Volume IV-4/W7 | Copyright
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W7, 51-58, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Sep 2018

20 Sep 2018


L. Gabrielli1, M. Rossi2, F. Giannotti1, D. Fadda1, and S. Rinzivillo1 L. Gabrielli et al.
  • 1Istituto di Scienza e Tecnologie dell’Informazione (ISTI), Consiglio Nazionale Delle Ricerche (CNR), Pisa, Italy
  • 2Università di Pisa, Italy

Keywords: Data Mining, Big Data, Urban Dashboard

Abstract. The new data sources give the possibility to answer analytically the questions that arise from mobility manager. The process of transforming raw data into knowledge is very complex, and it is necessary to provide metaphors of visualizations that are understandable to decision makers. Here, we propose an analytical platform that extracts information on the mobility of individuals from mobile phone by applying Data Mining methodologies. The main results highlighted here are both technical and methodological. First, communicating information through visual analytics techniques facilitates understanding of information to those who have no specific technical or domain knowledge. Secondly, the API system guarantees the ability to export aggregates according to the granularity required, enabling other actors to produce new services based on the extracted models. For the future, we expect to extend the platform by inserting other layers. For example, a layer for measuring the sustainability index of a territory, such as the ability of public transport to attract private mobility or the index that measures how many private vehicle trips can be converted into electrical mobility.

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