LAI: Ground-Based and Sentinel-2 Leaf Area Index Data

Ground-based Leaf Area Index (LAI) data from ENON and Nakakawane, paired with corresponding cloud-free Sentinel-2 satellite imagery. The dataset was authored by Xuanwen Wang and last updated on June 4, 2026. It is a small dataset of 806.9 KB, stored in CSV format.

Use Cases

• Train machine learning models to predict LAI from satellite reflectance data based on the ground-truth pairs.
• Validate satellite-derived LAI products using the provided ground-based measurements.
• Analyze the relationship between ground-observed vegetation indices and satellite sensor data.
• Develop calibration methods for Sentinel-2 imagery in specific geographic contexts.

Strengths

• Data pairs ground-truth LAI measurements with satellite imagery, enabling validation.
• Published under a permissive CC-BY-4.0 license for broad reuse.
• Last updated in 2026, suggesting recent maintenance.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The small file size (806.9 KB) indicates a limited scope, likely covering only specific sites.

Provenance

Source

Xuanwen Wang via figshare.

Collection Method

Likely involves field measurement collection and matching with satellite data processing.

Freshness

Last updated 2026-06-04 04:46:00; freshness should be verified.

Geography

Locations named ENON and Nakakawane.