GIS and optimisation:potential benefits for emergency facility location in humanitarian logistics

Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

The integration of multi-source data to improve the classification of remotely sensed images

The number of remote sensing platforms and sensors rises almost every year, yet much work on the interpretation of land cover is still carried out using either single images or images from the same source taken at different dates. Two questions could be asked of this proliferation of images: can the information contained in different scenes be used to improve the classification accuracy and, what is the best way to combine the different imagery? Two of these multiple image sources are MODIS on the Terra platform and ETM+ on board Landsat7, which are suitably complementary. Daily MODIS images with 36 spectral bands in 250-1000 m spatial resolution and seven spectral bands of ETM+ with 30m and 16 days spatial and temporal resolution respectively are available. In the UK, cloud cover may mean that only a few ETM+ scenes may be available for any particular year and these may not be at the time of year of most interest. The MODIS data may provide information on land cover over the growing season, such as harvest dates, that is not present in the ETM+ data. Therefore, the primary objective of this work is to develop a methodology for the integration of medium spatial resolution Landsat ETM+ image, with multi-temporal, multi-spectral, low-resolution MODIS \Terra images, with the aim of improving the classification of agricultural land. Additionally other data may also be incorporated such as field boundaries from existing maps. When classifying agricultural land cover of the type seen in the UK, where crops are largely sown in homogenous fields with clear and often mapped boundaries, the classification is greatly improved using the mapped polygons and utilising the classification of the polygon as a whole as an apriori probability in classifying each individual pixel using a Bayesian approach. When dealing with multiple images from different platforms and dates it is highly unlikely that the pixels will be exactly co-registered and these pixels will contain a mixture of different real world land covers. Similarly the different atmospheric conditions prevailing during the different days will mean that the same emission from the ground will give rise to different sensor reception. Therefore, a method is presented with a model of the instantaneous field of view and atmospheric effects to enable different remote sensed data sources to be integrated.

Remote sensing applied to land use and erosion hazard studies in Jamaica

The northern half of the parish of St. Catherine in Jamaica was selected as a test area to study, by means of remote sensing, the problems of soil erosion in a tropical environment. An initial study was carried out to determine whether eroded land within this environment could be successfully interpreted and mapped from the available 1: 25,000 scale aerial photographs. When satisfied that a sufficiently high percentage of the eroded land could be interpreted on the aerial photographs the main study was initiated. This involved interpreting the air photo cover of the study area for identifying and classifying land use and eroded land, and plotting the results on overlays on topographic base maps. These overlays were then composited with data on the soils and slopes of the study area. The areas of different soil type/slope/land use combinations were then measured, as was the area of eroded land for each of these combinations. This data was then analysed in two ways. The first way involved determining which of the combinations of soil type, slope and land use were most and least eroded and, on the basis of this, to draw up recommendations concerning future land use. The second analysis was aimed at determining which of the three factors, soil type, slope and land use, was most responsible for determining the rate of erosion. Although it was possible to show that slope was not very significant in determining the rate of erosion, it was much more difficult to separate the effects of land use and soil type. The results do, however, suggest that land use is more significant than soil type in determining the rate of erosion within the study area.

The application of remote sensing to water resources

Techniques are developed for the visual interpretation of drainage features from satellite imagery. The process of interpretation is formalised by the introduction of objective criteria. Problems of assessing the accuracy of maps are recognized, and a method is developed for quantifying the correctness of an interpretation, in which the more important features are given an appropriate weight. A study was made of imagery from a variety of landscapes in Britain and overseas, from which maps of drainage networks were drawn. The accuracy of the mapping was assessed in absolute terms, and also in relation to the geomorphic parameters used in hydrologic models. Results are presented relating the accuracy of interpretation to image quality, subjectivity and the effects of topography. It is concluded that the visual interpretation of satellite imagery gives maps of sufficient accuracy for the preliminary assessment of water resources, and for the estimation of geomorphic parameters. An examination is made of the use of remotely sensed data in hydrologic models. It is proposed that the spectral properties of a scene are holistic, and are therefore more efficient than conventional catchment characteristics. Key hydrologic parameters were identified, and were estimated from streamflow records. The correlation between hydrologic variables and spectral characteristics was examined, and regression models for streamflow were developed, based solely on spectral data. Regression models were also developed using conventional catchment characteristics, whose values were estimated using satellite imagery. It was concluded that models based primarily on variables derived from remotely sensed data give results which are as good as, or better than, models using conventional map data. The holistic properties of remotely sensed data are realised only in undeveloped areas. In developed areas an assessment of current land-use is a more useful indication of hydrologic response.

The application of remote sensing to the management of urban wildlife habitats

The project set out with two main aims. The first aim was to determine whether large scale multispectral aerial photography could be used to successfully survey and monitor urban wildlife habitats. The second objective was to investigate whether this data source could be used to predict population numbers of selected species expected to be found in a particular habitat type. Panchromatic, colour and colour infra-red, 1:2500 scale aerial photographs, taken in 1981 and 1984, were used. For the orderly extraction of information from the imagery, an urban wildlife habitat classification was devised. This was based on classifications already in use in urban environments by the Nature Conservancy Council. Pilot tests identified that the colour infra-red imagery provided the most accurate results about urban wildlife habitats in the study area of the Blackbrook Valley, Dudley. Both the 1981 and 1984 colour infra-red photographs were analysed and information was obtained about the type, extent and distribution of habitats. In order to investigate whether large scale aerial photographs could be used to predict likely animal population numbers in urban environments, it was decided to limit the investigation to the possible prediction of bird population numbers in Saltwells Local Nature Reserve. A good deal of research has already been completed into the development of models to predict breeding bird population numbers in woodland habitats. These models were analysed to determine whether they could be used successfully with data extracted from the aerial photographs. The projects concluded that 1:2500 scale colour infra-red photographs can provide very useful and very detailed information about the wildlife habitats in an urban area. Such imagery can also provide habitat area data to be used with population predictive models of woodland breeding birds. Using the aerial photographs, further investigations into the relationship between area of habitat and the breeding of individual bird species were inconclusive and need further research.

Representation of some class of time frequency distributions towards their determination through remote sensing techniques

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The politics of remote sensing with particular reference to Developing Countries

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Geometric spectral accuracy of airborne remote sensing

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From apartheid to unity: white capital and black power in the racial integration of South African football, 1976-1992

This article analyses the complex process that deracialised and democratised South African football between the early 1970s and 1990s. Based mainly on archival documents, it argues that growing isolation from world sport, exemplified by South Africa's expulsion from the Olympic movement in 1970 and FIFA in 1976, and the reinvigoration of the liberation struggle with the Soweto youth uprising triggered a process of gradual desegregation in the South African professional game. While Pretoria viewed such changes as a potential bulwark against rising black militancy, white football and big business had their own reasons for eventually supporting racial integration, as seen in the founding of the National Soccer League. As negotiations for a new democratic South Africa began in earnest between the African National Congress (ANC) and the National Party (NP) in the latter half of the 1980s, transformations in football and politics paralleled and informed each other. Previously antagonistic football associations began a series of 'unity talks' between 1985 and 1986 that eventually culminated in the formation of a single, non-racial South African Football Association in December 1991, just a few days before the Convention for a Democratic South Africa (CODESA) opened the process of writing a new post-apartheid constitution. Finally, three decades of isolation came to an end as FIFA welcomed South Africa back into world football in 1992 - a powerful example of the seemingly boundless potential of a liberated and united South Africa ahead of the first democratic elections in 1994.

Meta-analytic model comparisons of surface- and deep-level relational diversity effects on social integration and individual effectiveness

While diversity might give an organization a competitive advantage, individuals have a tendency to prefer homogenous group settings. Prior research suggests that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, prior empirical findings tend to be weak and inconsistent, and it remains unclear when, how and to what extent such differences affect group members’ social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness. To address these issues the current study conducted a meta-analysis and integrated the empirical results of 129 studies. For demographic diversity attributes (such as gender, ethnicity, race, nationality, age, functional background, and tenure) the findings support the idea that demographic dissimilarity undermines individual member performance via lower levels of social integration. These negative effects were more pronounced in pseudo teams – i.e. work groups in which group members pursue individual goals, work on individual tasks, and are rewarded for their individual performance. These negative effects were however non-existent in real teams - i.e. work groups in which groups members pursue group goals, work on interdependent tasks, and are rewarded (at least partially) based on their work group’s performance. In contrast, for underlying psychological diversity attributes (such as attitudes, personality, and values), the relationship between dissimilarity and social integration was more negative in real teams than in pseudo teams, which in return translated into even lower individual performance. At the same time however, differences in underlying psychological attributes had an even stronger positive effect on dissimilar group member’s individual performance, when the negative effects of social integration were controlled for. This implies that managers should implement real work groups to overcome the negative effects of group member’s demographic dissimilarity. To harness the positive effects of group members’ dissimilarity on underlying psychological attributes, they need to make sure that dissimilar group members become socially integrated.

The Great Slump of 2008–9 and Ukraine's integration with the European Union

For a number of years following the Orange revolution of 2004, Ukraine aspired to join the European Union. Although full integration was never a short-term prospect, European integration, through the Association Agreement and the Deep and Comprehensive Free Trade Area, offers considerable benefits to Ukraine. However, the country was severely affected by the Great Slump of 2008–9 in the global economy, and this profoundly negative experience has shaped Ukrainian domestic and foreign policy in the subsequent period, putting paid to aspirations to EU membership and influencing the Ukrainian government's decision to seek a closer relationship with Russia immediately following the presidential election of 2010. Nevertheless, closer relations with Russia should not adversely affect Ukraine's efforts at EU integration.

GIS linked environmental process models

In recent years there has been a great effort to combine the technologies and techniques of GIS and process models. This project examines the issues of linking a standard current generation 2½d GIS with several existing model codes. The focus for the project has been the Shropshire Groundwater Scheme, which is being developed to augment flow in the River Severn during drought periods by pumping water from the Shropshire Aquifer. Previous authors have demonstrated that under certain circumstances pumping could reduce the soil moisture available for crops. This project follows earlier work at Aston in which the effects of drawdown were delineated and quantified through the development of a software package that implemented a technique which brought together the significant spatially varying parameters. This technique is repeated here, but using a standard GIS called GRASS. The GIS proved adequate for the task and the added functionality provided by the general purpose GIS - the data capture, manipulation and visualisation facilities - were of great benefit. The bulk of the project is concerned with examining the issues of the linkage of GIS and environmental process models. To this end a groundwater model (Modflow) and a soil moisture model (SWMS2D) were linked to the GIS and a crop model was implemented within the GIS. A loose-linked approach was adopted and secondary and surrogate data were used wherever possible. The implications of which relate to; justification of a loose-linked versus a closely integrated approach; how, technically, to achieve the linkage; how to reconcile the different data models used by the GIS and the process models; control of the movement of data between models of environmental subsystems, to model the total system; the advantages and disadvantages of using a current generation GIS as a medium for linking environmental process models; generation of input data, including the use of geostatistic, stochastic simulation, remote sensing, regression equations and mapped data; issues of accuracy, uncertainty and simply providing adequate data for the complex models; how such a modelling system fits into an organisational framework.