Urban Green Space Supply-Demand Mismatches in Nanjing, China

Nanjing's central urban area in 2022 is analyzed for urban green space supply, demand, and spatial mismatches across traffic analysis zones (TAZs). The dataset likely contains metrics quantifying mismatches and urban morphological drivers, developed by Lijuan Sun. It was last updated on March 18, 2026.

Use Cases

• Identify green space deficits and surpluses based on traffic analysis zone data.
• Analyze urban morphological drivers of spatial inequities based on metrics like urban compactness and floor area ratio.
• Model the relationship between public facility coverage and green space supply-demand balance.
• Evaluate governance strategies for equity-oriented green space planning based on spatial mismatch quantification.

Strengths

• Data is specific to the central urban area of Nanjing in 2022.
• Analysis includes 48 TAZs with severe deficits and 203 TAZs with evident surpluses.
• An explainable machine learning model (XGBoost–SHAP) was applied to identify drivers.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to a single city case study.

Provenance

Source

figshare

Collection Method

Developed as part of a study quantifying UGS supply, demand, and spatial mismatches.

Time Range

2022

Freshness

Last updated 2026-03-18 17:24:47; freshness should be verified.

Geography

Central urban area of Nanjing, China.