Welcome to the Geographic AI for Soil Assessment gaia interface, your ultimate companion in Predicting and visualizing soil microbial biodiversity.
-
Updated
Aug 3, 2024 - Jupyter Notebook
Welcome to the Geographic AI for Soil Assessment gaia interface, your ultimate companion in Predicting and visualizing soil microbial biodiversity.
A package to support sediment source fingerprinting studies: characterising your dataset, selecting tracers (three-step method), modelling source contribution (BMM) and assessing the quality of modelling predictions using virtual mixtures (support BMM and MixSIAR).
Expandable And Scalable Infrastructure for Finite Element Methods, EASIFEM, is [Modern Fortran](https://fortran-lang.org) framework for solving partial differential equations (PDEs) using finite element methods. EASIFEM "eases" the efforts to develop scientific programs in Fortran.
This is a model of an aerobic high resolution incubation setup considering Henry's Law
Ongoing research on several projects..
A set of hands-on coding exercises to solve common tasks and simple problems in agricultural sciences.
Course material for LSU AGRO 4092: R for Spatial Analysis & Visualization
The scripts contained in this repository relate directly to the work conducted by the Tree Root Microbiome Project (TRMP) led by Dr Steve Wakelin.
Soil Sample and Soil Profile Datasets: an Open Compilation
Conformal Prediction for Digital Soil Mapping
An R implementation of the DSMART algorithm
This Repository compared which models and feature selection combination is best to use on SOC content prediction using Environmental Covariate.
This was a final data project for my isotopes class at Purdue. It might not be perfect because it has being a while and it was one of my first projects using R.
R scripts for predicting soil organic carbon using soil spectral library from visible, near-infrared and shortwave-infrared (VNIR) and middle-infrared (MIR) using LASSO and PLS regression methods and the target-oriented cross-validation strategy.
This repository contains the R code associated with our research paper on soil health practices, developed in collaboration with the Nebraska Healthy Soils Task Force (NE-HSTF).
This repository collects material (code, presentation, images, test data) prepared for the webinar series of the Excalibur H2020 Training
This repository contains files for automated soil sampling selection using the K-Means algorithm in R. The repository is intended for researchers and practitioners interested in automated soil sampling selection using the K-Means algorithm.
Soil Heating in Fire (SheFire) Model: Annotated .Rmd scripts and an R package to build and use a SheFire model for how different soil depths heat and cool during fires
The soilspec package: data and functions for the book 'Soil Spectral Inference with R'
Add a description, image, and links to the soil-science topic page so that developers can more easily learn about it.
To associate your repository with the soil-science topic, visit your repo's landing page and select "manage topics."