javari (2025) Vegetation Thresholds and Phase Transitions in Urban Heating of Arid Megacities

Identification

• Journal: Mendeley Data
• Year: 2025
• Date: 2025-12-05
• Authors: javari, Majid
• DOI: 10.17632/w3w3kv8vjm.1

Research Groups

Majid javari (Contributor)

Short Summary

This paper presents a comprehensive dataset, stored in Excel files within a ZIP archive, designed for analyzing vegetation thresholds and phase transitions in urban heating of arid megacities, including raw measurements, preprocessed variables, and model inputs/outputs.

Objective

• To provide a structured and comprehensive dataset for the study of vegetation thresholds and phase transitions in urban heating within arid megacities.

Study Configuration

• Spatial Scale: Urban areas within arid megacities, with data including coordinate and pixel indices, suggesting spatially resolved information.
• Temporal Scale: Temporal attributes (e.g., date) are included, but specific periods or frequencies are not detailed.

Methodology and Data

• Models used: Data includes inputs and outputs for analyses related to Land Surface Temperature (LST), Local Climate Zones (LCZ), and fusion techniques.
• Data sources: Raw measurements, preprocessed variables, and spatial/temporal attributes, compiled into tabular Excel files.

Main Results

• The primary output is a structured dataset, provided in a compressed archive, containing variables essential for analyzing urban climate phenomena, specifically urban heating, vegetation thresholds, and phase transitions in arid megacities.

Contributions

• This work contributes by making a dedicated, structured dataset publicly available, which is crucial for advancing research, modeling, and validation efforts concerning urban heating dynamics and the role of vegetation in arid megacities.

Funding

Not explicitly stated in the provided data description.

Citation

@article{javari2025Vegetation,
  author = {javari, Majid},
  title = {Vegetation Thresholds and Phase Transitions in Urban Heating of Arid Megacities},
  journal = {Mendeley Data},
  year = {2025},
  doi = {10.17632/w3w3kv8vjm.1},
  url = {https://doi.org/10.17632/w3w3kv8vjm.1}
}