Multiple Fabric Assessment: Focus on Method Versatility and Flexibility

Alessandro Araldi (1) , Joan Perez (2, 1) , Giovanni Fusco (1) , Takashi Fuse (2)

1 ESPACE - Étude des Structures, des Processus d’Adaptation et des Changements de l’Espace
2 UTokyo - The University of Tokyo

Metropolitan regions are very complex spaces for geographical analysis, above all due to their strong heterogeneity at the intra-urban level. This paper presents the progresses made by Multiple Fabric Assessment (MFA), a method specifically conceived for describing urban fabrics from the pedestrian perspective. To sum up, standard spatial units are first defined (Proximity Bands) and specific indicators are calculated at this level. Then, patterns amongst space are identified and clustered. The application of MFA method to new case studies (Marseille, Osaka, Rio de Janeiro and Brussels) has brought to highlight several peculiarities related to data availability, intrinsic urban space characteristics and aim of application. This paper collects the experiences gathered from these new case studies, highlighting key aspects that academics and practitioners should deal with, when using MFA. Our results show a versatile and flexible method, able to be adapt itself to any case study if not limited by data availability.

Domaines: Géographie; Méthodes et statistiques; Machine Learning [stat.ML]

Alessandro Araldi, Joan Perez, Giovanni Fusco, Takashi Fuse. Multiple Fabric Assessment: Focus on Method Versatility and Flexibility. O. Gervasi et al. Computational Science and Its Applications – ICCSA 2018 18th International Conference Proceedings - Part III, 10962, Springer, pp.251-267, 2018, Lecture Notes in Computer Science, 9783319951676. ⟨10.1007/978-3-319-95168-3_17⟩. ⟨hal-02176597⟩