An Approach for spatial and temporal data analysis: application for mobility modeling of workers in Luxembourg and its bordering areas

In this paper, we propose a general visual analytic approach to synthesis very large spatial data and discover interesting knowledge and unknown patterns from complex data based on Origin-Destination (OD) matrices. The research studies of Tobler constitute a good basis in this topic. This paper is interested in the proposal of 2 methods entitled respectively ?Weighted Linear Directional Mean: WLDM? and ?DS-WLDM?. The latter incorporates the Dempster-Shafer theory of evidence with WLDM. Both of the developed methods are an extension of ?Linear Directional Mean: LDM? for mobility modeling. With classical techniques such as LDM among others, the results of data mapping are not intelligible and easy to interpret. However with both WLDM and DS-WLDM methods it is easy to discover knowledge without losing a lot of information which is one of the interests of this paper. This proposal is generic and it intends to be applied for data mapping such as for geographical presentation of social and demographic information (e.g. mobility of people, goods and information) according to multiple spatial scales (e.g. locality, district, municipality). It could be applied also in transportation field (e.g. traffic flow). For the application, administrative data is used in order to evaluate spatial and temporal aspects of the daily and the residential mobility of workers in Luxembourg and its bordering areas.Mobility modeling; data mapping; spatial mobility; geographic knowledge discovery; location uncertainty; daily and residential mobility

Border effects on the travel mode choice of resident and crossborder workers in Luxembourg

We investigate the travel mode choice behaviour of both resident and cross-border workers in Luxembourg. Two categories of mode choice are considered: sustainable (public transport) and unsustainable (single occupancy car use), which both depend on a large set of spatial and sociodemographic variables. In particular, we determine whether and how the borders of the four countries involved (Luxembourg, Belgium, France, Germany) affect this choice. The results of a classical binary logistic regression model show that significant variables depend on the area of residence and that some border effects are relevant in the context of the studied cross-border areas. Moreover, the identification of these various border-effect variables does not require the use of big data processing techniques. Therefore the proposed method can be applied generally to other cross-border areas with an open border context to highlight the effects of border on functional integration. This study is helpful in terms of developing a better understanding of the determinants involved in the use of sustainable transport modes and in supporting decisionmaking to improve transport planning

A method and a tool for geocoding and record linkage

For many years, researchers have presented the geocoding of postal addresses as a challenge. Several research works have been devoted to achieve the geocoding process. This paper presents theoretical and technical aspects for geolocalization, geocoding, and record linkage. It shows possibilities and limitations of existing methods and commercial software identifying areas for further research. In particular, we present a methodology and a computing tool allowing the correction and the geo-coding of mailing addresses. The paper presents two main steps of the methodology. The first preliminary step is addresses correction (addresses matching), while the second caries geocoding of identified addresses. Additionally, we present some results from the processing of real data sets. Finally, in the discussion, areas for further research are identified.addresses correction; geocodage; matching; data management; record linkage

Simulation of land use changes using cellular automata and artificial neural network

This paper presents a method integrating artificial neural network (ANN) in cellular automata (CA) to simulate land use changes in Luxembourg and the areas adjacent to its borders. The ANN is used as a base of CA model transition rule. The proposed method shows promising results for prediction of land use over time. The ANN is validated using cross-validation technique and Receiver Operating Characteristic (ROC) curve analysis, and compared with logit model and a support vector machine approach. The application described in this paper highlights the interest of integrating ANNs in CA based model for land use dynamic simulation.Artificial neural network; Cellular automata; Modelling; Land use changes; Spatial planning and dynamics

Validation d'un modèle d'accessibilité par recoupement de données multi-sources. Application aux communes de Belgique

Dans le cadre du projet de recherche MOBLOC (Mobilities and Long Term Location Choice in Belgium), l'exploration à un niveau d'agrégation communal des interactions entre les mobilités résidentielle et quotidienne a nécessité la construction d'un modèle d'accessibilité routière à l'échelle de la Belgique. Dans un premier temps, un modèle de trafic en heures creuses affectant les flux selon un mode tout-ou-rien, est comparé à une base d'observations (MOBEL) ainsi qu'à deux modélisations (Google Maps et un modèle développé à l'UCL par Vandenbulke et al., 2009). Le modèle routier aux heures de pointe du matin procède à l'affectation d'une matrice de demande de déplacement domicile-travail et domicile-études sur la base de la recherche d'un équilibre utilisateur. En complément de l'analyse cartographique, différentes statistiques de qualité d?ajustement sont mises à contribution pour le calibrage et la validation du modèle d'accessibilité MOBLOC.accessibilité routière; heures de pointe; heures creuses; Belgique; modélisation

Structural and Calorimetric Studies of Zinc, Magnesium and Manganese Based Phosphate and Phosphate-Silicate Glasses

Glasses of the (50-x/2)Na2O-xMO-(50-x/2)P2O5 (M = Zn, Mg or Mn) (0 ≤ x ≤ 33 mol%), (50-x)Na2O-xMO-50P2O5 (M = Zn, Mn) (0 ≤ x ≤ 33 mol%), and (0.9-x)NaPO3-xSiO2-0.1ZnO (0 ≤ x ≤ 0.1 mol) were prepared by the melt quenching technique. Samples were investigated by means of X-ray diffraction, Archimede’s method, ellipsometry, Fourier-transformed infrared (FTIR), Raman, 31P solid state magic angle spinning nuclear magnetic resonance (MAS-NMR), UV-visible spectroscopy and calorimetry. For zinc, manganese and magnesium phosphate glasses, the increase in density with the addition of MO oxide suggests the compactness of the vitreous network. For zinc phosphate silicate glasses, the variations of density and refractive index were attributed to the structural changes when SiO2 oxide is progressively introduced. The increase in the glass transition temperature (Tg) reflects an increase in the cross-link strength of the structure as MO and SiO2 oxides are gradually incorporated. For all glass composition, spectroscopic investigations revealed the depolymerization of metaphosphate chains (Q2) allowing the formation of phosphate dimers (Q1). Calorimetric dissolution shows that the dissolution is endothermic for lower MO content and become exothermic when x rises. For (50-x/2)Na2O-xZnO-(50-x/2)P2O5 (0 ≤ x ≤ 33 mol%) glasses, the formation enthalpy increases with the incorporation of ZnO oxide

COVID-19 in Europe : Dataset at a sub-national level

The COVID-19 pandemic has hit humanity, straining health care systems, economies, and governments worldwide. In one of the responses to the pandemic, a big global effort has been mounted to collect, analyze, and make data publicly available. However, many of the existing COVID-19 public datasets are (i) aggregated at country level, and (ii) tend not to bring the COVID-19-specific data coupled with socio-demographic, economic, public policy, health, pollution and environmental factors, all of which may be key elements to study the transmission of the SARS-CoV-2 and its severity. To aid the evaluation of the determinants and impact of the COVID-19 pandemic at a large scale, we present here a new dataset with socio-demographic, economic, public policy, health, pollution and environmental factors for the European Union at the small regions level (NUTS3). The database is freely accessible at http://dx.doi.org/10.17632/2ghxnrkr9p.4. This dataset can help to monitor the COVID-19 mortality and infections at the sub-national level and enable analysis that may inform future policymaking

Développement d'une méthode et d'un outil d'aide à l'évaluation (application à la mobilité urbaine)

Ces travaux portent sur l'évaluation des projets de transport à partir d'un ensemble de critères ayant des degrés d'importance différents, en interaction, évalués par des sources d'information hétérogènes (experts, enquêtes, capteurs, modèles etc.). Les données collectées sont généralement entachées d'incertitude, d'imprécision et d'incomplétude. Pour résoudre ce problème d'évaluation des projets de transport, nous proposons une approche hybride baptisée HA4IA. Elle est basée sur la théorie de l'analyse multicritères, la logique floue et la théorie des croyances. Ces cadres théoriques présentent un cadre propice pour la gestion des données imprécises et incertaines. Nous proposons aussi un outil orienté web (DeSSIA), basé sur l'approche proposée. L'approche a été appliquée pour plusieurs projets de transport implémentés (à La Rochelle - France) dans le cadre d'un projet européen (SUCCESS / programme CIVITAS). L'outil développé est basé sur un environnement informatique open source (R, PHP, Mapserver, Mapscript, Jpgraph, XHTML, Ajax etc.). Il permet d'évaluer divers impacts liés à la mobilité urbaine. Les résultats d'évaluation peuvent être représentés sous forme de graphes (à l'aide des techniques de représentation graphique) ou de cartes (trafic, pollution, acoustique). La cartographie permet de représenter la répartition spatio-temporelle des impacts présentant un outil supplémentaire d'aide à l'évaluation géospatiale. Tout au long du développement de cet outil, une attention particulière a été accordée à l'identification et aux réponses apportées aux attentes de potentiels utilisateurs: services de transports urbains, spécialistes en aménagement du territoire, socio-économistes ou écologistes.These works problem consists in evaluating projects of transport starting from a set of criteria having different degrees of importance, in interaction and evaluated by heterogeneous sources of information (experts, surveys, sensors, model etc). The collected data are generally sullied with uncertainty and inaccuracy. To solve this problem of projects evaluation related to transportation, we propose a hybrid approach entitled HA4IA (Hybrid Approach for Impacts Assessment). It is based on the theory of the multi criteria analysis, fuzzy logic and belief theory. These theoretical frameworks present a favourable framework for the management of the vague and uncertain data. We propose also a tool (DeSSIA), based on the proposed approach. The approach was applied for several projects of transport implemented (in La Rochelle - France) within the framework of a European project (SUCCESS under CIVITAS program). The developed tool is based on a data-processing environment open source (R, PHP, Mapserver, Mapscript, Jpgraph, XHTML, Ajax etc). It makes it possible to evaluate various impacts related to urban mobility. The results of evaluation can be represented in the form of graphs (using the techniques of chart) or of maps (traffic, pollution, acoustics). The cartography makes it possible to represent the space-time distribution of the impacts presenting an additional geo-space tool of evaluation aid.COMPIEGNE-BU (601592101) / SudocSudocFranceF