Spatial Outlier-Driven Heterogeneity Model Data and Code

263.0 MB of data and code supporting the second-dimension outlier-driven heterogeneity model. The materials were created by authors Kai Ren, Yongze Song, Xinyue Yang, Xi Wang, Min Chen, and Qiang Yu and were last updated on June 1, 2026. The associated research article is published under DOI 10.1080/13658816.2026.2682957.

Use Cases

• Training spatial heterogeneity models based on the described outlier-driven framework.
• Benchmarking outlier detection algorithms on geospatial data.
• Reproducing the research findings from the associated article using the provided code and data.

Strengths

• Dataset size is 263.0 MB, indicating substantial material.
• Includes multiple file formats (XML, PDF, MD, CPG, SHP, R, DBF, SHX, SBN, JS, CSV, PRJ, SBX, RDA) for different use cases.
• Openly licensed under CC-BY-4.0 for reuse.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Collection Method

Data and code supporting a published research article.

Freshness

Last updated 2026-06-01 09:47:00; freshness should be verified.