Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Mapping the Membrane Topology of Hepatitis C Virus Nonstructural Protein 4B

BACKGROUND: Nonstructural protein 4B (NS4B) plays an essential role in the formation of the hepatitis C virus (HCV) replication complex. It is an integral membrane protein that has only poorly been characterized to date. In particular, a precise membrane topology is thus far elusive. Here, we explored a novel strategy to map the membrane topology of HCV NS4B. METHODS: Selective permeabilization of the plasma membrane, maleimide-polyethyleneglycol (mPEG) labeling of natural or engineered cysteine residues and immunoblot analyses were combined to map the membrane topology of NS4B. Cysteine substitutions were introduced at carefully selected positions within NS4B and their impact on HCV RNA replication and infectious virus production analyzed in cell culture. RESULTS: We established a panel of viable HCV mutants with cysteine substitutions at strategic positions within NS4B. These mutants are infectious and replicate to high levels in cell culture. In parallel, we adapted and optimized the selective permeabilization and mPEG labeling techniques to Huh-7 human hepatocellular carcinoma cells which can support HCV infection and replication. CONCLUSIONS: The newly established experimental tools and techniques should allow us to refine the membrane topology of HCV NS4B in a physiological context. The expected results should enhance our understanding of the functional architecture of the HCV replication complex and may provide new opportunities for antiviral intervention in the future.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Urban Governance und nachhaltige Quartiere: Ein Beitrag zur Förderung einer dauerhaft nachhaltigen Stadtentwicklung

Seit den 1990er Jahren werden zunehmend nachhaltige Quartiere realisiert. Dabei besteht häufig eine beachtliche Diskrepanz zwischen den Zielen, die von den beteiligten Akteuren angestrebt werden, deren Umsetzung (Realisierungsphase) und deren Erhalt auf Dauer (Nutzungsphase). Es stellt sich folglich die Frage, auf welche Weise die Projektqualität im Sinne einer nachhaltigen Quartiersentwicklung verbessert werden kann. Diese Projekte sind jedoch enorm komplex aufgrund der großen Interdisziplinarität und Interdependenz ihrer Ziele sowie der vielschichtigen Akteursstrukturen. Sie stellen daher be-sonders hohe Anforderungen an die Projektsteuerung. Das konkrete Ziel dieser Arbeit besteht darin, die Bedeutung einer Prozesssteuerung im Sinne von Urban Governance zur Realisierung und zum Erhalt nachhaltiger Quartiere zu untersuchen. Damit soll einen Beitrag zur Förderung einer nachhalti-gen Stadtentwicklung geleistet werden. Die Arbeit stützt sich auf ein umfassendes theoretisches Fundament zum Thema Governance, wobei die relevanten Elemente für den Kontext nachhaltiger Quartiere herausgearbeitet werden. Die Hypothesen prüfen die Bedeutung der Schlüsselcharakteristika von Urban Governance (Kooperation, Partizipation, Verhandlungen) für die Projektqualität während der Realisierungs- und Nutzungsphase. Eine erste empirische Untersuchung wurde an zwanzig europäischen nachhaltigen Modellquartieren vorgenommen. Stärken und Schwächen aus der Perspektive der Nachhaltigkeit werden analysiert, deren Ursachen identifiziert und Handlungsoptio-nen aufgezeigt. Die Erkenntnisse zeigen die Notwendigkeit einer Verbesserung der Projektsteuerung während der Realisierungs- und der Nutzungsphase. Auf der Grundlage dieser Erkenntnisse wird ein umfassender Ansatz zur empirischen Untersuchung von Urban Governance im Kontext nachhaltiger Quartiere entwickelt. Dieser beruht auf dem akteurzentrierten Institutionalismus und den Merkmalen der Urban Governance. Anhand dieses Ansatzes wird mithilfe von Experteninterviews der Realisierungsprozess des nach-haltigen Quartiers Kronsberg (Hannover) analysiert. Betrachtet werden dabei die beteiligten Akteure und ihre Handlungso-rientierungen, die verwendeten Schlüsselinstrumente sowie aufgetretene Divergenzen zwischen Akteuren und deren Auswirkungen auf die Projekt- und Prozessqualität. Eine Vertiefung relevanter Themenfelder wird anhand der Fallstudie Neu-Oerlikon (Zürich) vorgenommen. Diese empirische Arbeit zeigt, dass eine Prozesssteuerung im Sinne von Urban Governance im Vergleich zu einer klassis-chen hierarchischen Steuerung eine notwendige aber nicht hinreichende Bedingung zur Verbesserung der Projektqualität nachhaltiger Quartiere darstellt. An konkreten Beispielen wird herausgearbeitet, dass der Mehrwert einer solchen Steuerung nur unter bestimmten Voraussetzungen erzielt werden kann: In manchen Situationen ist die Steuerungsform Kooperation und die Interaktionsform Verhandlung in ihrer Wirksamkeit zur Sicherung der Projektqualität begrenzt und hierarchische Interventionen sind notwendig. Nicht ein bestimmtes Steuerungsmodell per se ist geeignet, sondern es kommt auf den Ein-zelfall an: auf die Akteursstruktur, die individuellen und institutionellen Handlungsorientierungen der Akteure und deren Ver-haltensweisen, die Rahmenbedingungen und die Ausgestaltung des Urban Governance-Prozesses. Wenn die Spielregeln dieses Prozesses von den Akteuren nicht wirklich angenommen und gelebt werden, dominieren individuelle und institutio-nelle Akteursinteressen zu Lasten der Projektqualität. Ferner zeigen die Untersuchungen, dass die Partizipation der zukünftigen Quartiersnutzer in der Praxis häufig unzureichend ist. Dies führt zu Einbußen in der Projektqualität. Entscheidend ist auf jeden Fall, dass mindestens ein Akteur, in der Regel die öffentliche Hand, präsent ist, der die Definition anspruchsvoller Nachhaltigkeitsstandards, deren Umsetzung und deren Erhalt sichert sowie die notwendigen Rahmenbedingungen dafür schafft. Diese Arbeit belegt darüber hinaus, dass der Erhalt der Projektqualität während der Nutzungsphase (Faktor Zeit) bisher un-zureichend beachtet und in die Projektplanung einbezogen wird. Gerade dieser Aspekt bestimmt aber, ob das Quartier auch auf Dauer dem Nachhaltigkeitsanspruch gerecht werden kann! Tatsächlich handelt es sich um einen fortlaufenden Prozess, der nicht mit der Einweihung des Quartiers abgeschlossen ist. Vor diesem Hintergrund werden relevante Handlungsfelder beschrieben und die Notwendigkeit der langfristigen Fortsetzung einer Steuerung im Sinne von Urban Governance bzw. der Herausbildung einer Urban Governance-Kultur aufgezeigt. Aus den empirischen Erhebungen werden Erfolgs- und Risikofaktoren für Urban Governance-Prozesse während der Realisierungs- und der Nutzungsphase abgeleitet. Ferner werden bisher vernachlässigte Handlungsfelder (langfristiges Umwelt-management, ökologische Finanzierungsformen, urbane Landwirtschaft, Umweltkommunikation, etc.) eruiert. Die Berücksichtigung dieser Erkenntnisse ist unerlässlich für eine Verbesserung der Projektqualität nachhaltiger Quartiere. ---------------------------------------------- Gouvernance urbaine et quartiers durables: Entre intensions et mise en oeuvre --- Résumé --- Depuis les années 90, la thématique des quartiers durables a gagné en importance, même si leur développement s'est avéré difficile. Le décalage entre les objectifs, leur mise en oeuvre et le projet tel qu'il est vécu par ses habitants est souvent important et nécessite d'être réduit. Un quartier durable est par nature un projet complexe, aux objectifs ambitieux situé à la croisée de multiples champs disciplinaires, mobilisant de nombreux acteurs aux intérêts divergents. De plus, chaque projet, du fait des ses spécificités, requiert un pilotage adapté. L'objectif principal de la recherche vise à analyser la nature du pilotage du processus de conception, de réalisation et d'exploitation des quartiers durables. Ses résultats ont pour ambition de contribuer à optimiser et promouvoir le développement urbain durable. Le fondement théorique de la recherche se base sur le concept de gouvernance urbaine, adapté au contexte particulier de la gouvernance des quartiers durables. La gouvernance urbaine, au sens où nous l'entendons, est un mode de pilotage basé sur la coopération entre les acteurs publics et privés. Les hypothèses centrales du travail testent la portée et les limites des caractéristiques-clefs de la gouvernance urbaine (coopération, participation, négociation), ainsi que l'importance de la notion de pérennité pour la qualité du projet. Dans un premier temps, nous avons analysé vingt quartiers durables modèles européens et identifié leurs atouts et leurs faiblesses en termes de durabilité, ainsi que leurs divers modes de pilotage. Les enseignements tirés de ces exemples révèlent la nécessité d'améliorer le pilotage des projets. Dans un deuxième temps, nous avons élaboré une grille d'analyse fine fondée sur l'approche institutionnelle des acteurs et les caractéristiques-clefs de la gouvernance urbaine. En nous appuyant sur cette grille, nous avons analysé le processus de conception et de réalisation du quartier durable de « Kronsberg » (Hanovre) à l'aide des éléments suivants : les acteurs (avec leurs intérêts et objectifs propres), les instruments d'aménagement du territoire, les modes de pilotage, les zones de divergence et de convergence entre les acteurs, ainsi que leurs impacts sur le processus et le projet. Dans un troisième temps, les hypothèses centrales ont été testées sur le quartier de « Neu-Oerlikon » (Zurich) afin d'approfondir et d'élargir les enseignements tirés de celui de « Kronsberg ». Les résultats des analyses mettent en évidence le fait qu'un pilotage de projet selon le modèle de la gouvernance urbaine est certes une condition nécessaire mais non suffisante pour améliorer la qualité du projet. De plus, la valeur ajoutée de la gouvernance urbaine n'est valable qu'à certaines conditions. En effet, la coopération et la négociation peuvent même, dans certaines situations, réduire la qualité du projet ! Le principal enseignement de la recherche révèle qu'il n'y a pas de mode de pilotage idéal, mais que la qualité d'un projet dépend d'une multitude de facteurs, tels que les constellations d'acteurs, leurs intérêts personnels et institutionnels, les conditions cadres et les « règles du jeu » de la gouvernance urbaine. Si les « règles du jeu » en particulier ne sont pas réellement appropriées par l'ensemble des acteurs, les intérêts et les comportements personnels ou institutionnels prédominent au détriment de la qualité du projet. De même, si la participation des futurs usagers à l'élaboration du projet de quartier durable n'est pas assurée, tant la qualité du projet que sa pérennité en pâtissent. Nous avons également constaté que la présence d'un acteur (en règle générale les autorités publiques) qui veille à la définition d'objectifs ambitieux en matière de développement durable et à leur application constitue un apport essentiel à la qualité du projet. En outre, la recherche met en évidence les carences dans le suivi et le maintien à long terme des qualités de durabilité de la phase d'exploitation des projets de quartiers durables analysés. Dans la phase d'exploitation, le degré de coopération diminue généralement et les modes de fonctionnement et de pilotage sectoriels se mettent en place au détriment de la qualité du projet. Cela confirme la nécessité de poursuivre le processus de pilotage selon le modèle de la gouvernance urbaine au-delà de la phase de réalisation des projets. La recherche précise les enjeux des champs d'action de la phase d'exploitation (domaine encore peu étudié) et démontre la pertinence du mode de pilotage préconisé. Enfin, les analyses permettent d'identifier des facteurs de réussite et de risque susceptibles d'influencer les systèmes de gouvernance urbaine, ainsi que les enjeux des domaines de la durabilité encore négligés (agriculture urbaine, gestion environnementale dans la durée, comportement des usagers, financement équitable, etc.). La prise en compte de ces enseignements est essentielle à l'amélioration de la gestion de futurs projets de quartiers durables. ---------------------------------------------- Urban Governance and Sustainable Neighbourhoods: A Contribution to a Lasting Sustainable Development --- Abstract --- Since the 1990s, sustainable neighbourhoods have become an increasingly important topic. However, their development has proven to be difficult. There is an often considerable gap, which must be reduced, between the initial goals, the way they are implemented and how the project is finally inhabited. A sustainable neighbourhood is inherently a complex project, with ambitious goals that lie at the intersection of multiple disciplines, involving numerous stakeholders with diverging interests. Moreover, each project, due to its specific characteristics, requires an adapted steering. The main goal of this research is to analyse the nature of the steering process during the planning, realisation and use of sustainable neighbourhoods. The results aim to contribute to the promotion of sustainable urban development. The theoretical foundation of this research is based on the concept of urban governance, adapted to the particular context of sustainable neighbourhoods. Urban governance is understood in this work, as a mode of project steering based on the cooperation between public and private stakeholders. The central hypotheses of this work test the importance and the limits of the key characteristics of urban governance (cooperation, participation, negotiation) as well as the importance of continuity for the project quality. To begin with, we surveyed and analysed twenty exemplary European sustainable neighbourhoods and identified their strengths and weaknesses in terms of sustainability, as well as their diverse steering modes. The lessons learned from these examples reveal the need to improve the projects' steering. Secondly we elaborated a detailed framework for analysis founded on stakeholder-centred institutionalism and the key characteristics of urban governance. By systematically applying this framework, we analysed the planning and implementation process of the sustainable neighbourhood "Kronsberg" (Hannover). Our focus was on the following dimensions: the stakeholders (with their particular interests and goals), the instruments of spatial planning, the steering modes, the points of divergence and convergence amongst the stakeholders, as well as their impacts on the process and on the project. The final step was to test the core hypotheses on the neighbourhood "Neu-Oerlikon" (Zürich) in order to broaden the lessons learned from "Kronsberg". The results of the analysis highlight the fact that an urban governance type project steering is certainly a necessary but insufficient condition to improve the project quality. Moreover, the added value of urban governance is only valid under certain conditions. In fact, cooperation and negotiation can even in certain situations reduce the project's quality! The main lesson of this research is that there is not an ideal steering mode, but rather that the quality of the project depends on numerous factors, such as the stakeholder constellation, their individual and institutional interests, the general conditions and the "rules of the game" of urban governance. If these "rules of the game" are not really appropriated by all stakeholders, individual and institutional interests and behaviours predominate at the expense of the project's quality. Likewise, if the future users' participation in the project development is insufficient, both the project's quality and its continuity suffer. We have also observed that the presence of a stakeholder (in general the public authorities) who ensures the definition of ambitious goals in terms of sustainable development and their implementation is crucial for the project's quality. Furthermore, this research highlights the deficiencies in the follow-up and long-term preservation of the sustainability qualities in the neighbourhood projects which we have analysed. In the use phase, the degree of cooperation generally diminishes. Attitudes and project management become more sectorial at the expense of the project's quality. This confirms the need to continue the steering process according to the principles of urban governance beyond the project's implementation phase. This research specifies the challenges that affect the use phase (a still neglected area) and shows the relevance of the recommended steering mode. Finally, the analyses also identify the success and risk factors that may influence urban-governance systems, as well as the challenges of still neglected fields of sustainability (urban agriculture, long-term environmental management, user behaviour, fair funding, etc.). Taking into account these outcomes is essential to improve the management of future sustainable-neighbourhood projects.

Emergence of Swiss metropole and scaling properties of urban clusters

Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Mapping the human connectome at multiple scales with diffusion spectrum MRI.

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.