Techniques for Representation of Regional Clusters in Geographical In-formation Systems

This paper provides an overview of visualization techniques adapted for regional clusters presentation in Geographic Information Systems. Clusters are groups of companies and insti-tutions co-located in a specific geographic region and linked by interdependencies in providing a related group of products and services. The regional clusters can be visualized by projecting the data into two-dimensional space or using parallel coordinates. Cluster membership is usually represented by different colours or by dividing clusters into several panels of a grille display. Taking into consideration regional clusters requirements and the multilevel administrative division of the Romania’s territory, I used two cartograms: NUTS2- regions and NUTS3- counties, to illustrate the tools for regional clusters representation.Geographic Information Systems, Regional Clusters, Spatial Statistics, Geographic Data Visualisation

Community structure detection in the evolution of the United States airport network

This is the post-print version of the Article. Copyright © 2013 World Scientific PublishingThis paper investigates community structure in the US Airport Network as it evolved from 1990 to 2010 by looking at six bi-monthly intervals in 1990, 2000 and 2010, using data obtained from the Bureau of Transportation Statistics of the US Department of Transport. The data contained monthly records of origin-destination pairs of domestic airports and the number of passengers carried. The topological properties and the volume of people traveling are both studied in detail, revealing high heterogeneity in space and time. A recently developed community structure detection method, accounting for the spatial nature of these networks, is applied and reveals a picture of the communities within. The patterns of communities plotted for each bi-monthly interval reveal some interesting seasonal variations of passenger flows and airport clusters that do not occupy a single US region. The long-term evolution of the network between those years is explored and found to have consistently improved its stability. The more recent structure of the network (2010) is compared with migration patterns among the four US macro-regions (West, Midwest, Northeast and South) in order to identify possible relationships and the results highlight a clear overlap between US domestic air travel and migration

Spatial and multidimensional analysis of the Dutch housing market using the Kohonen Map and GIS

In this work the idea is to analyse general spatially identifiable housing market related data on Dutch districts (wijken) with the SOM (Kohonen Map) and a GIS. One of the authors has earlier carried out purely visual SOM analysis of that data, where patterns formed on a larger ‘map’ (the output matrix of the SOM) were used as a basis for classification of the Dutch housing market segments on a nationwide level. This way the SOM was used as a method for exploratory data analysis. Now we attempt a more rigorous method of determining the segmentation using a smaller ‘map’ size, in order to be able to export the SOM-output directly to a GIS-system to analyse it further. Two technical issues interest us: one, the robustness of the results – do the five basic housing market segments found in the earlier analysis prevail (we call these urban, urban periphery, pseudo-rural, traditional, and low-income segments); and two, which classes fit the real situation better and which worse, when using the RMSE for a measure of goodness? We also keep an eye on policy implications and aim at comparing our classifications with the ‘actual’ ones used in official discourse.

Measuring the Initial Mass Function of Low Mass Stars and Brown Dwarfs

I review efforts to determine the form and any lower limit to the initial mass function in the Galactic disk, using observations of low-mass stars and brown dwarfs in the field, young clusters and star forming regions. I focus on the methodologies that have been used and the uncertainties that exist due to observational limitations and to systematic uncertainties in calibrations and theoretical models. I conclude that whilst it is possible that the low-mass IMFs deduced from the field and most young clusters are similar, there are too many problems to be sure; there are examples of low-mass cluster IMFs that appear to be very discrepant and the IMFs for brown dwarfs in the field and young clusters have yet to be reconciled convincingly.Comment: From a series of lectures presented at the Evry-Schatzman school on Low-mass stars and the transition from stars to brown dwarfs, edited by C. Charbonnel, C. Reyle, M. Schultheis. To appear in the EAS Conference Series. 47p

Creative Thinking and Modelling for the Decision Support in Water Management

This paper reviews the state of art in knowledge and preferences elicitation techniques. The purpose of the study was to evaluate various cognitive mapping techniques in order to conclude with the identification of the optimal technique for the NetSyMod methodology. Network Analysis – Creative System Modelling (NetSyMod) methodology has been designed for the improvement of decision support systems (DSS) with respect to the environmental problems. In the paper the difference is made between experts and stakeholders knowledge and preference elicitation methods. The suggested technique is very similar to the Nominal Group Techniques (NGT) with the external representation of the analysed problem by means of the Hodgson Hexagons. The evolving methodology is undergoing tests within several EU-funded projects such as: ITAES, IISIM, NostrumDSS.Creative modelling, Cognitive mapping, Preference elicitation techniques, Decision support

The Observed Properties of High-Redshift Cluster Galaxies

We use the semi-analytic models of galaxy formation developed by Kauffmann, White \& Guiderdoni to generate predictions for the observed properties of cluster and group galaxies at redshifts between 0 and 0.6. We examine four sets of cosmological initial conditions: low-density CDM models with and without cosmological constant, a flat CDM model and a mixed dark matter model. These models were selected because they span a wide range in cluster formation epoch. The semi-analytic models that we employ are able to follow both the evolution of the dark matter component of clusters and the formation and evolution of the stellar populations of the cluster galaxies. We are thus able to generate model predictions that can be compared directly with the observational data. In the low-density CDM models, clusters form at high red- shift and accrete very little mass at recent times. Our models predict that essentially no evolution in the observed properties of clusters will have occurred by a redshift of 0.6, in direct contradiction with the data. In contrast, in the MDM model, both galaxies and clusters form extremely late. This model predicts evolution which appears to be too extreme to be in agreement with the observations. The flat CDM model, which is intermediate in structure formation epoch, is most successful. This model is able to account for the evolution of the blue fraction of rich clusters with redshift, the relationship between blue fraction and cluster richness at different epochs, and the changes in the distribution of the morphologies of cluster galaxies by a redshift of 0.4.Comment: Latex file, 12 pages, postscript figures on request, 99