The city and the metropolis : urban form through multiple fabric assessment in Marseille, France

This paper presents a multi-scale detection of urban fabric types through Multiple Fabric Assessment in Marseille, France's second city. MFA is a computer-aided streetscape-based urban morphometric protocol for morphological regionalization of large urban areas. First presented at ISUF 2017, MFA has already been successfully applied to the metropolitan areas of the French Riviera, Osaka and Brussels. The protocol is first applied to the central city, and then to the much larger metropolitan area around Marseille and Aix-en-Provence, stretching over 7000 km2 and home to 2.6 million inhabitants. In both cases, MFA detects eight well-defined families of urban fabrics with clear morphological specificities. The change of spatial extent has nevertheless consequences on the analysis results. On the one hand, urban fabric types detected at the two scales show a precise pattern of correspondences. On the other, each scale allows a finer description of its most preponderant morphological regions, detecting more specific types which are bundled together at the other scale. This is the case for the traditional urban fabrics of the compact city at the municipal scale, and for the suburban fabrics at the metropolitan scale. Accepting some generalisation, the urban fabric types detected by MFA are able to account for the variety of urban forms identified in 36 urban fragments by Marseille's metropolitan planning agency through classical morphological analysis. Beyond the different grain of the analyses (streetscapes vs urban blocks), expert-based and computer-aided classifications are in good agreement. Allowing comprehensive multiscale analyses of urban fabrics for the whole metropolitan area of Marseille, MFA showed the patchwork nature of its 20th century developments and put in perspective the overstated fragmentation of the 19th century urbanisation. Participating to the emerging field of urban morphometrics, MFA opens the way to wider comparative analysis at the national and international levels

Ageing and urban form in Aix-Marseille-Provence metropolis

The world population is ageing. In France, this phenomenon is particularly pronounced with 19.6% of the population being over 65-year-old in 2018. While it has been recognized that urban form plays an important role in ensuring a sustainable future for urban areas, ageing dynamics are challenging the core concept of urban sustainability. Maintaining or improving the quality of life of an ageing population through urban built form will become as much important, and as much recognized, as ensuring urban environmental sustainability in the future. Today, the well-being of the elderly is still reduced to the economic aspects of the silver economy or to ergonomic aspects in building design. While socio-demographic micro-data on the elderly are available, a comprehensive metropolitan-wide and fine-scale description of the urban forms where seniors live must rely on the latest developments of urban morphometrics. From historic city centres to suburban residential areas, passing through modernist apartment blocks, none of these typical forms seems particularly suited to the needs posed by ageing, which must accommodate accessibility to housing itself and to local shops, health care and services in general. The question of the role of different urban forms over the spatial distribution of the seniors thus arises, as well as the capacity of spatial arrangements to suit the needs and specificities of an ageing population. The case study is a metropolitan area that offers a great heterogeneity of urban forms: Aix- Marseille-Provence, in Southern France. Some areas show over or under-representation of seniors, while others are better at ensuring a generational mix. In most cases, the spatial distribution of the seniors can be linked to specific building hull forms. The spatial distribution of these hull types, and their close relationships to ageing and accessibility are presented in this paper

Crystal Structure of a Complex of DNA with One AT-Hook of HMGA1

We present here for the first time the crystal structure of an AT-hook domain. We show the structure of an AT-hook of the ubiquitous nuclear protein HMGA1, combined with the oligonucleotide d(CGAATTAATTCG)2, which has two potential AATT interacting groups. Interaction with only one of them is found. The structure presents analogies and significant differences with previous NMR studies: the AT-hook forms hydrogen bonds between main-chain NH groups and thymines in the minor groove, DNA is bent and the minor groove is widened

Bayesian Network Clustering and Self-Organizing Maps under the Test of Indian Districts. A comparison

This paper compares Hierarchical Clustering, Bayesian Networks and Self-Organizing Map Neural Networks (SOM and superSOM) approaches used for clustering purposes in geographic space. The same dataset, covering the Republic of India and made of 55 indicators for 640 spatial units (administrative districts), is used in the three analyses. Indicators descry the several aspects of urban, economic and socio-demographic development in India. Bayesian Networks use a likelihood function while SOM/SuperSOM and Hierarchical Clustering minimize variance of Euclidean distance in variable space, the former by preserving the topological properties within the output space and the latter by successively combining similar items. Relatively similar multi-step protocols have been implemented for the three techniques, to take into account variable redundancy. Methods as well as clustering results are compared. From this perspective, the aim of the paper is to highlight the similarities between the protocols and to evaluate the differences between the segmentation approaches (geographical and variable space comparisons). A few key points are also discussed such as the data pre-processing steps, the conception of latent factors and the choice of the number of clusters.Cet article compare les méthodes de la classification hiérarchique, des réseaux bayésiens et des réseaux de neurones de type self-organizing maps (SOM et superSOM) utilisés afin de partitionner des unités spatiales. Le même jeu de données, relatif à la République de l’Inde et composé de 55 indicateurs pour 640 unités spatiales (districts administratifs), est utilisé dans les trois cas. Les indicateurs couvrent plusieurs aspects du développement urbain, économique et sociodémographique de l’Inde. Les réseaux bayésiens utilisent une fonction de vraisemblance tandis les SOM/SuperSOM et la classification hiérarchique minimisent la variance de la distance euclidienne dans l'espace des variables, le premier en préservant la notion de topologie dans les sorties du modèle et le second en combinant successivement les objets similaires. Des protocoles à plusieurs étapes relativement similaires ont été mis en place pour les trois techniques pour réduire la redondance des variables dans le jeu de données. Les méthodes ainsi que les résultats des partitionnements sont comparés. Dans cette perspective, le but de l’article est de mettre en évidence les similitudes entre les protocoles ainsi que d'évaluer les différences entre les approches de segmentation (dans l’espace des variables ainsi que dans l’espace géographique). Quelques points clés sont également discutés tels que les étapes de prétraitement des données, la conception des facteurs latents et le choix du nombre de clusters

Exploring inequalities in India through housing overcrowding

International audienc

Spatial Analysis of the Indian Subcontinent: the Complexity Investigated through Neural Networks

International audienceIndia is a very complex space for geographical analysis, above all when the focus of the research is on the rapid transformation of the Indian space, related to urbanization and socioeconomic development. This paper adopts an inductive approach using a database specifically conceived for describing the 640 administrative districts of India between 2001 and 2011. Neu-ral Networks SOM and superSOM approaches are used to cluster districts. Different model options will be presented and a few key points like the importance of prior variable clustering and robust initialization will be highlighted. These key points can be considered as essential prerequisites for any spatial analysis using Neural Networks. The results of the models show that the Indian space can be meaningfully segmented into a limited number of district profiles, corresponding to particular sub-spaces. Our results show a complex and heterogeneous country, with sub-spaces possessing logics of their own and far away from any cliché

Inde rurale, Inde urbaine: qualification et quantification de l'aptitude au changement des territoires indiens

Actes de la conférence : Aux Frontières de l'Urbain http://halshs.archives-ouvertes.fr/halshs-00958799 [Collection : Actes Avignon -ISBN : 978 2 9105 4509 1]L'Inde est souvent perçue par les grandes entreprises occidentales comme l'un des nouveaux eldorados des pays émergents de part ses processus d'urbanisation et son industrialisation croissante. Mais, la réalité Indienne est tout autre. En valeur absolue, la population indienne a augmenté de 181 millions d'habitants entre 2001 et 2011 contre 79,5 millions pour le nombre de travailleurs à temps plein. De plus, le système agraire intensif en zone rurale a contribué à établir une concurrence féroce entre agriculteurs tout en réduisant le nombre de propriétaires terriens. Ainsi, l'augmentation du niveau de vie liée à la croissance économique ne sera pas distribuée de façon homogène sur un territoire où les clivages socio-économiques sont déjà accentués par un système hermétique de castes. De surcroit, l'Inde est un espace qui possède une histoire urbaine longue et complexe. Il en résulte une multitude de systèmes urbains fonctionnels aux caractéristiques internes et externes variées. La délimitation avec l'espace rural devient de plus en plus difficile à définir, mais surtout impossible à généraliser à l'ensemble de ce pays du fait de son immensité. Le présent article s'insère dans un programme de recherche plus vaste et ayant pour objectif l'étude des transformations socio-économiques et des niveaux de vie des ménages indiens. Dans cette étude, chacun des 640 districts de l'Union Indienne est considéré comme un écosystème jouissant d'un potentiel de transformation socio-économique et territoriale. Cet article a pour objectif de caractériser par une classification multivariée de type Bayésien le degré de réaction au changement d'état de ces écosystèmes. L'hypothèse étant qu'il est possible de déterminer à quel degré un district indien est propice à l'innovation et, dans le cas de cet article, au passage in situ à un type fonctionnement plus " moderne ". Plusieurs cas de figures regroupent ces observations : du district faisant partie intégrante d'une agglomération au district non-urbanisé. De plus, les sauts d'étapes peuvent rapidement inverser ou accentuer une tendance à l'ouverture en Inde. Cet article présentera les résultats préliminaires obtenus en étudiant la dynamique décennale 2001-2011 par la caractérisation bayésienne des facteurs internes (variables socio-économiques, consommation, emploi, urbanisation, etc.) et externes (degré de métropolisation, appartenance à des macrostructures urbaines, etc.) des 640 districts indiens