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https://github.com/ropensci/mapscanner
R package to print maps, draw on them, and scan them back in
https://github.com/ropensci/mapscanner
maps r-package scan spatial
Last synced: 3 months ago
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R package to print maps, draw on them, and scan them back in
- Host: GitHub
- URL: https://github.com/ropensci/mapscanner
- Owner: ropensci
- License: other
- Created: 2019-06-27T12:55:23.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2024-07-19T15:09:39.000Z (4 months ago)
- Last Synced: 2024-07-21T23:50:34.556Z (3 months ago)
- Topics: maps, r-package, scan, spatial
- Language: R
- Homepage: https://docs.ropensci.org/mapscanner/
- Size: 8.54 MB
- Stars: 88
- Watchers: 11
- Forks: 7
- Open Issues: 6
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Codemeta: codemeta.json
Awesome Lists containing this project
- jimsghstars - ropensci/mapscanner - R package to print maps, draw on them, and scan them back in (R)
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set (
collapse = TRUE,
comment = "#>",
out.width = "100%"
)
```
# mapscanner 
[](https://github.com/ropensci/mapscanner/actions?query=workflow%3AR-CMD-check)
[](https://cran.r-project.org/package=mapscanner/)
[](https://cran.r-project.org/package=mapscanner)
[](https://app.codecov.io/gh/ropensci/mapscanner)
[](https://www.repostatus.org/#active)
[](https://github.com/ropensci/software-review/issues/330)
## What does this package do for me?
`mapscanner` is an **R** package that enables lines drawn by hand on maps to be
converted to spatial objects. The package has two primary functions: one for
producing maps, and one for rectifying hand-drawn lines to the coordinate
system of the original map. The package is intended for use in social surveys
and similar endeavours in which hand-drawn markings on maps need to be
converted to spatial objects. Maps can be either paper- or screen-based.
Markings on paper maps need to be scanned, photographed, or otherwise
digitised, while maps with screen-based markings need to be saved as
`.png`-format images.
## Installation
The current stable version can be installed from CRAN with:
```{r cran-inst, eval = FALSE}
install.packages ("mapscanner")
```
Alternatively, the development version can be installed via [rOpenSci's
r-universe](https://ropensci.r-universe.dev/) by running the following prior to
calling `install.packages()`:
```{r r-univ, eval = FALSE}
options (repos = c (
ropensci = "https://ropensci.r-universe.dev",
CRAN = "https://cloud.r-project.org"
))
```
The package can then be loaded for usage in a R session with
```{r library}
library (mapscanner)
```
## Usage
The package is designed to enable the following workflow:
1. Generate a map with the
[`ms_generate_map()`](https://docs.ropensci.org/mapscanner/reference/ms_generate_map.html)
function, which automatically produces both `.pdf` and `.png` versions;
2. Either print the `.pdf` version to use as desired in any kind of survey
environment, or use either the `.pdf` or `.png` versions in digital form for
screen-based surveys.
3. Draw on the map;
4. For paper maps, digitise the drawn-on (from here on, "modified") map,
converting it to either `.pdf` or `.png` format; and
5. Rectify the modified version against the original via the
[`ms_rectify_map()`](https://docs.ropensci.org/mapscanner/reference/ms_rectify_map.html)
function, which distinguishes individual annotations,
and converts each one to a spatial object able to be analysed in any desired
manner.
### Practical tips
The `mapscanner` package is intended to aid a *practical* workflow, and so
a few practical tips may be recommended here to ensure best results:
1. The original digital files generated with
[`ms_generate_map()`](https://docs.ropensci.org/mapscanner/reference/ms_generate_map.html)
are necessary to rectify subsequently drawn-on and scanned maps, and so must
be retained at all times.
2. Marks drawn on maps should be *coloured* -- any black or grey markings will
be ignored. This has the advantage that individual annotations *not*
intended to be converted to spatial objects (such as unique identification
or participant codes) may be made on maps in black or grey.
3. For drawings of areas, best results will be achieved through ensuring that
all lines form closed polygons. While the default `type = "hulls"` argument
should work even when lines are not closed, the `type = "polygons"` argument
will generally produce more accurate results, yet should only be used when
all lines form closed polygons (see below for details on how these two differ).
4. Digitised versions of paper maps should contain *white* borders, so do not,
for example, photograph modified maps lying on dark surfaces. If maps are to
be photographed, then best results can be achieved by simply placing them on
a larger, enclosing sheet of white paper.
The following two sections describe the two primary functions of the
`mapscanner` package, corresponding to the two primary steps of producing maps
to be used in surveys (or other activities), and rectifying modified maps
against these originals in order to extract spatial objects. The second of
these sections also describes the kinds of markings able to be recognised, and
the kinds of spatial objects to which these may be converted.
### Mapbox API tokens
Map generation with `mapscanner` requires a personal token or key from
[`mapbox`](https://www.mapbox.com/), which can be obtained by following the
links from
[https://docs.mapbox.com/api](https://docs.mapbox.com/api/#access-tokens-and-token-scopes/).
If you already have a token, the easiest way to use it with `mapscanner` is to
create (or edit) a file `~/.Renviron`, and insert a line,
``` bash
MAPBOX_TOKEN=
```
This will then be available every time you start R, without any need to
explicitly set the token each time you want to use the package. The token may
be given any unique name that includes "mapbox" (case insensitive).
Alternatively, if you wish to keep your token truly private, and only use it
for your current R session, you may load `mapscanner`, and then run
`set_mapbox_token()`.
### Map generation
Having obtained and set a [`mapbox`](https://www.mapbox.com/) token as
described above, `mapscanner` may then be used to generate maps. The package
comes with a sample map of Omaha, Nebraska, USA, and one with some red lines
drawn on it: 
That's just a standard `png` image with no notion of geographical coordinates.
The original map was generated with
```{r omaha-fakey, eval = FALSE}
bbox <- rbind (
c (-96.12923, -96.01011),
c (41.26145, 41.32220)
) # portion of omaha
ms_generate_map (bbox, max_tiles = 16L, mapname = "omaha")
```
```{r omaha, echo = FALSE}
bbox <- rbind (
c (-96.12923, -96.01011),
c (41.26145, 41.32220)
)
message ("Successfully generated 'omaha.pdf' and 'omaha.png'")
```
As indicated, the function generates a map in both `.pdf` and `.png` formats.
These files must be retained as the "master" maps against which subsequently
modified -- drawn-over and scanned-in -- versions will be rectified.
### Map rectification
The magic within the `mapscanner` package happens via the [`RNiftyReg`
package](https://github.com/jonclayden/RNiftyReg), itself primarily intended to
align brain scans and other medical images, but which is precisely the tool
needed here. The package comes with two sample `.png` images which can be used
to demonstrate map rectification. In the following code, `f_modified` is the
image shown above, modified from the original by drawing a red line around
a particular region of Omaha.
```{r scan_maps}
f_orig <- system.file ("extdata", "omaha.png", package = "mapscanner")
f_mod <- system.file ("extdata", "omaha-polygons.png", package = "mapscanner")
res <- ms_rectify_map (f_orig, f_mod, type = "polygons")
res
```
The rectification can take quite some time, during which [`RNiftyReg`
package](https://github.com/jonclayden/RNiftyReg) is constructing the best
transformation of the modified image back on to the original. The result of
`ms_rectify_map()` is a spatial object in
[`sf`](https://cran.r-project.org/package=sf)-format in which each drawn
component is represented as a separate polygon. Finally, we can plot the result
as an interactive map using packages like
[`mapview`](https://github.com/r-spatial/mapview) with the following commands:
```{r mapview, eval = FALSE}
library (mapview)
mapview (res)
```
or [`mapdeck`](https://github.com/symbolixAU/mapdeck), which similarly requires
a mapbox token:
```{r mapdeck, eval = FALSE}
library (mapdeck)
set_token (Sys.getenv (""))
mapdeck () %>%
add_polygon (res,
fill_colour = "#ffff00cc",
stroke_colour = "#ff0000", stroke_width = 20
)
```
```{r leaflet, echo = FALSE, eval = FALSE}
library (leaflet)
leaflet (res) %>%
addPolygons (
color = "#FF1111", weight = 1, opacity = 1.0,
fillOpacity = 0.5
) %>%
addProviderTiles ("CartoDB.Positron") %>%
setView (
lng = mean (bbox [1, ]),
lat = mean (bbox [2, ]),
zoom = 12
)
```
And our hand-drawn lines shown above have been converted to standard spatial
objects able to be analysed in any desired way. See the [package
vignette](https://docs.ropensci.org/mapscanner/articles/mapscanner.html) for
more detail of what the `mapscanner` package can do.
## Code of Conduct
Please note that this package is released with a [Contributor Code of
Conduct](https://ropensci.org/code-of-conduct/). By contributing to this
project, you agree to abide by its terms.
[](https://ropensci.org)
## Contributors
All contributions to this project are gratefully acknowledged using the [`allcontributors` package](https://github.com/ropenscilabs/allcontributors) following the [all-contributors](https://allcontributors.org) specification. Contributions of any kind are welcome!
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