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Privacy Risk on Trajectories
This method provides a Privacy Risk Assessment on mobility data, in terms of trajectories or aggregation of trajectories, i.e., locations with frequency of visit and locations...-
Python
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Python
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Sociometer
The Sociometer is an analytical framework based on data mining methods that analizes users’ call habits, and classifies people into behavioral categories, among residents,...-
PDF
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PDF
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TAR
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PDF
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Origin Destination Matrix Computation
This method provides the sql-postgis query to calculate the Origin-Destination matrix starting from a geometry table and a set of GPS trajectories. This kind of matrix, which...-
sql
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sql
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STS-EPR: Modelling individual mobility considering the spatial, temporal, and...
Modelling human mobility is crucial in several scientific areas, from urban planning to epidemic modeling, traffic forecasting, and what-if analysis. On the one hand, existing... -
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HTML
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HTML
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Simulation of individual mobility using STS-EPR
In this experiment we simulate the mobility of individuals in New York City, London, and Tokyo, using STS-EPR. For each city, we compare the synthetic trajectories generated...-
PDF
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PDF
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Matlas - TClustering
Ordering points to identify the clustering structure (OPTICS) is an algorithm for finding density-based clusters in spatial data. Its basic idea is similar to DBSCAN, but it...-
HTML
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HTML
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Mobility data sharing: application potential and ethical issues webinar
4th SoBigData++ Awareness Panel Webinar Programme Decentralized anonymization of mobility data Speaker: Josep Domingo-Ferrer (Universitat Rovira i Virgili, Catalonia)... -
Automating and utilizing equal-distribution data classification
Data classification, i.e., organising data items in groups (classes), is a general technique widely used in data visualisation and cartography, in particular, for creation of...-
PDF
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PDF
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Changes of mobility routines during the COVID-19 pandemic
Non-Pharmaceutical Interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, have dramatically influenced our everyday behaviour. This method allows to... -
Exploration of time use by citizens based on their movement tracks
This resource consists of a visual analytics framework and a set of supporting tools for deriving place meaning and reconstructing personal mobility diaries from episodic...-
PDF
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mp4
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rep
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PDF
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Mobility-emissions
A collection of methods (relying on the scikit-mobility and OSMnx Python libraries) to compute emissions starting from vehicles' mobility trajectories. In particular, methods...-
GitHub
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GitHub
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Deep Gravity model
Deep Gravity is an effective model to generate flow probabilities that exploits many features (e.g., land use, road network, transport, food, health facilities) extracted from... -
Validation of the Deep Gravity model
We conducted experiments on mobility flows in England, Italy, and New York State to show that Deep Gravity achieves a significant increase in performance, especially in... -
Co Bridges Pair wise Visual Connection and Comparison for Multi item Data Str...
In various domains, there are abundant streams or sequences of multi-item data of various kinds, e.g. streams of news and social media texts, sequences of genes and sports...-
PDF
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PDF
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Geo-semantic-parsing AI-powered geoparsing by traversing semantic knowledge g...
Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus... -
Scikit-mobility
Scikit-mobility is a library for human mobility analysis in Python. The library allows to: represent trajectories and mobility flows with proper data structures, TrajDataFrame...-
URL
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URL