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# cleangeo quickstart guide

The goal of this document is to get you up and running with **cleangeo** as quickly as possible.

**cleangeo** was initially born from some assistance provided to users that were facing issues in processing spatial data in R (see the original post at <https://gis.stackexchange.com/questions/113964/fixing-orphaned-holes-in-r>).

The main problem with their data is that some spatial objects did not have valid geometries, exposing different types of geometry errors, preventing any easy spatial data processing. Then, **cleangeo** was built in order to facilitate handling and catching geometry issues, and provide an utility to _clean_ the spatial objects.

This short document shows you how to inspect spatial objects, and clean them with **cleangeo**.

## Install cleangeo

``cleangeo`` is available for download from CRAN. To get the latest ``cleangeo`` you can install it from its development repository hosted in Github. For this, you will need the ``devtools`` package and run:

```{r, eval=FALSE}
remotes::install_github("eblondel/cleangeo")
```

## Load cleangeo

To load the package in R, do the following:

```{r}
library(cleangeo)
```

## Work with cleangeo

Let's load the package and read some some test spatial objects.

```{r}
file <- system.file("extdata", "example.shp", package = "cleangeo")

require(sf)
sf <- sf::st_read(file)
sp <- as(sf, "Spatial")
```

The next step is to _inspect_ these spatial objects, in order to detect potential geometry issues, and make a ``summary``:

```{r}
report <- clgeo_CollectionReport(sp)
clgeo_SummaryReport(report)
```

By analysing this report, you will see that 2 of the 3 spatial objects are not valid. The issues deal with a problem of _geometry validity_. Quite interesting to have such comprehensive report, but _how to fix these issues?_ This is where **cleangeo** can really help you! so let's try to **clean** these spatial objects.

The below one-line code uses ``clgeo_Clean`` on our spatial objects.

```{r}
sp.clean <- clgeo_Clean(sp)

```

And now? Well, let's check the new spatial objects!

```{r}
report.clean <- clgeo_CollectionReport(sp.clean)
clgeo_SummaryReport(report.clean)

```