patmejia/soil_spectra_ml

ML-driven network for precise clay content prediction from MIR soil spectra

soil spectra ml

predictive clay mineral in soil spectroscopy

soilspectraml is an open-source initiative aimed at developing machine learning models for predictive soil spectroscopy, with a focus on accurate clay content prediction from mid-infrared (mir) soil spectra.

overview

find a quick overview of soil spectroscopy and the ss4gg hackathon here.

this image illustrates the size-based classification of soil minerals, highlighting the distinctive attributes of clay in terms of texture, water retention, and nutrient interaction.

objective

develop a machine learning model to accurately predict soil clay content across diverse mir instruments, using root mean squared error (rmse) as the performance metric.

download Data

a. authenticate with kaggle api:

• see this article for instructions on how to authenticate with the kaggle api:

c. download dataset:

• run the following command to download the dataset:

  cd data/raw
  kaggle competitions download -c ss4gg-hackathon-mir-soil-spectroscopy

• this command downloads the dataset for the ss4gg-hackathon-mir-soil-spectroscopy competition to the current directory (i.e., data/raw/).

features

• clay content prediction: utilizes mir soil spectroscopy for precise clay content estimation.
• interoperable models: ensures model consistency and accuracy across diverse mir instruments.
• open soil spectral library ossl utilization: leverages the ossl for robust model training and evaluation.
• machine learning framework: incorporates a modular ml framework allowing easy model iteration and evaluation.

getting started

1. prerequisites:
2. installation:
3. dataset:
4. training models:
5. model evaluation:

usage

documentation

contribution

we welcome contributions, bug reports, and feature requests. please refer to the contributing.md file for guidelines.

license

this project is licensed under the mit license. see the license.md file for details.

contact

• repository: https://github.com/patmejia/soil_spectra_ml
• issue tracker: https://github.com/patmejia/soil_spectra_ml/issues

acknowledgements

• ss4gg hackathon: mir soil spectroscopy modeling by zecojls, kaggle, 2023. link

• cookiecutter data science for the project structure guidelines