Authors

Approaches

Dataset

Helpful Aspect

Drawback

Tobler, 1987

Flow mapping through arrows.

Migration OD data

First introduced the use of arrows.

Overlapped arrows confuse visualization.

Andreinko & Andreinko, 2008

OD matrix

GPS data

Effective aggregation of movement data.

Region to region spatial information is missing.

Yue et al., 2009

A time-dependent flow interaction matrix

Taxi Trajectory data

Understanding pattern regarding the level of attractiveness.

Pick Up and Drop off point is taken as O & D. So, which segment is being used is not clear.

Wood et al., 2010

Mapping OD vector using a regular grid.

Migration Flow

Representation of region-to-region spatial information

Fails expressing OD flow change.

Wang et al., 2015

Using Eigen lines as discrete OD links

Mobile Phone Record

High penetration rate, wide service area.

Eigen lines are not capable of representing all streets with traffic but only those having obvious traffic.

Wang et al., 2019

Expressing OD characteristic through chord diagram.

Taxi GPS Data

High automation,

Grasp real-time traffic situation.

Pick Up and Drop off point is taken as O & D. So, which segment is being used is not clear.

Liao et al., 2019

Human check-in & trajectory data fusion.

Taxi Trajectory Data

Allows understanding time-evolving trip purpose pattern.

Little Visualization capability, only covers weekly data.

Rizwan et al., 2020

Spatial distribution of human check-in data

LBSN data

Gives insights on human activities over space-time.

Not comprehensive. Only include recorded check-ins which may differ from actual urban flow.

Liu et al., 2022

Flow clustering method.

Taxi Trajectory Data

High-level activity dynamics and travel behavior are expressed on geographic context.

Pick Up and Drop off point is taken as O & D. So, which segment is being used is not clear.