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XFlowMap: Cross-Scale Visualization of Massive Origin-Destination Data

XFlowMap: Cross-Scale Visualization of Massive Origin-Destination Data

Introduction

XFlowMap integrates cross-scale pattern detection, automated generalization, and cartographic design to reveal meaningful structures in massive origin–destination datasets. It identifies salient flows at their appropriate origin and destination scales, without relying on predefined aggregation units. A scan-statistic-based procedure evaluates and generalizes flow clusters, while a new flow symbol represents location, direction, strength, and geographic scale together. The resulting maps reduce clutter while preserving important patterns, supporting comparisons across population groups, travel purposes, or time periods.

Demonstrated with U.S. migration and urban taxi trips, XFlowMap reveal comprehensive flow patterns that conventional methods can obscure. Potential applications extend to commuting, logistics, patient travel, tourism, and trade—where understanding flows across scales can inform transportation planning, service provision, and regional coordination. Its central contribution is making complex movement patterns both analytically meaningful and visually accessible, supporting static communication and interactive exploration.

Related Publications

Guo, D., & Jin, H. (2026). XFlowMap: cross-scale generalization and mapping of massive origin-destination data. Cartography and Geographic Information Science , 1–22

URL DOI
BibTeX 
@article{guoXFlowMapCrossscaleGeneralization2026,
  author = {Guo, Diansheng and Jin, Hai},
  title = {XFlowMap: cross-scale generalization and mapping of massive origin-destination data},
  journal = {Cartography and Geographic Information Science},
  year = {2026},
  pages = {1--22},
  publisher = {Informa UK Limited},
  doi = {10.1080/15230406.2026.2738731},
  url = {https://doi.org/10.1080/15230406.2026.2738731},
}

Zhu, X., Guo, D., Koylu, C., & Chen, C. (2019). Density-based multi-scale flow mapping and generalization. Computers, Environment and Urban Systems , 77, 101359

URL DOI
BibTeX 
@article{zhu2019density,
  author = {Zhu, Xi and Guo, Diansheng and Koylu, Caglar and Chen, Chongcheng},
  title = {Density-based multi-scale flow mapping and generalization},
  journal = {Computers, Environment and Urban Systems},
  year = {2019},
  volume = {77},
  pages = {101359},
  eid = {101359},
  publisher = {Elsevier BV},
  doi = {10.1016/j.compenvurbsys.2019.101359},
  url = {https://doi.org/10.1016/j.compenvurbsys.2019.101359},
}

Guo, D., & Zhu, X. (2014). Origin-Destination Flow Data Smoothing and Mapping. IEEE Transactions on Visualization and Computer Graphics , 20(12), 2043–2052

URL DOI
BibTeX 
@article{guo2014origin,
  author = {Guo, Diansheng and Zhu, Xi},
  title = {Origin-Destination Flow Data Smoothing and Mapping},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2014},
  volume = {20},
  number = {12},
  pages = {2043--2052},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tvcg.2014.2346271},
  url = {https://doi.org/10.1109/tvcg.2014.2346271},
}

Koylu, C., & Guo, D. (2017). Design and evaluation of line symbolizations for origin–destination flow maps. Information Visualization , 16(4), 309–331

URL DOI
BibTeX 
@article{koylu2017design,
  author = {Koylu, Caglar and Guo, Diansheng},
  title = {Design and evaluation of line symbolizations for origin–destination flow maps},
  journal = {Information Visualization},
  year = {2017},
  volume = {16},
  number = {4},
  pages = {309--331},
  publisher = {SAGE Publications},
  doi = {10.1177/1473871616681375},
  url = {https://doi.org/10.1177/1473871616681375},
}

Guo, D. (2009). Flow Mapping and Multivariate Visualization of Large Spatial Interaction Data. IEEE Transactions on Visualization and Computer Graphics , 15(6), 1041–1048

URL DOI
BibTeX 
@article{guo2009flow,
  author = {Guo, Diansheng},
  title = {Flow Mapping and Multivariate Visualization of Large Spatial Interaction Data},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2009},
  volume = {15},
  number = {6},
  pages = {1041--1048},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  doi = {10.1109/tvcg.2009.143},
  url = {https://doi.org/10.1109/tvcg.2009.143},
}

Software Download

Download the latest release package for XFlowMap: Cross-Scale Visualization of Massive Origin-Destination Data:

xflowmap_test.zip
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