Politicization of research and the relevance of geography: some experiences and reflections for an ongoing debate

In this paper we address the revival of interest in recent years in the relevance of geographical research and highlight problems of politicization faced by researchers through cases of policy-oriented research in the UK and Belgium. We argue that geographers should be aware of the possibilities and constraints for critical engagement in the context of policy-oriented research. We identify at least two important opportunities for researchers to avoid clientelistic relationships with contractors and enhance their political relevance. First, researchers can stick to letter of the contract and maintain academic standards while at the same time interpreting their tasks according to their own ethical and political judgements. Second, relevance can be increased by forming alliances within and beyond the formal hierarchies of the state and the academy. The identification and utilization of these 'spaces of relevance' can be seen as the first step towards an approach that strategically seeks a balance between societal engagement on the one hand and contractual obligations, policy relevance and academic standards on the other.     

Changes in Vascular Plant Biodiversity in the Netherlands in the 20th Century Explained by their Climatic and other Environmental Characteristics

In the Netherlands nation-wide databases are available with about 10 million records of occurrences of vascular plant species in the 20th century on a scale of approximately 1 km². These data were analysed with a view to identifying relationships between changes in botanical biodiversity and climatic and other environmental factors. Prior to analysis the data were corrected for several major forms of survey bias. The records were broken down into three periods: 1902–1949, 1975–1984 and 1985–1999. Using multiple regression analysis, differences between successive periods were related to plant functional characteristics as explanatory variables. Between the periods 1902–1949 and 1975–1984 there were small but significant increases in the presence of both thermophilic (‘warm’) and psychrophilic (‘cold’) species. However, in the final decades of the 20th century there was a marked increase in thermophilic species only, coinciding with the marked increase in ambient temperature observed during this period, evidence at least of a rapid response of Dutch flora to climate change. Urbanisation was also examined as an alternative explanation for the increase in thermophilic plant species and was found to explain only 50% of the increased presence of such species in the final decades of the 20th century. Besides temperature-related effects, the most important change during the 20th century was a strong decline in oligotrophic and a marked increase in eutrophic plant species.     

Socioeconomic segregation in European capital cities. Increasing separation between poor and rich

Socioeconomic inequality is on the rise in major European cities, as are concerns over it, since it is seen as a threat to social cohesion and stability. Surprisingly, relatively little is known about the spatial dimensions of rising socioeconomic inequality. This paper builds on a study of socioeconomic segregation in 12 European cities: Amsterdam, Athens, Budapest, London, Madrid, Oslo, Prague, Riga, Stockholm, Tallinn, Vienna, and Vilnius. Data used derive from national censuses and registers for 2001 and 2011. The main conclusion is that socioeconomic segregation has increased. This paper develops a rigorous multifactor approach to understand segregation and links it to four underlying, partially overlapping, structural factors: social inequalities, globalization and economic restructuring, welfare regimes, and housing systems. Taking into account contextual factors resulted in a better understanding of actual segregation levels, while introducing time lags between structural factors and segregation outcomes will likely further improve the theoretical model.     

Spectral mixture analysis for mapping land degradation in semi-arid areas

Spectral mixture analysis (SMA) is an image-processing technique used for the analysis of airborne hyperspectral remote-sensing data which consist of a large number of spectral bands, typically over 100. In this paper the possibilities are examined of using SMA for the analysis of Landsat Thematic Mapper satellite data with only six bands in the visible to shortwave-infrared wavelength. We use data from a semi-arid area in the Sanmatenga province of Burkina Faso, an area known to experience land-degradation problems. In SMA, we assume that pixels in an image consist of one or more homogeneous (uniform in character) or pure surfaces, the so called end-members. The end-members were derived from the image data on the basis of specific image characteristics. Field data was collected to describe the characteristics of these end-members in terms of land cover, soil and degradation phenomena. The end-members derived from the image analysis, although statistically pure in terms of image spectral characteristics, prove to be mixtures at a field scale. This lack of purity is explained by the nature of semi-arid areas which is more heterogeneous than that of most other areas. The SMA yielded cover percentages for the end-members from which an unsupervised classification was made. Comparison of the classification with the results of SMA shows that the latter provides information on the amount and spatial distribution of land characteristics such as land degradation.     

Bed load transport on the shoreface by currents and waves

Tide-driven bed load transport is an important portion of the net annual sediment transport rate in many shoreface and shelf environments. However, bed load transport under waves cannot be measured in the field and bed load transport by currents without waves is barely measurable, even in spring tidal conditions. There is, consequently, a strong lack of field data and validated models. The present field site was on the shoreface and inner shelf at 2 to 8.5 km offshore the central Dutch coast (far outside the surfzone), where tidal currents flow parallel to the coast. Bed load transports were carefully measured with a calibrated sampler in spring tidal conditions without waves at a water depth of 13–18 m with fine and medium sands. The near-bed flow was measured over nearly a year and used for integration to annual transport rates. An empirical bed load model was derived, which predicts bed load transports that are a factor of > 5 smaller than predicted by existing models. However, they agree with laboratory data of sand and gravel transport in currents near incipient motion. The damped transport rates may have been caused by cohesion of sediment or turbulence damping due to mud or biological activity. The annual bed load transport rate was calculated using a probability density function (pdf) derived from the near-bed current and orbital velocity data which represented the current and wave climate well when compared to 30 years of data from a nearby wave station. The effect of wave stirring was included in the transport calculations. The net bed load transport rate is a few m²/year. This is much less than predicted in an earlier model study, which is partly due to different bed load models but also due to the difference in velocity pdf. The annual transport rate is very sensitive to the probability of the largest current velocities.     

Using modular 3D digital earth applications based on point clouds for the study of complex sites

This article discusses the use of 3D technologies in digital earth applications (DEAs) to study complex sites. These are large areas containing objects with heterogeneous shapes and semantic information. The study proposes that DEAs should be modular, have multi-tier architectures, and be developed as Free and Open Source Software if possible. In DEAs requiring high reliability in the 3D measurements, point clouds are proposed as basis for the 3D Digital digital earth representation. For the development of DEAs, we propose to follow a workflow with four components: data acquisition and processing, data management, data analysis and data visualization. For every component, technological challenges of using 3D technologies are identified and solutions applied for a case study are presented. The case study is a modular 3D DEA developed for the archaeological project Mapping the Via Appia. The 3D DEA allows archaeologists to virtually analyze a complex study area.     

LAND USE SCANNER: An integrated GIS based model for long term projections of land use in urban and rural areas

This paper describes the structure of the LAND USE SCANNER model, a GIS based model developed to generate spatial forecasts for various types of land use for a large number of grids. The model basically allocates land according to bid prices for various types of land use. The possibility of government intervention in land use is taken into account among others by adding aggregate constraints. The model includes all relevant land use types such as residential, industrial, agricultural, natural areas and water. The model is driven by sectoral models providing forecasts of aggregate land use in various land use categories. An application of the first version of the model is given for the Netherlands with some 200,000 grid cells. Further developments and refinements of the model are planned for the near future. Received: 18 February 1998/Accepted: 29 September 1998