Dataset for A Source–Medium–Receiver Framework for Modelling Wind-Driven Vegetation Coolin

Processed remote sensing, meteorological, and topographic variables for analyzing Land Surface Temperature (LST) relationships. The 184.8 MB dataset contains 17 parameters covering vegetation dynamics, urban built-up features, water indices, surface reflectance, atmospheric factors, and terrain characteristics. Author Hassan Qasim published the data on figshare under a CC-BY-4.0 license, last updated in May 2026.

Use Cases

• Modeling wind-driven vegetation cooling effects in cities based on remote sensing and meteorological variables.
• Analyzing the relationship between urban built-up features and Land Surface Temperature variations.
• Evaluating how water indices and surface reflectance influence local temperature patterns.
• Investigating the impact of terrain characteristics on urban heat island effects.

Strengths

• Contains 17 processed parameters spanning remote sensing, meteorological, and topographic domains.
• Covers a multi-year study period from 2021 to 2024.
• Data is structured to evaluate specific relationships with Land Surface Temperature.

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.

Provenance

Source

figshare

Collection Method

Processed from remote sensing, meteorological, and topographic sources.

Time Range

2021 to 2024

Freshness

Last updated 2026-05-19 08:36:11

Geography

Urban landscapes (specific location not stated)