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
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Updated
Jun 2, 2022 - R
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
Course material for LSU AGRO 4092: R for Spatial Analysis & Visualization
Welcome to the Geographic AI for Soil Assessment gaia interface, your ultimate companion in Predicting and visualizing soil microbial biodiversity.
Ongoing research on several projects..
This repository collects material (code, presentation, images, test data) prepared for the webinar series of the Excalibur H2020 Training
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.
This Repository compared which models and feature selection combination is best to use on SOC content prediction using Environmental Covariate.
An R implementation of the DSMART algorithm
Used simple linear regression to analyze the relationship between soil nutrient supply rates and hop alpha acid content and presented a research poster at an undergraduate research symposium.
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
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 is a model of an aerobic high resolution incubation setup considering Henry's Law
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.
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).
A proof of concept of how a holistic data-driven approach could be used to make better future planning decisions for land zoning.
The scripts contained in this repository relate directly to the work conducted by the Tree Root Microbiome Project (TRMP) led by Dr Steve Wakelin.
Comparing different data preprocessing methods to predict soil organic carbon content on soil spectra features
Conformal Prediction for Digital Soil Mapping
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