Mobilkit: A Python Toolkit for Urban Resilience and Disaster Risk Management Analytics using High Frequency Human Mobility Data

Ubaldi, Enrico, Yabe, Takahiro, Jones, Nicholas, Khan, Maham Faisal, Alessandra, Feliciotti, Di Clemente, Riccardo, Ukkusuri, Satish V. and Strano, Emanuele (2024) Mobilkit: A Python Toolkit for Urban Resilience and Disaster Risk Management Analytics using High Frequency Human Mobility Data. Journal of Open Source Software (9). p. 5201.

Abstract

Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and response to natural disasters. However, limited tools exist to enable rapid analytics using mobility data, and tend not to be tailored specifically for disaster risk management. We present an open-source, Python-based toolkit designed to conduct replicable and scalable post-disaster analytics using GPS location data. Privacy, system capabilities, and potential expansions of \textitMobilkit are discussed.

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Official URL:	https://doi.org/10.21105/joss.05201
Item Type:	Article
Disciplines:	Network Science
Depositing User:	Riccardo Di Clemente
Date Deposited:	13 Mar 2024 11:24
Last Modified:	16 May 2024 12:17
URI:	https://nul.repository.guildhe.ac.uk/id/eprint/328

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