Spatial Correlation Network of Agricultural Carbon Emissions in China, 2015-2023

Panel data for 31 provinces in China from 2015 to 2023, used to construct a spatial correlation network of agricultural carbon emissions. The dataset was created by Jiasheng He and employs a modified gravity model and social network analysis to examine network characteristics and driving factors. It was last updated on 2026-04-26.

Use Cases

• Analyze spatial correlation patterns of agricultural carbon emissions based on the constructed network.
• Identify key provinces and regional functional differentiation based on node-level network features.
• Model the influence of factors like spatial adjacency and income differences on network formation based on the Quadratic Assignment Procedure analysis.

Strengths

• Covers a 9-year time range from 2015 to 2023.
• Includes data for all 31 provinces in China, suggesting no isolated nodes in the network.
• Analysis identifies specific central provinces (e.g., Hubei, Henan) within the spatial network.

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 its focus on Chinese provinces.

Provenance

Source

figshare, author Jiasheng He

Collection Method

Constructed from panel data using a modified gravity model and social network analysis.

Time Range

2015-2023

Freshness

Last updated 2026-04-26 09:30:55; freshness should be verified.

Geography

31 provinces in China