whep

Processing agro-environmental data

https://github.com/eduaguilera/whep

Keywords

Repository

Processing agro-environmental data

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# Who Has Eaten the Planet 


[![R-CMD-check](https://github.com/eduaguilera/whep/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/eduaguilera/whep/actions/workflows/R-CMD-check.yaml)
[![CRAN status](https://www.r-pkg.org/badges/version/whep)](https://CRAN.R-project.org/package=whep)
[![whep status badge](https://eduaguilera.r-universe.dev/whep/badges/version)](https://eduaguilera.r-universe.dev/whep)
[![Codecov test coverage](https://codecov.io/gh/eduaguilera/whep/branch/main/graph/badge.svg)](https://app.codecov.io/gh/eduaguilera/whep?branch=main)


## Project

#### **Who Has Eaten the Planet? The paths of food systems beyond the safe and just operating space (1850-2020)**

Food production covers the most basic human need, and simultaneously is the
main driver of anthropogenic environmental impacts. These impacts have resulted
in the transgression, during the brief period since the industrial revolution,
of the planetary boundaries defining the safe operating space of humanity. A
rich research literature quantifies the last 60 years’ fast, heterogeneous,
and often unfair development in food supply and related environmental impacts,
and how these depend on agro-climatic factors, technology, and trade flows, all
of which have greatly changed but with different trajectories around the world.
However, these developments lack an integrated approach, and are very poorly
quantified before 1961. WHEP will bridge these knowledge gaps, assessing "who
has eaten the planet" by answering the questions: 

> What are the environmental impacts of food production since 1850?

> What is the role of trade in food supply and in displacing the responsibilities for these impacts?

> How are impacts related to planetary boundaries, food supply and inequality?

These highly ambitious goals are addressed by four objectives: 

1. Constructing a consolidated global country-level annual database on
    agricultural production and management, using massive data collation in
    combination with modeling.
2. Estimating the environmental impacts: greenhouse gas emissions and carbon,
    land, water, nitrogen, and phosphorus through spatially explicit,
    integrated, dynamic modeling.
3. Calculating product footprints and tracing them along international trade
    chains.
4. Analyzing the observed trajectories in the safe and just operating space,
    by assessing the drivers, and how impacts at the production and consumption
    levels are related to fair and healthy supply. This ground-breaking
    research will shed new light on the environmental history of food, opening
    up many new research frontiers, and providing necessary information to
    design fair and sustainable policies.

You can also visit the [European project site](https://cordis.europa.eu/project/id/101115126).

## R package

The WHEP project heavily relies on data. We use the R programming language.
This repository is built as an R package containing functionality that we
think might be useful to share to others as part of the project. This will
also include functions for easily downloading the data gathered by the project.

## Installation

The package is under constant development. Initial stable releases are
available from both CRAN and [R-universe
](https://eduaguilera.r-universe.dev/whep).

You can install the stable version on CRAN:

``` r
install.packages('whep')
```

If you want the development version of `whep`, you can:

``` r
# Install from GitHub
pak::pak("eduaguilera/whep")

# Install from R-universe
install.packages(
  "whep",
  repos = c("https://eduaguilera.r-universe.dev", "https://cloud.r-project.org")
)
```

## Usage

You can read more about the package's functionalities from the documentation
at the [reference page](https://eduaguilera.github.io/whep/reference/index.html).

## Contributing

We try to follow best coding practices, specifically focused on R package
creation. The process is roughly summarized in:

- Use git. Work on your own branch.
- Track dependencies using `renv` R package.
- Add your new functionality inside `R/` directory as functions.
- Add function documentation.
- Write clean code. Follow [Tidyverse style guide](https://style.tidyverse.org/).
- Write tests for your code.
- Create pull requests. Ask for review.

The project is starting with **contributors** that are still learning about
coding and best practices. For this reason, if you're **inexperienced**, we have
written a **small free online book** explaining most of the things you need from
the previous steps, covering both git and R package development. You can
directly **access it [here](https://lbm364dl.github.io/follow-the-workflow)**.
Anyone is welcome to contribute, but we highly recommend to go through this
guide to become familiar with the workflow if you are still not used to it.

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