paar/README.Rmd at main · PPaccioretti/paar · GitHub

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---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

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

# paar <a href="https://ppaccioretti.github.io/paar/"><img src="man/figures/logo.png" align="right" height="139" alt="paar website" /></a>


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The goal of `paar` is to provide useful tools for cleaning and processing spatial data in precision agriculture.

## Installation

You can install the released version of paar from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("paar")
```
You can install the development version from [GitHub](https://github.com/PPaccioretti/paar) with:

``` r
# install.packages("pak")
pak::pkg_install("PPaccioretti/paar")
```

## Example

The package provides a complete protocol for automated error removal.
Default values of all functions are optimized for precision agriculture data.

```{r example, message=FALSE}
library(paar)
library(sf)
data("barley", package = 'paar')
```

The `barley` dataset contains grain yield data collected were using calibrated commercial yield monitors, mounted on combines equipped with DGPS.

```{r barley}
#Convert barley data to an spatial object
barley_sf <- st_as_sf(barley, coords = c("X", "Y"), crs = 32720)

barley_dep <-
  depurate(barley_sf, "Yield")

# Summary of depurated data
summary(barley_dep)
```

Spatial yield values before and after the depuration process can be visualized

```{r, fig.height=2, fig.height=5, out.width="50%", fig.show="hold"}
plot(barley_sf["Yield"], main = "Before depuration")
plot(barley_dep$depurated_data["Yield"], main = "After depuration")
```

The distribution of yield values can also be compared

```{r, fig.height=2, fig.height=5, out.width="50%", fig.show="hold"}
boxplot(barley_sf[["Yield"]], main = "Before depuration")
boxplot(barley_dep$depurated_data[["Yield"]], main = "After depuration")
```


## References

- Vega, A., Córdoba, M., Castro-Franco, M. et al. (2019). Protocol for automating error removal from yield maps. Precision Agric 20, 1030–1044  https://doi.org/10.1007/s11119-018-09632-8
- Paccioretti, P., Córdoba, M., & Balzarini, M. (2020). FastMapping: Software to create field maps and identify management zones in precision agriculture. Computers and Electronics in Agriculture, 175, 105556 https://doi.org/10.1016/j.compag.2020.105556.