Geospatial visualization: raster maps

class: center, middle, inverse, title-slide

.title[
# Geospatial visualization: raster maps
]
.author[
### MACS 24000 <br /> University of Chicago
]

---

# Geospatial visualizations

* Earliest form of information visualizations
* Geospatial data visualizations
* [Google Maps](https://www.google.com/maps)

---

# Dr. John Snow

.center[

[![:scale 70%](https://upload.wikimedia.org/wikipedia/commons/2/27/Snow-cholera-map-1.jpg)](https://commons.wikimedia.org/wiki/File:Snow-cholera-map-1.jpg)

]

---

# Minard's map of Napoleon's march on Russia

[![Charles Minard's 1869 chart showing the number of men in Napoleon’s 1812 Russian campaign army, their movements, as well as the temperature they encountered on the return path. Source: Wikipedia.](https://upload.wikimedia.org/wikipedia/commons/2/29/Minard.png)](https://en.wikipedia.org/wiki/File:Minard.png)

---

# Minard's map of Napoleon's march on Russia

[![English translation of Minard's map](https://upload.wikimedia.org/wikipedia/commons/thumb/e/e2/Minard_Update.png/1280px-Minard_Update.png)](https://commons.wikimedia.org/wiki/File:Minard_Update.png)

---

# Designing modern maps

* Depict spatial features
* Incorporate additional attributes and information
* Major features
    * Scale
    * Projection
    * Symbols

---

# Scale

* Proportion between distances and sizes on a map and their actual distances and sizes on Earth
* Small-scale map
* Large-scale map

---

# Large-scale map

---

# Small-scale map

---

# Projection

* Process of taking a three-dimensional object and visualizing it on a two-dimensional surface
* No 100% perfect method for this
* Always introduces distortions
* Properties of projection methods
    1. Shape
    1. Area
    1. Angles
    1. Distance
    1. Direction

---

# Conformal projections

---

# Equal-area projections

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# Mollweide

---

# Symbols

---

# `ggmap`

* Package for drawing maps using `ggplot2` and **raster** map tiles
* Static image files generated by mapping services
* Focus on incorporating data into existing maps
* Severely limits ability to change the appearance of the geographic map

---

# Obtain map images

* [OpenStreetMap](https://www.openstreetmap.org/)
* [Stamen Maps](http://maps.stamen.com/#terrain/12/37.7706/-122.3782)
* [Google Maps](https://maps.google.com)

## Method for specifying map regions

1. Bounding box
1. Center/zoom

---

# Bounding box

```r
# store bounding box coordinates
chi_bb <- c(
  left = -87.936287,
  bottom = 41.679835,
  right = -87.447052,
  top = 42.000835
)

chicago_stamen <- get_stamenmap(
  bbox = chi_bb,
  zoom = 11
)
chicago_stamen
```

```
## 627x712 terrain map image from Stamen Maps. 
## See ?ggmap to plot it.
```

---

# Bounding box

```r
ggmap(chicago_stamen)
```

---

# Level of detail

---

# Identifying bounding box

> Use [bboxfinder.com](http://bboxfinder.com/#0.000000,0.000000,0.000000,0.000000) to determine the exact longitude/latitude coordinates for the bounding box you wish to obtain.

---

# Types of map tiles

---

# Import crime data

* City of Chicago open data portal
* [Crime data from 2017](https://data.cityofchicago.org/Public-Safety/Crimes-2017/d62x-nvdr)

```
## Rows: 267,345
## Columns: 22
## $ ID                     <dbl> 11094370, 11118031, 11134189, 11156462, 1116487…
## $ `Case Number`          <chr> "JA440032", "JA470589", "JA491697", "JA521389",…
## $ Date                   <chr> "09/21/2017 12:15:00 AM", "10/12/2017 07:14:00 …
## $ Block                  <chr> "072XX N CALIFORNIA AVE", "055XX W GRAND AVE", …
## $ IUCR                   <chr> "1122", "1345", "4651", "1110", "0265", "143A",…
## $ `Primary Type`         <chr> "DECEPTIVE PRACTICE", "CRIMINAL DAMAGE", "OTHER…
## $ Description            <chr> "COUNTERFEIT CHECK", "TO CITY OF CHICAGO PROPER…
## $ `Location Description` <chr> "CURRENCY EXCHANGE", "JAIL / LOCK-UP FACILITY",…
## $ Arrest                 <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,…
## $ Domestic               <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE…
## $ Beat                   <chr> "2411", "2515", "0922", "2514", "1221", "0232",…
## $ District               <chr> "024", "025", "009", "025", "012", "002", "005"…
## $ Ward                   <dbl> 50, 29, 12, 30, 32, 20, 9, 12, 12, 27, 32, 17, …
## $ `Community Area`       <dbl> 2, 19, 58, 19, 24, 40, 49, 30, 30, 23, 24, 44, …
## $ `FBI Code`             <chr> "10", "14", "26", "11", "02", "15", "03", "06",…
## $ `X Coordinate`         <dbl> 1156443, 1138788, 1159425, 1138653, 1161264, 11…
## $ `Y Coordinate`         <dbl> 1947707, 1913480, 1875711, 1920720, 1905292, 18…
## $ Year                   <dbl> 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017,…
## $ `Updated On`           <chr> "03/01/2018 03:52:35 PM", "03/01/2018 03:52:35 …
## $ Latitude               <dbl> 42.01229, 41.91871, 41.81467, 41.93858, 41.8958…
## $ Longitude              <dbl> -87.69971, -87.76551, -87.69073, -87.76583, -87…
## $ Location               <chr> "(42.012293397, -87.699714109)", "(41.918711651…
```

---

# Plot high-level map of crime

.pull-left[

```r
chicago <- chicago_stamen
ggmap(chicago)
```

]

.pull-right[

]

---

# Using `geom_point()`

.pull-left[

```r
ggmap(chicago) +
  geom_point(
    data = crimes,
    mapping = aes(
      x = Longitude,
      y = Latitude
    )
  )
```

]

.pull-right[

]

---

# Using `geom_point()`

.pull-left[

```r
ggmap(chicago) +
  geom_point(
    data = crimes,
    aes(
      x = Longitude,
      y = Latitude
    ),
    size = .25,
    alpha = .01
  )
```

]

.pull-right[

]

---

# Using `stat_density_2d()`

.pull-left[

```r
ggmap(chicago) +
  geom_density_2d(
    data = crimes,
    aes(
      x = Longitude,
      y = Latitude
    )
  )
```

]

.pull-right[

]

---

# Using `stat_density_2d()`

.pull-left[

```r
ggmap(chicago) +
  stat_density_2d(
    data = crimes,
    aes(
      x = Longitude,
      y = Latitude,
      fill = stat(level)
    ),
    geom = "polygon"
  )
```

]

.pull-right[

]

---

# Using `stat_density_2d()`

---

# Looking for variation

---

# Locations of murders

```
## # A tibble: 671 × 22
##          ID `Case Number` Date            Block IUCR  `Primary Type` Description
##       <dbl> <chr>         <chr>           <chr> <chr> <chr>          <chr>      
##  1    23128 JA149608      02/11/2017 07:… 001X… 0110  HOMICIDE       FIRST DEGR…
##  2    23851 JA530946      11/30/2017 11:… 088X… 0110  HOMICIDE       FIRST DEGR…
##  3    23355 JA302423      06/11/2017 06:… 047X… 0110  HOMICIDE       FIRST DEGR…
##  4    23379 JA312425      06/18/2017 04:… 006X… 0110  HOMICIDE       FIRST DEGR…
##  5    23673 JA490016      10/28/2017 10:… 048X… 0110  HOMICIDE       FIRST DEGR…
##  6    23224 JA210752      04/03/2017 12:… 013X… 0110  HOMICIDE       FIRST DEGR…
##  7    23627 JA461918      10/07/2017 11:… 018X… 0110  HOMICIDE       FIRST DEGR…
##  8    23628 JA461918      10/07/2017 11:… 018X… 0110  HOMICIDE       FIRST DEGR…
##  9 10836558 JA138326      02/01/2017 06:… 013X… 0142  HOMICIDE       RECKLESS H…
## 10    23477 JA364517      07/26/2017 05:… 047X… 0110  HOMICIDE       FIRST DEGR…
## # … with 661 more rows, and 15 more variables: `Location Description` <chr>,
## #   Arrest <lgl>, Domestic <lgl>, Beat <chr>, District <chr>, Ward <dbl>,
## #   `Community Area` <dbl>, `FBI Code` <chr>, `X Coordinate` <dbl>,
## #   `Y Coordinate` <dbl>, Year <dbl>, `Updated On` <chr>, Latitude <dbl>,
## #   Longitude <dbl>, Location <chr>
```

---

# Locations of murders

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# Locations of murders

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# Locations of murders

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# Additional aesthetics

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# Exercise using `ggmap`

![](https://pixel.nymag.com/imgs/daily/strategist/2018/09/05/schwinn-recumbent-exercise-bike.w710.h473.2x.jpg)