pygeoglim 1.0.4

A Python package for extracting geological attributes from GLiM and GLHYMPS datasets

pygeoglim

pygeoglim is a Python package for extracting geology attributes—specifically lithological and hydrogeological properties—from GLiM and GLHYMPS datasets for any region or watershed in CONUS region. It is built for use in hydrological modeling, large-sample hydrology, and Earth system research.

📋 Table of Contents

• Installation
• Quick Start
• Extracted Attributes
• Data Sources
• Requirements
• Citation
• License
• Author

📦 Installation

From PyPI (Recommended)

pip install pygeoglim

From GitHub

pip install git+https://github.com/galib9690/pygeoglim.git

Development Mode

git clone https://github.com/galib9690/pygeoglim.git
cd pygeoglim
pip install -e .

🚀 Quick Start

Basic Usage

from pygeoglim import load_geometry, glim_attributes, glhymps_attributes

# Load geometry from bounding box
geom = load_geometry(bbox=[-85.5, 39.5, -85.0, 40.0])

# Extract lithology attributes (GLiM)
glim = glim_attributes(geom)

# Extract hydrogeology attributes (GLHYMPS)
glhymps = glhymps_attributes(geom)

# Combine results
attributes = {glim, glhymps}
print(attributes)

Using Shapefile Input

You can also pass a shapefile path instead of a bounding box:

# Load geometry from shapefile
geom = load_geometry(shapefile="path/to/watershed.shp")

# Extract attributes
glim = glim_attributes(geom)
glhymps = glhymps_attributes(geom)

📊 Extracted Attributes

Lithology (GLiM Dataset)

Attribute	Description
geol_1st_class	Dominant lithology class
glim_1st_class_frac	Fraction of dominant class
geol_2nd_class	Second most common lithology class
glim_2nd_class_frac	Fraction of second most common class
carbonate_rocks_frac	Fraction of carbonate rocks

Hydrogeology (GLHYMPS Dataset)

Attribute	Description	Units
geol_porosity	Area-weighted porosity	fraction
geol_permeability	Area-weighted permeability	log₁₀ m²
geol_permeability_linear	Permeability (linear scale)	m²
hydraulic_conductivity	Hydraulic conductivity	m/s

🌍 Data Sources

GLiM – Global Lithological Map

• Citation: Hartmann, J., & Moosdorf, N. (2012). The new global lithological map database GLiM: A representation of rock properties at the Earth surface. Geochemistry, Geophysics, Geosystems, 13, Q12004.
• DOI: 10.1029/2012GC004370
• Dataset DOI: 10.1594/PANGAEA.788537

GLHYMPS – Global Hydrogeology Maps

• Citation: Gleeson, T., Moosdorf, N., Hartmann, J., & Van Beek, L. P. H. (2014). A Glimpse Beneath Earth's Surface: Global Hydrogeology Maps (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891–3898.
• DOI: 10.1002/2014GL059856

📋 Requirements

• Python ≥ 3.8
• geopandas ≥ 0.12
• shapely ≥ 1.8
• numpy ≥ 1.20
• pandas ≥ 1.3

📖 Citation

If you use this package in your research, please cite:

@software{galib2025pygeoglim,
  author = {Galib, Mohammad},
  title = {pygeoglim: A Python package for extracting geological attributes from GLiM and GLHYMPS datasets},
  url = {https://github.com/galib9690/pygeoglim},
  year = {2025}
}

Please also cite the original datasets (GLiM and GLHYMPS) as referenced in the Data Sources section.

🐛 Issues and Support

If you encounter any problems or have questions:

• Check the Issues page
• Create a new issue with a detailed description
• Include your Python version, package version, and error messages

🤝 License

Distributed under the MIT License. See LICENSE for more information.

👨‍💻 Author

Mohammad Galib
Purdue University

• 📧 Email: [[e-mail]]
• 🌐 GitHub: @galib9690
• 🏛️ Institution: Purdue University

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