Xiaofan Liang March 13th, 2024
By the end of this practical lab you will be able to:
osmdatatmapleaflet (Optional)tmaps using RpubCHEATSHEETS! You are encouraged to download RStudio Cheatsheets. You can find them on RStudio website here, or a comprehensive list (more than what has been listed) here. For example, here you can find base R syntax, dplyr, ggplot2, sf.
| Functions | Tasks |
|---|---|
getbb(). |
[osmdata] Retrieve bounding box by coordinates or place names. |
opq() |
[osmdata] Build an Overpass query based on bounding box and osm features |
add_osm_feature() |
[osmdata] Add a feature to an Overpass query |
add_osm_features() |
[osmdata] Alternative version of
add_osm_feature for creating single queries with multiple
features. |
osmdata_sf() |
[osmdata] Return an OSM Overpass query as an osmdata object in sf format |
addTiles() |
[leaflet] Add a tile layer (basemap) to the map |
addPolygons() |
[leaflet] Add polygons to the map |
addPolylines() |
[leaflet] Add lines to the map |
addCircleMarkers() |
[leaflet] Add circle markers to the map |
For Python submission (in ipynb format), make sure
your Python code replicate ALL the R code in the Lab
(and if it is difficult to replicate exactly, at least cover all the
learning objectives). The recommended approach is to copy each heading
and write your python code below. You may reference OSMnx
and Pyrosm library in Python for OSM-related analysis and
Folium for visualization with leaflet capacity.
The two new libraries in this lab are osmdata and
leaflet.
osmdata is an R package for downloading and using data
from OpenStreetMap (OSM).
Leaflet is an open-source
JavaScript library for interactive maps. The R package
leaflet makes it easy to create maps from R.
#replace my path with yours to the Lab 5 folder
setwd("/Users/xiaofanliang/Dropbox (University of Michigan)/UM_Teaching/URP535_Urban_Informatics/Lab/Lab10/")
#install.packages('tidyverse')
library(tidyverse)
#install.packages('tmap')
library(tmap)
#install.packages('tmap')
library(osmdata)
#install.packages('leaflet')
library(leaflet)OSM data has three geometry: Node (which can be POI but also a node that forms the geometry of a polygon), Way (polygons, such as buildings), and Relation (a collection of nodes, ways, and relations geometry, such as a bus line). In this lab, we will mostly be working with Node and Way.
The code below intends to retrieve buildings in Ann Arbor
area. In general, there are two steps for downloading OSM data:
1) determine the bounding box for data download, 2) tell OSM what
features (e.g., amenities? roads? buildings?) you want to download and
convert the queried data into sf format. Let’s dive in.
An OSM query starts with a bounding box. You can input a place name
as a character string. This function getbb() uses the free
Nominatim API provided by OpenStreetMap to find the bounding box (bb)
associated with place names. It is recommended to double check the
returned bounding box, because many places in the world may have the
same name! The function opq() stands for OverPass Query,
which helps you format your R code into queries that Overpass API can
take in. Thus, when you print out q, what you see are the
meta data fed into the Overpass Query.
getbb("Ann Arbor US")## min max
## x -83.79957 -83.67581
## y 42.22267 42.32389getbb("University of Michigan US")## min max
## x -83.75022 -83.66497
## y 42.24223 42.31251q <- opq(bbox = getbb("University of Michigan US"))
q## $bbox
## [1] "42.242226,-83.7502236,42.3125148,-83.6649743"
##
## $prefix
## [1] "[out:xml][timeout:25];\n(\n"
##
## $suffix
## [1] ");\n(._;>;);\nout body;"
##
## $features
## NULL
##
## $osm_types
## [1] "node" "way" "relation"
##
## attr(,"class")
## [1] "list" "overpass_query"
## attr(,"nodes_only")
## [1] FALSEYou can also input four coordinates in the form of
c(xmin, ymin, xmax, ymax) to determine the bounding box.
You can get xmin and ymin coordinates by
clicking the bottom left corner of the intended area and
xmax and ymax coordinates by clicking the top
right corner of the intended area in the Google Maps. In this case,
since we are working with North Campus, which is not a well-defined
place name in OSM, we will use bounding box to retrieve OSM data
instead.
# these coordinates are roughly the bottom left and top right corner of UM North Campus.
q <- opq(bbox = c(-83.725706, 42.287305, -83.704518, 42.302508))
q## $bbox
## [1] "42.287305,-83.725706,42.302508,-83.704518"
##
## $prefix
## [1] "[out:xml][timeout:25];\n(\n"
##
## $suffix
## [1] ");\n(._;>;);\nout body;"
##
## $features
## NULL
##
## $osm_types
## [1] "node" "way" "relation"
##
## attr(,"class")
## [1] "list" "overpass_query"
## attr(,"nodes_only")
## [1] FALSEsf objectsNext, we need to tell OSM what data we want to retrieve. OSM features
are stored in key-value (or
key-tag/feature-value) pairs. For
instance, to retrieve data on restaurants, then you need to put
key='amenity' and value='restaurant'.
How do you find out what key-value pairs are available on
OSM? - Go to OSM Wiki Map
Features Page. This covers most commonly used key-value pairs, but
is not exhuastive. It also provides definition of each
key-value pair. - Use available_features()
and available_tags() functions in osmdata().
This uses the same info as the Map Features Page above. - Google
specific interests with OSM Wiki (e.g., search “restaurant in OSM” will
return you this
page) - You may also use TagInfo to find out how
many incidents exist for each key-tag pair. If the
incidents are low, then this key-tag pair may not be
useful for your analysis, or this key-tag pair is only
used in a specific local context.
# expand features in R Environment to see all entries
features <- available_features()
head(features)## [1] "4wd_only" "abandoned" "abutters" "access" "addr" "addr:city"# you need to input a specific key to see all associated tags
# expand tags in R Environment to see all tags associated with amenity
tags <- available_tags("highway")
head(tags)## # A tibble: 6 × 2
## Key Value
## <chr> <chr>
## 1 highway bridleway
## 2 highway bus_guideway
## 3 highway bus_stop
## 4 highway busway
## 5 highway construction
## 6 highway corridorLet’s show how to withdraw buildings first. The
key-value pair for withdrawing all buildings is
key="building". Without specifying the value
argument, osmdata defaults to withdraw ALL
values under the key. osmdata_sf() returns an OSM Overpass
query as an osmdata object in sf format. Other formats are available
through osmdata_xml(), osmdata_data_frame(),
etc. For instance, if you are not planning to map the OSM data,
osmdata_data_frame() may be a better format for simple data
wrangling.
building <- opq(bbox = c(-83.725706, 42.287305, -83.704518, 42.302508)) %>%
add_osm_feature(key = 'building') %>%
osmdata_sf()
building## Object of class 'osmdata' with:
## $bbox : 42.287305,-83.725706,42.302508,-83.704518
## $overpass_call : The call submitted to the overpass API
## $meta : metadata including timestamp and version numbers
## $osm_points : 'sf' Simple Features Collection with 2999 points
## $osm_lines : NULL
## $osm_polygons : 'sf' Simple Features Collection with 342 polygons
## $osm_multilines : NULL
## $osm_multipolygons : 'sf' Simple Features Collection with 8 multipolygonsThe output of building shows the meta data. You can see
that there are data under both the osm_points and
osm_polygons metadata. It is possible that someone mapped
buildings labeled the nodes that form the building polygons as
buildings. We want to disregard that and go for
osm_polygons instead.
# retrieve the polygons and only print the first six rows / features
building_polygons <- building$osm_polygons
head(building_polygons)## Simple feature collection with 6 features and 65 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -83.71816 ymin: 42.29071 xmax: -83.7129 ymax: 42.29377
## Geodetic CRS: WGS 84
## osm_id name access addr:city
## 82245561 82245561 Pierpont Commons <NA> Ann Arbor
## 82246736 82246736 Bob and Betty Beyster Building <NA> Ann Arbor
## 82246737 82246737 Walgreen Drama Center <NA> Ann Arbor
## 82246798 82246798 Herbert H. Dow Building <NA> Ann Arbor
## 82249123 82249123 Ann and Robert H. Lurie Tower <NA> <NA>
## 82249280 82249280 G. G. Brown Building <NA> Ann Arbor
## addr:housenumber addr:postcode addr:state addr:street
## 82245561 2101 48109 <NA> Bonisteel Boulevard
## 82246736 2260 48109 MI Hayward Street
## 82246737 1226 48109 <NA> Murfin Avenue
## 82246798 2300 <NA> MI Hayward Street
## 82249123 <NA> <NA> <NA> <NA>
## 82249280 2350 <NA> MI Hayward Street
## alt_name amenity brand brand:wikidata
## 82245561 <NA> community_centre <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA>
## 82246737 <NA> arts_centre <NA> <NA>
## 82246798 <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> <NA>
## 82249280 G. G. Brown Laboratory <NA> <NA> <NA>
## building building:levels building:levels:underground
## 82245561 university 2 <NA>
## 82246736 university 4 <NA>
## 82246737 university 3 <NA>
## 82246798 university 3 <NA>
## 82249123 yes <NA> <NA>
## 82249280 university 3 <NA>
## building:material building:part check_date construction cuisine
## 82245561 <NA> <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA> <NA>
## 82246737 <NA> <NA> <NA> <NA> <NA>
## 82246798 brick <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> <NA> <NA>
## 82249280 <NA> <NA> <NA> <NA> <NA>
## description
## 82245561 <NA>
## 82246736 This building is occupied by the Computer Science & Engineering Department.
## 82246737 <NA>
## 82246798 This building is occupied by the Materials Science & Engineering Department.
## 82249123 <NA>
## 82249280 This building is occupied by the Mechanical Engineering Department and the Civil & Environmental Engineering Department.
## email height
## 82245561 <NA> <NA>
## 82246736 <NA> <NA>
## 82246737 <NA> <NA>
## 82246798 <NA> <NA>
## 82249123 <NA> 50.3
## 82249280 <NA> <NA>
## image
## 82245561 <NA>
## 82246736 https://cse.engin.umich.edu/wp-content/uploads/sites/3/2021/12/beyster-2021-09-1536x778.jpg
## 82246737 <NA>
## 82246798 <NA>
## 82249123 <NA>
## 82249280 <NA>
## internet_access landuse laundry_service layer leisure loc_name
## 82245561 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246737 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246798 <NA> <NA> <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> <NA> <NA> <NA>
## 82249280 <NA> <NA> <NA> <NA> <NA> <NA>
## man_made max_level min_level name:zh note official_name
## 82245561 <NA> <NA> <NA> 皮尔朋特公共楼 <NA> <NA>
## 82246736 <NA> <NA> <NA> 鲍勃和贝蒂贝斯特楼 <NA> <NA>
## 82246737 <NA> <NA> <NA> 沃尔格林表演中心 <NA> <NA>
## 82246798 <NA> <NA> <NA> 大分子工程系 <NA> <NA>
## 82249123 tower <NA> <NA> 卢琳钟楼 <NA> <NA>
## 82249280 <NA> <NA> <NA> 环境工程系 <NA> <NA>
## old_name opening_hours operator
## 82245561 <NA> Mo-Fr 07:00-24:00; Sa,Su 08:00-24:00 <NA>
## 82246736 <NA> Mo-Fr 07:00-19:00; PH off University of Michigan
## 82246737 <NA> <NA> <NA>
## 82246798 <NA> Mo-Fr 07:00-19:00; PH off University of Michigan
## 82249123 <NA> <NA> University of Michigan
## 82249280 <NA> Mo-Fr 07:00-18:00; PH off University of Michigan
## parking phone plant:method plant:output:electricity
## 82245561 <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA>
## 82246737 <NA> <NA> <NA> <NA>
## 82246798 <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> <NA>
## 82249280 <NA> <NA> <NA> <NA>
## plant:output:hot_water plant:source power ref ref:US:EIA religion
## 82245561 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246737 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246798 <NA> <NA> <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> <NA> <NA> <NA>
## 82249280 <NA> <NA> <NA> <NA> <NA> <NA>
## roof:levels roof:shape self_service shelter shop short_name source
## 82245561 <NA> flat <NA> <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA> <NA> BBB <NA>
## 82246737 0 flat <NA> <NA> <NA> WDC <NA>
## 82246798 2 flat <NA> <NA> <NA> DOW <NA>
## 82249123 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 82249280 <NA> flat <NA> <NA> <NA> GGB <NA>
## start_date supervised takeaway tower:construction tower:type website
## 82245561 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246736 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246737 <NA> <NA> <NA> <NA> <NA> <NA>
## 82246798 <NA> <NA> <NA> <NA> <NA> <NA>
## 82249123 <NA> <NA> <NA> tower bell_tower <NA>
## 82249280 <NA> <NA> <NA> <NA> <NA> <NA>
## wheelchair wikidata wikipedia geometry
## 82245561 <NA> <NA> <NA> POLYGON ((-83.71785 42.2910...
## 82246736 <NA> <NA> <NA> POLYGON ((-83.71579 42.2929...
## 82246737 <NA> <NA> <NA> POLYGON ((-83.71677 42.2921...
## 82246798 <NA> <NA> <NA> POLYGON ((-83.71577 42.2933...
## 82249123 <NA> Q6704939 en:Lurie Tower POLYGON ((-83.71627 42.2920...
## 82249280 <NA> <NA> <NA> POLYGON ((-83.7129 42.29296...Now you can see the output is similar to the sf objects
we have been working with and we can map them in tmap
interactive view.
Next, we would like to retrieve roads. Roads are called
highway key in OSM, which do not mean actual highway in
reality. Here we retrieve all the roads.
roads <- opq(bbox = c(-83.725706, 42.287305, -83.704518, 42.302508)) %>%
add_osm_feature(key = 'highway') %>%
osmdata_sf()
roads_lines <- roads$osm_lines
head(roads_lines)## Simple feature collection with 6 features and 79 fields
## Geometry type: LINESTRING
## Dimension: XY
## Bounding box: xmin: -83.71808 ymin: 42.28764 xmax: -83.70726 ymax: 42.30253
## Geodetic CRS: WGS 84
## osm_id name access alt_name area barrier bicycle
## 8720530 8720530 Beal Avenue <NA> <NA> <NA> <NA> <NA>
## 8720537 8720537 Bonisteel Boulevard <NA> <NA> <NA> <NA> <NA>
## 8721309 8721309 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 8721314 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721728 8721728 <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 8722056 Hubbard Road <NA> Hubbard Avenue <NA> <NA> <NA>
## bridge centre_turn_lane covered crossing crossing:island
## 8720530 <NA> <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> <NA> <NA>
## crossing:markings cycleway cycleway:both cycleway:both:lane
## 8720530 <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA>
## 8722056 <NA> shared_lane <NA> <NA>
## cycleway:left cycleway:right description direction flashing_lights foot
## 8720530 <NA> <NA> <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> <NA> <NA> <NA>
## footway garden:type golf golf_cart handrail handrail:center
## 8720530 <NA> <NA> <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> <NA> <NA> <NA>
## handrail:left handrail:right height highway horse incline indoor
## 8720530 <NA> <NA> <NA> residential <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> residential <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> service <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> service <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> service <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> residential <NA> <NA> <NA>
## informal lanes lanes:backward lanes:both_ways lanes:forward layer
## 8720530 <NA> 2 <NA> <NA> <NA> <NA>
## 8720537 <NA> 2 <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> 3 2 <NA> 1 <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> 2 <NA> <NA> <NA> <NA>
## leisure level lit maxspeed maxspeed:type name_1 noname note oneway
## 8720530 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> yes <NA> <NA> <NA> <NA> <NA> yes
## 8721309 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## operator parking:right ramp segregated service shoulder sidewalk
## 8720530 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8720537 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
## sidewalk:left sidewalk:right step_count surface tiger:cfcc
## 8720530 <NA> <NA> <NA> <NA> A41
## 8720537 <NA> <NA> <NA> asphalt A41
## 8721309 <NA> <NA> <NA> <NA> A41
## 8721314 <NA> <NA> <NA> asphalt A41
## 8721728 <NA> <NA> <NA> <NA> A74
## 8722056 <NA> <NA> <NA> <NA> A41
## tiger:county tiger:name_base tiger:name_base_1
## 8720530 Washtenaw, MI Beal <NA>
## 8720537 Washtenaw, MI Bonisteel <NA>
## 8721309 Washtenaw, MI <NA> <NA>
## 8721314 Washtenaw, MI <NA> <NA>
## 8721728 Washtenaw, MI <NA> <NA>
## 8722056 Washtenaw, MI Hubbard <NA>
## tiger:name_direction_prefix tiger:name_type tiger:name_type_1
## 8720530 <NA> Ave <NA>
## 8720537 <NA> Blvd <NA>
## 8721309 <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA>
## 8721728 <NA> <NA> <NA>
## 8722056 <NA> <NA> <NA>
## tiger:reviewed tiger:zip_left tiger:zip_left_1 tiger:zip_right
## 8720530 no 48105 <NA> 48105
## 8720537 no 48105 48109 48105
## 8721309 no <NA> <NA> <NA>
## 8721314 no <NA> <NA> <NA>
## 8721728 no <NA> <NA> <NA>
## 8722056 <NA> 48109 48105 48109
## tiger:zip_right_1 tunnel turn:lanes turn:lanes:backward
## 8720530 <NA> <NA> <NA> <NA>
## 8720537 48109 <NA> <NA> <NA>
## 8721309 <NA> <NA> <NA> <NA>
## 8721314 <NA> <NA> <NA> left|right
## 8721728 <NA> <NA> <NA> <NA>
## 8722056 48105 <NA> <NA> <NA>
## turn:lanes:forward wheelchair width geometry
## 8720530 <NA> <NA> <NA> LINESTRING (-83.7127 42.300...
## 8720537 <NA> <NA> <NA> LINESTRING (-83.71297 42.29...
## 8721309 <NA> <NA> <NA> LINESTRING (-83.7127 42.299...
## 8721314 <NA> <NA> <NA> LINESTRING (-83.70726 42.30...
## 8721728 <NA> <NA> <NA> LINESTRING (-83.70956 42.28...
## 8722056 <NA> <NA> <NA> LINESTRING (-83.71408 42.29...This example below shows how to retrieve multiple features
(amenities) at once. You can retrieve features under the same geometry
(e.g., point, line, polygon) in one file through
add_osm_features() function. Note that it has an additional
s as compared with the add_osm_feature()
function above.
amenity <- opq(bbox = c(-83.725706, 42.287305, -83.704518, 42.302508)) %>%
add_osm_features(features = c(
"amenity" = "restaurant",
"amenity" = "cafe"
)) %>%
osmdata_sf()
amenity_point <- amenity$osm_points
head(amenity_point)## Simple feature collection with 6 features and 19 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -83.72297 ymin: 42.29088 xmax: -83.71584 ymax: 42.29875
## Geodetic CRS: WGS 84
## osm_id name addr:city addr:housenumber addr:postcode
## 3062442001 3062442001 Fireside Café <NA> <NA> <NA>
## 3062442003 3062442003 Fireside Roast <NA> <NA> <NA>
## 3062453855 3062453855 Nagomi Sushi Ann Arbor 1754 48105
## 3064374713 3064374713 Saica Ann Arbor 1733 48105
## 3065601646 3065601646 Blue Apple <NA> <NA> <NA>
## 3072665433 3072665433 Mujo Cafe <NA> <NA> <NA>
## addr:state addr:street addr:unit amenity brand brand:wikidata
## 3062442001 <NA> <NA> <NA> restaurant <NA> <NA>
## 3062442003 <NA> <NA> <NA> cafe <NA> <NA>
## 3062453855 <NA> Plymouth Road <NA> restaurant <NA> <NA>
## 3064374713 <NA> Plymouth Road <NA> restaurant <NA> <NA>
## 3065601646 <NA> <NA> <NA> cafe <NA> <NA>
## 3072665433 <NA> <NA> <NA> cafe <NA> <NA>
## check_date cuisine delivery
## 3062442001 <NA> <NA> <NA>
## 3062442003 <NA> sandwich;coffee_shop <NA>
## 3062453855 <NA> japanese <NA>
## 3064374713 <NA> japanese;sushi <NA>
## 3065601646 <NA> sandwich;pizza <NA>
## 3072665433 2023-07-26 sandwich <NA>
## opening_hours
## 3062442001 Mo-Fr 09:00-17:00
## 3062442003 <NA>
## 3062453855 Mo-Th 11:00-22:00;Fr,Sa 11:00-22:30;Su 12:00-22:00
## 3064374713 Mo-Fr 11:00-22:00; Sa 12:00-22:00; Su 12:00-21:00
## 3065601646 Mo-Th 07:00-01:00; Fr 07:00-23:00; Sa 09:00-23:00; Su 09:00-01:00
## 3072665433 Mo-Th 07:00-02:00; Fr 07:00-18:00; Sa off; Su 12:00-02:00
## payment:mcard phone takeaway website
## 3062442001 yes <NA> <NA> <NA>
## 3062442003 yes <NA> <NA> <NA>
## 3062453855 <NA> +1 734 761 5800 <NA> http://nagomia2.com/
## 3064374713 <NA> +1 734 769 1212 <NA> http://www.saicasushi.com/
## 3065601646 yes <NA> <NA> <NA>
## 3072665433 <NA> <NA> <NA> <NA>
## geometry
## 3062442001 POINT (-83.71765 42.29092)
## 3062442003 POINT (-83.7177 42.29088)
## 3062453855 POINT (-83.72297 42.29795)
## 3064374713 POINT (-83.72164 42.29875)
## 3065601646 POINT (-83.72127 42.29364)
## 3072665433 POINT (-83.71584 42.29149)Now we will overlay all the data together and see it on the
tmap interactive map! Notice that we added some simple
aesthetics, so that roads are colored in light grey, buildings are
colored in darkgrey and the border transparency is set to 0 (which
essentially removes the border), and amenity points are colored in red
with 50% transparency and scaled to size 0.2.
If you hover to the OSM data, the default popup is OSM id, which is
the first column in the data. If we publish a web map with OSM data, we
would like the pop up to be more informative. The id
argument in tm_polygons(), tm_lines(), or
tm_symbols() helps set which column should show up on the
hovering pop up. The popup.vars argument determines the
content for on-click pop up. Try hovering to the point geometry
(amenities) and see the hover info and on-click popup have changed!
tmap_mode('view')## tmap mode set to interactive viewingtm_shape(roads_lines) +
tm_lines(col='black') +
tm_shape(building_polygons) +
tm_polygons(col='darkgrey') +
tm_shape(amenity_point) +
tm_symbols(size=0.2, col='red', alpha=0.5,
# determine variable that should show on hover
id = 'name',
# determine variables that should show on click
popup.vars=c('Name: ' = 'name', 'Amenity: ' = 'amenity'))