labour productivity

This paper initially presents an exploratory spatial data analysis which indicates the presence of small-scale geographical variations in levels and standard deviations of labour productivity across England and Wales in 2005. We identify the presence of spatial autocorrelation for both measures. This finding motivates a subsequent review and extension of theories which suggest the possible presence of small-scale geographical patterns of labour productivity.Labour productivity; standard deviation; districts and local authorities; geographical autocorrelation

The verification of LANDSAT data in the geographical analysis of wetlands in west Tennessee

The reliability of LANDSAT imagery as a medium for identifying, delimiting, monitoring, measuring, and mapping wetlands in west Tennessee was assessed to verify LANDSAT as an accurate, efficient cartographic tool that could be employed by a wide range of users to study wetland dynamics. The verification procedure was based on the visual interpretation and measurement of multispectral imagery. The accuracy testing procedure was predicated on surrogate ground truth data gleaned from medium altitude imagery of the wetlands. Fourteen sites or case study areas were selected from individual 9 x 9 inch photo frames on the aerial photography. These sites were then used as data control calibration parameters for assessing the cartography accuracy of the LANDSAT imagery. An analysis of results obtained from the verification tests indicated that 1:250,000 scale LANDSAT data were the most reliable scale of imagery for visually mapping and measuring wetlands using the area grid technique. The mean areal percentage of accuracy was 93.54 percent (real) and 96.93 percent (absolute). As a test of accuracy, the LANDSAT 1:250,000 scale overall wetland measurements were compared with an area cell mensuration of the swamplands from 1:130,000 scale color infrared U-2 aircraft imagery. The comparative totals substantiated the results from the LANDSAT verification procedure

The verification of LANDSAT data in the geographical analysis of wetlands in western Tennessee

There are no author-identified significant results in this report

Global late Quaternary megafauna extinctions linked to humans, not climate change

The late Quaternary megafauna extinction was a severe global-scale event. Two factors, climate change and modern humans, have received broad support as the primary drivers, but their absolute and relative importance remains controversial. To date, focus has been on the extinction chronology of individual or small groups of species, specific geographical regions or macroscale studies at very coarse geographical and taxonomic resolution, limiting the possibility of adequately testing the proposed hypotheses. We present, to our knowledge, the first global analysis of this extinction based on comprehensive country-level data on the geographical distribution of all large mammal species (more than or equal to 10 kg) that have gone globally or continentally extinct between the beginning of the Last Interglacial at 132 000 years BP and the late Holocene 1000 years BP, testing the relative roles played by glacial–interglacial climate change and humans. We show that the severity of extinction is strongly tied to hominin palaeobiogeography, with at most a weak, Eurasia-specific link to climate change. This first species-level macroscale analysis at relatively high geographical resolution provides strong support for modern humans as the primary driver of the worldwide megafauna losses during the late Quaternary