grtsdb

Spatially balanced sampling based on the General Randomized Tessellation Stratified (GRTS) using R and SQLite

https://github.com/inbo/grtsdb

Keywords

Repository

Spatially balanced sampling based on the General Randomized Tessellation Stratified (GRTS) using R and SQLite

README.Rmd

---
output: github_document
---



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

# grtsdb


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The goal of `grtsdb` is to create a spatially balanced sample based on the 'Generalised Random Tesselation Stratified' strategy.
We store the base schema in an SQLite database to make the sampling reproducible.
Sampling the same database with the same parameters yields a stable sample.

## Installation

To install the latest stable version use

``` r
# activate the INBO r-universe
options(
  repos = c(
    INBO = 'https://inbo.r-universe.dev', CRAN = 'https://cloud.r-project.org'
  )
)
install.packages("grtsdb")
```

You can install the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("remotes")
remotes::install_github("inbo/grtsdb")
```

## Example

This is a basic example.

Connect to a database.

```{r}
tmp_copy <- tempfile(pattern = "grts", fileext = ".sqlite")
if (system.file("grts.sqlite", package = "grtsdb") != "") {
  file.copy(system.file("grts.sqlite", package = "grtsdb"), tmp_copy)
}
library(grtsdb)
db <- connect_db(tmp_copy)
```

To extract a sample, you'll need to specify the bounding box in projected coordinates and the size of the grid cells.

```{r example}
bbox <- rbind(
  c(0, 32),
  c(0, 32)
)
extract_sample(grtsdb = db, samplesize = 10, bbox = bbox, cellsize = 1)
```

Repeating the sample yields the same results.

```{r}
extract_sample(grtsdb = db, samplesize = 10, bbox = bbox, cellsize = 1)
```

```{r echo = FALSE}
drop_legacy_sites(grtsdb = db, level = 5)
```

You can add legacy sites to the sampling scheme.

```{r}
legacy <- rbind(
  c(4, 4),
  c(17, 6)
)
add_legacy_sites(legacy, bbox = bbox, cellsize = 1, grtsdb = db)
extract_legacy_sample(grtsdb = db, samplesize = 10, bbox = bbox, cellsize = 1)
```

You can compact the database for storage.

```{r}
compact_db(db)
```

Disconnect the database when done.

```{r}
dbDisconnect(db)
```

```{r eval = system.file("grts.sqlite", package = "grtsdb") == "", echo = FALSE}
dir.create("inst", showWarnings = FALSE)
file.copy(tmp_copy, file.path("inst", "grts.sqlite"))
```

Owner

Citation (CITATION.cff)

cff-version: 1.2.0
message: If you use this software, please cite it as below.
authors:
- family-names: Onkelinx
  given-names: Thierry
  orcid: https://orcid.org/0000-0001-8804-4216
- family-names: De Vos
  given-names: Bruno
  orcid: https://orcid.org/0000-0001-9523-3453
contact:
- email: thierry.onkelinx@inbo.be
  family-names: Onkelinx
  given-names: Thierry
- email: info@inbo.be
  name: Research Institute for Nature and Forest
title: 'grtsdb: Create a Sampling Frame Using GRTS'
version: '0.2'
abstract: Create an SQLite database containing the sampling framework for different
  levels of resolution. Take a sample from this framework.
license: GPL-3.0
type: software
repository-code: https://github.com/inbo/grtsdb
identifiers:
- type: url
  value: https://inbo.github.io/grtsdb/

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