Understanding the socio-economic distribution of multiple deprivation: An application of self-organising maps

In this paper we seek to contribute to recent efforts to develop and implement multi-dimensional approaches to social exclusion by applying self-organising maps (SOMs) to a set of material deprivation indicators from the Irish component of EU-SILC. The first stage of our analysis involves the identification of sixteen clusters that confirm the multi-dimensional nature of deprivation in contemporary Ireland and the limitations of focusing solely on income. In going beyond this mapping stage, we consider both patterns of socio-economic differentiation in relation to cluster membership and the extent to which such membership contributes to our understanding of economic stress. Our analysis makes clear the continuing importance of traditional forms of stratification relating to factors such as income, social class and housing tenure in accounting for patterns of multiple deprivation. However, it also confirms the role of acute life events and life cycle and location influences. Most importantly, it demonstrates that conclusions relating to the relative impact of different kinds of socio-economic influences are highly dependent on the form of deprivation being considered. Our analysis suggests that debates relating to the extent to which poverty and social exclusion have become individualized should take particular care to distinguish between different kinds of outcomes. Further analysis demonstrates that the SOM approach is considerably more successful than a comparable latent class analysis in identifying those exposed to subjective economic stress. (C) 2010 International Sociological Association Research Committee 28 on Social Stratification and Mobility. Published by Elsevier Ltd. All rights reserved.

Mapping patterns of multiple deprivation using self-organising maps: An application to EU-SILC data for Ireland

The development of conceptual frameworks for the analysis of social exclusion has somewhat out-stripped related methodological developments. This paper seeks to contribute to filling this gap through the application of self-organising maps (SOMs) to the analysis of a detailed set of material deprivation indicators relating to the Irish case. The SOM approach allows us to offer a differentiated and interpretable picture of the structure of multiple deprivation in contemporary Ireland. Employing this approach, we identify 16 clusters characterised by distinct profiles across 42 deprivation indicators. Exploratory analyses demonstrate that, controlling for equivalised household income, SOM cluster membership adds substantially to our ability to predict subjective economic stress. Moreover, in comparison with an analogous latent class approach, the SOM analysis offers considerable additional discriminatory power in relation to individuals' experience of their economic circumstances. The results suggest that the SOM approach could prove a valuable addition to a 'methodological platform' for analysing the shape and form of social exclusion. (c) 2009 Elsevier Inc. All rights reserved.

Forensic Geomorphology

Geomorphology plays a critical role in two areas of geoforensics: searching the land for surface or buried objects and sampling or imaging rural scenes of crime and control locations as evidence. Most of the associated geoscience disciplines have substantial bodies of work dedicated to their relevance in forensic investigations, yet geomorphology (specifically landforms, their mapping and evolution, soils and relationship to geology and biogeography) have had no such exposure. This is strange considering how fundamental to legal enquiries the location of a crime and its evolution are, as this article will demonstrate. This work aims to redress the balance by showing how geomorphology is featured in one of the earliest works on forensic science methods, and has continued to play a role in the sociology, archaeology, criminalistics and geoforensics of crime. The application geomorphology has in military/humanitarian geography and environmental/engineering forensics is briefly discussed as these are also regularly reviewed in courts of law

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.

Hidrogeomorfologia e sustentabilidade de recursos hídricos subterrâneos

A água subterrânea de rochas duras é uma fonte importante para fins domésticos, industriais e agrícolas e mesmo para o consumo humano. A geologia, a tectónica, a geomorfologia e as características hidrológicas controlam o fluxo, ocorrência e armazenamento das águas subterrâneas. A disponibilidade da água subterrânea no meio geológico está totalmente dependente das áreas de recarga e de descarga numa determinada bacia. A precipitação é a principal fonte de recarga em aquíferos descontínuos, enquanto que a descarga depende dos declives do terreno e dos gradientes do nível hidrostático e ainda das condições hidrogeológicas do solo. A hidrogeomorfologia é um domínio interdisciplinar emergente, que estuda as relações entre as unidades geomorfológicas e o regime das águas superficiais e subterrâneas de uma determinada área. A compreensão do papel da geomorfologia é essencial para avaliar de forma rigorosa os sistemas hidrogeológicos e os recursos hídricos. Os dados de detecção remota providenciam uma informação espacial valiosa e actualizada da superfície terrestre e dos recursos naturais. Os recentes avanços tecnológicos colocaram as técnicas de detecção remota e os sistemas de informação geográfica (SIG) numa posição cimeira como ferramentas de gestão metodológica. Foi criada, em ambiente SIG, uma base de geo-dados, essencialmente derivada da detecção remota, da cartografia e do trabalho de campo. Esta base de dados, organizada em diferentes níveis de informação, inclui uma avaliação principalmente focalizada no uso do solo, climatologia, declives, geologia, geomorfologia e hidrogeologia. No presente estudo foram cruzados diversos níveis de informação, com a geração de múltiplos mapas temáticos para atingir um quadro integrado dos diversos sectores no Norte e Centro de Portugal. Os sectores em estudo (Caldas da Cavaca, Termas de Entre-os-Rios, Águas de Arouca e Águas do Alardo) estão localizados em sistemas hidrogeológicos predominantemente constituídos por rochas graníticas, por vezes intersectadas por filões de quartzo, aplito-pegmatíticos e doleríticos. Para apoiar a elaboração dos mapas hidrogeomorfológicos foi criada uma base SIG, contendo diversa informação, nomeadamente topografia, hidrografia, litologia, tectónica, morfoestrutura, hidrogeologia, geofísica e uso do solo. Além disso, foram realizadas várias campanhas de campo, as quais permitiram: o estabelecimento dum mapeamento geológico, geomorfológico e hidrogeológico; a caracterização in situ do grau de alteração, resistência e grau de fracturação dos maciços rochosos; o desenvolvimento de um inventário hidrogeológico em conjunto com alguns ensaios expeditos in situ. A interligação entre os parâmetros geomorfológicos, hidrológicos e hidrogeológicos dos sistemas de água subterrânea “normal” e hidromineral destaca a importância de uma cartografia e duma modelação conceptual hidrogeomorfológica. Além disso, contribuirá para um melhor apoio à decisão na gestão sustentável dos recursos hídricos.

Regional Knowledge Maps - Potential and Challenges

Regional knowledge map is a tool recently demanded by some actors in an institutional level to help regional policy and innovation in a territory. Besides, knowledge maps facilitate the interaction between the actors of a territory and the collective learning. This paper reports the work in progress of a research project which objective is to define a methodology to efficiently design territorial knowledge maps, by extracting information of big volumes of data contained in diverse sources of information related to a region. Knowledge maps facilitate management of the intellectual capital in organisations. This paper investigates the value to apply this tool to a territorial region to manage the structures, infrastructures and the resources to enable regional innovation and regional development. Their design involves the identification of information sources that are required to find which knowledge is located in a territory, which actors are involved in innovation, and which is the context to develop this innovation (structures, infrastructures, resources and social capital). This paper summarizes the theoretical background and framework for the design of a methodology for the construction of knowledge maps, and gives an overview of the main challenges for the design of regional knowledge maps.

Challenges and Potentials for Keyword Extraction from Company Websites for the Development of Regional Knowledge Maps

Regional Innovation Systems describe the relations between actors, structures and infrastructures in a region in order to stimulate innovation and regional development. For these systems the collection and organization of information is crucial. In the present paper we investigate the possibilities to extract information from websites of companies. First we describe regional innovation systems and the information types that are necessary to create them. Then we discuss the possibilities of text mining and keyword extraction techniques to extract this information from company websites. Finally, we describe a small scale experiment in which keywords related to economic sectors and commodities are extracted from the websites of over 200 companies. This experiment shows what the main challenges are for information extraction from websites for regional innovation systems.