movr: Human Mobility Analysis in R

Analyzing and Visualizing Human Mobility Data in R

movr is an R package that provides comprehensive tools for analyzing and visualizing spatio-temporal human mobility data. It originates from research on human mobility patterns and offers general transformation, calculation, and visualization utilities for mobility analysis.

Installation

From CRAN (Recommended):

install.packages("movr")

From GitHub (Development Version):

# Install devtools if you haven't already
if (!requireNamespace("devtools", quietly = TRUE)) {
  install.packages("devtools")
}

# Install movr from GitHub
devtools::install_github("caesar0301/movr")

Quick Start

# Load the package
library(movr)

# Load example data
data(movement)

# Basic trajectory visualization
plot_traj3d(movement, x = "lon", y = "lat", z = "timestamp")

# Create a flow map
flowmap_data <- flowmap(movement, from = "origin", to = "destination")
plot_flowmap(flowmap_data)

Features

• 3D Trajectory Visualization: Interactive 3D plots of mobility trajectories

• Flow Maps: Visualize population movements and migration patterns

• Spatial Analysis: Voronoi tessellation, spatial correlation, and coverage analysis

• Temporal Analysis: Time-of-day patterns, session generation, and temporal entropy

• Statistical Tools: Radius of gyration, entropy measures, and predictability analysis

• Data Quality: Comprehensive data quality assessment and validation tools

Operating System Support

`movr` only supports Linux and macOS systems.

• ✅ Linux: Ubuntu, Debian, and other Linux distributions

• ✅ macOS: All macOS versions (tested on recent releases)

• ❌ Windows: Not supported natively

• 🔄 Windows via WSL: Supported through Windows Subsystem for Linux

Note: We have tested the package on Ubuntu and macOS systems. For Windows users, we recommend using Windows Subsystem for Linux (WSL) with Ubuntu.

Contents:

Documentation

• Installation Guide
  • System Requirements
  • Operating System Support
  • Installation Methods
  • Platform-Specific Instructions
  • Troubleshooting
  • Getting Help
  • Verification
• Quick Start Guide
  • Loading the Package
  • Basic Trajectory Visualization
  • Flow Map Analysis
  • Spatial Analysis
  • Temporal Analysis
  • Data Quality Assessment
  • Advanced Visualizations
  • Next Steps
  • Getting Help
• Examples and Tutorials
  • 3D Trajectory Visualization
  • Flow Maps
  • Spatial Analysis
  • Temporal Analysis
  • Statistical Analysis
  • Data Quality Assessment
  • Coordinate Transformations
  • Utility Functions
  • Sequence Analysis
  • Visualization Gallery
  • Advanced Examples
• API Reference
  • Function Categories
  • Getting Help
  • Function Arguments
  • Data Format
• Contributing to movr
  • Getting Started
  • Development Setup
  • Code Style
  • Making Changes
  • Pull Request Guidelines
  • Testing
  • Documentation
  • Release Process
  • Getting Help

Indices and tables

• Index

• Module Index

• Search Page

Citation

If you use movr in your research, please cite:

@article{CHEN2017464,
  author = {Xiaming Chen and Haiyang Wang and Siwei Qiang and Yongkun Wang and Yaohui Jin},
  title = {Discovering and modeling meta-structures in human behavior from city-scale cellular data},
  journal = {Pervasive and Mobile Computing},
  volume = {40},
  pages = {464--476},
  year = {2017},
  doi = {https://doi.org/10.1016/j.pmcj.2017.02.001},
  url = {https://www.sciencedirect.com/science/article/pii/S1574119217300743}
}