Introduction to package mapsapi
Author: Michael Dorman
Date: 2023-07-21

# Introduction to package `mapsapi`

#### Michael Dorman

#### 2023-07-21

## Introduction

The `mapsapi` package provides an interface to the Google Maps APIs, currently four of them:

- Google Maps Direction API
- Google Maps Distance Matrix API
- Google Maps Geocode API
- Maps Static API

Functions `mp_directions`, `mp_matrix` and `mp_geocode` are used to access the Directions, Matrix and Geocode APIs, respectively. They return an `xml_document` object (package `xml2`) with the response contents.

- Given a directions response, functions `mp_get_routes` and `mp_get_segments` can be used to process the response document into a spatial layer. Function `mp_get_routes` gives each alternative as a separate line, while function `mp_get_segments` gives each segment (that is, a portion of the route associated with specific driving instructions) as a separate line.

- Given a distance matrix response, function `mp_get_matrix` can be used to obtain distance/duration matrices.

- Given a geocode response, functions `mp_get_points` and `mp_get_bounds` can be used to obtain geocoded locations as a point or polygon (bounds) layer.

The fourth function `mp_map` is used to access the Maps Static API. It returns a `stars` raster RGB image, which can be used as background in maps.

## Installation

The CRAN version can be installed with:

    install.packages("mapsapi")

The development version can be installed using `remotes`:

    install.packages("remotes")
    remotes::install_github("michaeldorman/mapsapi")

Once installed, the package can be loaded with `library`:

    library(mapsapi)

A Google Maps APIs key is required to use the package:

    key = "AIz....."

## Directions

The following expression queries the Directions API for driving directions from Tel-Aviv and Haifa. Note that locations can be specified as a coordinate pair, a textual address or an `sf` spatial object. For example:

    doc = mp_directions(
      origin = c(34.81127, 31.89277),
      destination = "Haifa",
      alternatives = TRUE,
      key = key,
      quiet = TRUE
    )

Alternatively, we can use the sample response data included in the packages:

    library(xml2)
    doc = as_xml_document(response_directions_driving)

Given the response object, we can use `mp_get_routes` to create a spatial layer of route lines:

    r = mp_get_routes(doc)

Here is the resulting object:

    r

    ## Simple feature collection with 2 features and 11 fields
    ## Geometry type: LINESTRING
    ## Dimension:     XY
    ## Bounding box:  xmin: 34.76391 ymin: 31.87341 xmax: 35.10642 ymax: 32.79439
    ## Geodetic CRS:  WGS 84
    ##     alternative_id leg_id                   summary distance_m distance_text
    ## 1-1              1      1 Yitzhak Rabin Hwy/Route 6     126121        126 km
    ## 2-1              2      1         Hwy 2/Kvish HaHof     122251        122 km
    ##     duration_s  duration_text duration_in_traffic_s duration_in_traffic_text
    ## 1-1       5265 1 hour 28 mins                    NA                       NA
    ## 2-1       5402 1 hour 30 mins                    NA                       NA
    ##     departure_time arrival_time                       geometry
    ## 1-1           <NA>         <NA> LINESTRING (34.81144 31.892...
    ## 2-1           <NA>         <NA> LINESTRING (34.81144 31.892...

and a visualization using `leaflet`:

    library(leaflet)
    pal = colorFactor(palette = "Dark2", domain = r$alternative_id)
    leaflet() %>%
      addProviderTiles("CartoDB.DarkMatter") %>%
      addPolylines(data = r, opacity = 1, weight = 7, color = ~pal(alternative_id))

Separate segments can be extracted from the same response using `mp_get_segments`:

    seg = mp_get_segments(doc)

Here are the first six features of the resulting object:

    head(seg)

    ## Simple feature collection with 6 features and 12 fields
    ## Geometry type: LINESTRING
    ## Dimension:     XY
    ## Bounding box:  xmin: 34.80859 ymin: 31.88656 xmax: 34.82317 ymax: 31.89256
    ## Geodetic CRS:  WGS 84
    ##       alternative_id leg_id segment_id                   summary travel_mode
    ## 1-1-1              1      1          1 Yitzhak Rabin Hwy/Route 6     driving
    ## 1-1-2              1      1          2 Yitzhak Rabin Hwy/Route 6     driving
    ## 1-1-3              1      1          3 Yitzhak Rabin Hwy/Route 6     driving
    ## 1-1-4              1      1          4 Yitzhak Rabin Hwy/Route 6     driving
    ## 1-1-5              1      1          5 Yitzhak Rabin Hwy/Route 6     driving
    ## 1-1-6              1      1          6 Yitzhak Rabin Hwy/Route 6     driving
    ##                                                               instructions
    ## 1-1-1 Head <b>southwest</b> on <b>Bnei Moshe St</b> toward <b>Negba St</b>
    ## 1-1-2                                Turn <b>left</b> onto <b>Negba St</b>
    ## 1-1-3                    Turn <b>left</b> onto <b>Rachel Hirshenzon St</b>
    ## 1-1-4        Turn <b>right</b> onto <b>Herzl St</b>/<wbr/><b>Route 412</b>
    ## 1-1-5                            Turn <b>left</b> onto <b>Abarbanel St</b>
    ## 1-1-6    At the roundabout, continue straight onto <b>Derech Jerusalem</b>
    ##       distance_m distance_text duration_s duration_text departure_time
    ## 1-1-1        322        0.3 km         65         1 min           <NA>
    ## 1-1-2        180        0.2 km         36         1 min           <NA>
    ## 1-1-3        327        0.3 km         75         1 min           <NA>
    ## 1-1-4        548        0.5 km        108        2 mins           <NA>
    ## 1-1-5        503        0.5 km         83         1 min           <NA>
    ## 1-1-6        364        0.4 km         52         1 min           <NA>
    ##       arrival_time                       geometry
    ## 1-1-1         <NA> LINESTRING (34.81144 31.892...
    ## 1-1-2         <NA> LINESTRING (34.80859 31.890...
    ## 1-1-3         <NA> LINESTRING (34.80968 31.889...
    ## 1-1-4         <NA> LINESTRING (34.81257 31.891...
    ## 1-1-5         <NA> LINESTRING (34.81437 31.886...
    ## 1-1-6         <NA> LINESTRING (34.81956 31.887...

and a visualization:

    pal = colorFactor(
      palette = sample(colors(), length(unique(seg$segment_id))),
      domain = seg$segment_id
      )
    leaflet(seg) %>%
      addProviderTiles("CartoDB.DarkMatter") %>%
      addPolylines(opacity = 1, weight = 7, color = ~pal(segment_id), popup = ~instructions)

## Distance Matrix

The following expression queries the Distance Matrix API to obtain a matrix of driving distance and duration between all combinations of three locations: Tel-Aviv, Jerusalem and Beer-Sheva.

    locations = c("Tel-Aviv", "Jerusalem", "Beer-Sheva")

    doc = mp_matrix(
      origins = locations,
      destinations = locations,
      key = key,
      quiet = TRUE
    )

Alternatively, we can use the sample response data included in the packages:

    doc = as_xml_document(response_matrix)

The `mp_get_matrix` function can then be used to process the XML response into a `matrix`. Possible values of the matrix include:

- `distance_m`—Distance, in meters
- `distance_text`—Distance, textual description
- `duration_s`—Duration, in seconds
- `duration_text`—Duration, textual description

    m = mp_get_matrix(doc, value = "distance_m")
    colnames(m) = locations
    rownames(m) = locations
    m

    ##            Tel-Aviv Jerusalem Beer-Sheva
    ## Tel-Aviv          0     66866     108728
    ## Jerusalem     68524         0     118083
    ## Beer-Sheva   110858    106562          0

## Geocode

The following expression queries the Directions API for geocoding a single address:

    doc = mp_geocode(
      addresses = "Tel-Aviv",
      key = key,
      quiet = TRUE
    )

Alternatively, we can use the sample response data included with the package:

    doc = list("Tel-Aviv" = as_xml_document(response_geocode))

Given the response object, we can use `mp_get_points` to create a spatial layer of geocoded point locations:

    pnt = mp_get_points(doc)
    pnt

    ## Simple feature collection with 1 feature and 5 fields
    ## Geometry type: POINT
    ## Dimension:     XY
    ## Bounding box:  xmin: 34.78177 ymin: 32.0853 xmax: 34.78177 ymax: 32.0853
    ## Geodetic CRS:  WGS 84
    ##   id status  address        address_google location_type
    ## 1  1     OK Tel-Aviv Tel Aviv-Yafo, Israel   APPROXIMATE
    ##                        pnt
    ## 1 POINT (34.78177 32.0853)

Here is a visualization using `leaflet`:

    leaflet() %>%
      addProviderTiles("CartoDB.DarkMatter") %>%
      addCircleMarkers(data = pnt)

Or the bounds:

    bounds = mp_get_bounds(doc)
    bounds

    ## Simple feature collection with 1 feature and 4 fields
    ## Geometry type: POLYGON
    ## Dimension:     XY
    ## Bounding box:  xmin: 34.74252 ymin: 32.02925 xmax: 34.85198 ymax: 32.14661
    ## Geodetic CRS:  WGS 84
    ##   id status  address        address_google                       geometry
    ## 1  1     OK Tel-Aviv Tel Aviv-Yafo, Israel POLYGON ((34.74252 32.02925...

And a visualization using `leaflet`:

    leaflet() %>%
      addProviderTiles("CartoDB.DarkMatter") %>%
      addPolygons(data = bounds)

## Static maps

The `mp_map` function can be used to access the Maps Static API to download an RGB image with a map.

Here is an example:

    r = mp_map(center = "31.253205,34.791914", zoom = 14, key = key, quiet = TRUE)

Alternatively, we can use the sample response data included with the package:

    r = response_map

The result is a `stars` raster, which can be plotted with `plot`:

    library(stars)
    plot(r)

    ## Loading required package: abind

    ## Loading required package: sf

    ## Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE

or with `ggplot2`:

    library(ggplot2)
    cols = attr(r[[1]], "colors")
    ggplot() +
      geom_stars(data = r, aes(x = x, y = y, fill = color)) +
      scale_fill_manual(values = cols, guide = FALSE) +
      coord_sf()

    ## Warning: The `guide` argument in `scale_*()` cannot be `FALSE`. This was deprecated in
    ## ggplot2 3.3.4.
    ## ℹ Please use "none" instead.
    ## This warning is displayed once every 8 hours.
    ## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
    ## generated.