NumSpecL: Satellite Observation Data for Atmospheric Correction Research

Experimental datasets supporting research on overcoming atmospheric limitations in satellite imagery. The 2.9 GB collection, published by dongyi li under a CC-BY-4.0 license, includes TIF and XLSX files. It was last updated on June 2, 2026.

Use Cases

• Developing atmospheric correction models based on spectral learning techniques mentioned in the description
• Benchmarking numerical optimization methods for processing satellite data
• Training machine learning models to compensate for atmospheric window limitations
• Analyzing the performance of coupled optimization and learning approaches for remote sensing

Strengths

• Dataset size is explicitly 2.9 GB, indicating a substantial volume of data.
• Files are provided in both geospatial (TIF) and structured (XLSX) formats, suggesting multimodal utility.
• License is clearly stated as CC-BY-4.0, allowing for broad reuse.

Limitations

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

Provenance

Source

dongyi li

Collection Method

Experimental datasets used in a specific research manuscript.

Freshness

Last updated 2026-06-02 07:19:40; freshness should be verified.