Abdel-Fattah (2025) GEE Script

Identification

• Journal: Mendeley Data
• Year: 2025
• Date: 2025-11-24
• Authors: Abdel-Fattah, Mohamed
• DOI: 10.17632/4vrxpp67m9

Research Groups

• Hainan University
• Zagazig University Faculty of Agriculture

Short Summary

This dataset provides remote sensing products, soil indicators, environmental layers, and an analytical Google Earth Engine (GEE) script to support studies on the integrated framework linking Normalized Difference Vegetation Index (NDVI), soil organic carbon (SOC), and environmental drivers in tropical agroecosystems.

Objective

• To provide a comprehensive, globally-scaled dataset and an associated Google Earth Engine (GEE) script for investigating the integrated framework linking Normalized Difference Vegetation Index (NDVI), soil organic carbon (SOC), and environmental drivers in tropical agroecosystems.

Study Configuration

• Spatial Scale: Global
• Temporal Scale: Not specified in the provided text.

Methodology and Data

• Models used: Random Forest (for predictions), Google Earth Engine (for data preprocessing, indicator computation, statistical analysis, and output generation).
• Data sources: Derived remote sensing products (e.g., for NDVI, rainfall, temperature, land cover), soil indicators (e.g., soil organic carbon).

Main Results

• Provision of a comprehensive dataset including global-scale raster layers for Normalized Difference Vegetation Index (NDVI), soil organic carbon (SOC), rainfall, temperature, and land cover.
• The dataset also includes derived correlation maps (NDVI–SOC, NDVI–rainfall, NDVI–temperature) and Random Forest predictions.
• A full Google Earth Engine (GEE) script is provided for data preprocessing, indicator computation, statistical analysis, and output generation, ensuring reproducibility.

Contributions

• Provides a reproducible framework and comprehensive dataset for global-scale studies on vegetation dynamics, soil carbon, and climate-vegetation interactions, particularly in tropical agroecosystems.
• Facilitates further spatial analysis and comparative global studies by offering georeferenced raster files (EPSG:4326) and an open-source GEE script.

Funding

• Not specified in the provided text.

Citation

@article{AbdelFattah2025GEE,
  author = {Abdel-Fattah, Mohamed},
  title = {GEE Script},
  journal = {Mendeley Data},
  year = {2025},
  doi = {10.17632/4vrxpp67m9},
  url = {https://doi.org/10.17632/4vrxpp67m9}
}