human-mobility

scikit-mobility: mobility analysis in Python

a PyTorch implementation of the paper "Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information"

Thanks to the proliferation of smart devices, such as smartphones and wearables, which are equipped with computation, communication and sensing capabilities, a plethora of new location-based services and applications are available for the users at any time and everywhere. Understanding human mobility has gain importance to offer better services …

[IEEE TITS 2024] Activity-aware human mobility prediction with hierarchical graph attention recurrent network.

[SIGSPATIAL 2026] Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks

This is a list of useful information about urban mobility prediction. Related papers, datasets and codes are included.

a Python package designed to facilitate access to this mobility data and associated spatial tessellations, while standardizing the data for ease of use and analysis. As easy as pip install pyspainmobility

Urban Dynamics Through the Lens of Human Mobility

This repository contains the code for the paper "ST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility Prediction".

Analyzing and Visualizing Human Mobility Data in R

Improving Next Location Prediction with Inferred Activity Semantics in Mobile Phone Data

Advances on human mobility science, covering the reading list of recent top academic conferences.

PyTorch implementation of the paper-"Human Mobility Prediction with Causal and Spatial-constrained Multi-task Network"

Collect and filter location information from social network services.

[NeurIPS 2025] RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility

Bias adjustment for mobile-phone-derived mobility data

sparkmobility: processing large human mobility dataset with Spark

Framework for modelling dynamical complex systems

A SLAW mobility simulator based on the OMNeT++ and INET frameworks