Large-scale digital mapping of soil organic carbon content by using machine learning algorithms

Soil Sample and Soil Profile Datasets: an Open Compilation

Repository of Jupyter notebooks aimed at learning how to use Python to retrieve data from Google Earth Engine

Open datasets for crop modeling describing climate and soil in France.

Code for analysis of soils, crops, and nutrition along a distance-to-forest gradient in Ethiopia

SWAT+ model input data preparation helper

The scripts contained in this repository relate directly to the work conducted by the Tree Root Microbiome Project (TRMP) led by Dr Steve Wakelin.

🌱A machine learning web and mobile application for soil type classification for plant decision making

Comparing different data preprocessing methods to predict soil organic carbon content on soil spectra features

Ongoing research on several projects..

MASSAI multi-agent simulation of sustainable agricultural intensification

Rhizosphere interactions under diverse canola genotypes: a key component in nitrogen use efficiency

Published original data and R code from “Above- and belowground plant pathogens along elevational gradients: patterns and potential mechanisms”

Brassica napus root and rhizosphere microbial nitrogen processing impacts on nitrogen use efficiency

The soil mate app provides a simple and convenient way to collect soil data at sample locations in the field. The Soil Mate app is targeted across multiple industries, including agriculture, environmental science, geology, and mining. The current version of the app collects soil texture data.

simple tool to find intersections

SCMA work now in https://github.com/ANZSoilData/def-au-scma

A university project that aims to explore various data mining techniques like Data Exploration, Association Rule Mining, Supervised and Unsupervised Learning, applied to real-world datasets, focusing on soil fertility analysis and COVID-19 cases evolution over time.

Soil Data Access Scripts

Reproducible Research Compendium for "Improving Models to Predict Holocellulose and Klason Lignin Contents for Peat Soil Organic Matter with Mid-Infrared Spectra" and "The need to reinterpret Hodgkins et al. (2018)".