index.Rmd

--- 
title: "Soil Predictions using MIR-Spectroscopy"
site: bookdown::bookdown_site
documentclass: book
bibliography: [book.bib, packages.bib]
biblio-style: apalike
link-citations: yes
description: ""
---

```{r include=FALSE}
# automatically create a bib database for R packages
knitr::write_bib(c(
  .packages(), 'bookdown', 'knitr', 'rmarkdown'
), 'packages.bib')
```

# Introduction
![](./images/soil-pic.png)

This guide documents the use of MIR-spectroscopy at the **Woods Hole Research Center**, to predict various soil health properties. It is aimed at helping other teams build soil spectral libraries, create models from their data, access model performance against known values, and ultimately make predictions on new data. The machine learning methods outlined in this document were selected after assessing the performance of a variety of models. This process is explained in the following paper: 

*Dangal S.R.S., J. Sanderman, S. Wills, and L. Rameriz-Lopez. 2019. [Accurate and Precise Prediction of Soil Properties from a Large Mid-Infrared Spectral Library](https://www.mdpi.com/2571-8789/3/1/11). Soil Systems 3(1):11. doi:10.3390/soilsystems3010011*

Questions and comments can be sent to jsanderman@whrc.org or crivard@whrc.org    

![Jonathan Sanderman](./images/jsanderman.png)     ![Shree Dangal](./images/sdangal.png)     ![Charlotte Rivard](./images/crivard.png)


**Woods Hole Research Center**    
Website: [whrc.org](https://whrc.org/)    
Instagram: [woodsholeresearchcenter](https://www.instagram.com/woodsholeresearchcenter/)    
Address: 149 Woods Hole Rd, Falmouth, MA 02540      

![](./images/logo2.png)