Semantic Segmentation and Space Syntax Analysis for Urban Monitoring

Alper Gönül's dataset integrates semantic segmentation of street-level views with space syntax analysis of street network configurations. The 5.1 MB dataset is available in XLS and XLSX formats under a CC-BY-4.0 license. It was last updated on June 2, 2026.

Use Cases

• Train models for automated urban feature detection based on street-level semantic segmentation.
• Analyze the relationship between street network configuration and visual perception using space syntax metrics.
• Benchmark technology-driven urban monitoring methods that integrate visual and network data.

Strengths

• Dataset is 5.1 MB, indicating a manageable size for initial exploration.
• Available under a permissive CC-BY-4.0 license, allowing for broad reuse and modification.
• Integrates two distinct technology-driven methods for urban analysis, as described.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• 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

Alper Gönül via figshare

Collection Method

Likely generated by integrating semantic segmentation of street-level imagery with space syntax analysis of street networks.

Freshness

Last updated 2026-06-02 16:25:59; freshness should be verified.