Learning GIS with ice-cream parlors

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background-image: linear-gradient(to bottom, transparent 0%, black 120%), url('img/cover.png')

# "Learning GIS with<br>ice-cream parlors"

Open Source in GIS conference &bull; June 9th, 2021

.small[ Amit Levinson &bull; [<svg viewBox="0 0 576 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:white;" xmlns="http://www.w3.org/2000/svg">  <path d="M280.37 148.26L96 300.11V464a16 16 0 0 0 16 16l112.06-.29a16 16 0 0 0 15.92-16V368a16 16 0 0 1 16-16h64a16 16 0 0 1 16 16v95.64a16 16 0 0 0 16 16.05L464 480a16 16 0 0 0 16-16V300L295.67 148.26a12.19 12.19 0 0 0-15.3 0zM571.6 251.47L488 182.56V44.05a12 12 0 0 0-12-12h-56a12 12 0 0 0-12 12v72.61L318.47 43a48 48 0 0 0-61 0L4.34 251.47a12 12 0 0 0-1.6 16.9l25.5 31A12 12 0 0 0 45.15 301l235.22-193.74a12.19 12.19 0 0 1 15.3 0L530.9 301a12 12 0 0 0 16.9-1.6l25.5-31a12 12 0 0 0-1.7-16.93z"></path></svg>](https://amitlevinson.com) [<svg viewBox="0 0 496 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:white;" xmlns="http://www.w3.org/2000/svg">  <path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg>](https://github.com/AmitLevinson) [<svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:white;" xmlns="http://www.w3.org/2000/svg">  <path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"></path></svg>](https://twitter.com/Amit_Levinson) [<svg viewBox="0 0 448 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:white;" xmlns="http://www.w3.org/2000/svg">  <path d="M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z"></path></svg>](https://www.linkedin.com/in/amit-levinson/)
]

---
class: bold-last-item

# About me

- Sociology MA Graduate, BGU

- Been using R Programming language for < 2 years

- Had no idea what is GIS prior to using R

- Enjoy:

- Open source tools (R, Linux, Git, MySQL)
  
--

- Blogging
  
--

- Learning new things

- &#127850; & &#129371;

---

## "Regular" data

How I first encountered and learn to work with data:

```r
head(iris)
```

```
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa
```

---

## Spatial data<sup>*</sup>

How I encountered spatial data (e.g. `.shp`):

```r
head(shelters[,2])
```

```
*## Simple feature collection with 6 features and 0 fields
*## Geometry type: POINT
*## Dimension:     XY
*## Bounding box:  xmin: 181680.1 ymin: 574027.4 xmax: 181972.9 ymax: 574304
*## Projected CRS: Israel 1993 / Israeli TM Grid
## # A tibble: 6 x 1
##              geometry
*##           <POINT [m]>
*## 1 (181710.6 574217.8)
## 2   (181680.1 574304)
## 3   (181820.6 574243)
## 4 (181819.3 574027.4)
## 5 (181972.9 574046.2)
## 6 (181912.3 574151.1)
```

.footnote[
\* To reflect my learning process, I address spatial data here as in a vector format (and not, e.g., raster)
]

???
- data of shelters across beer-sheva
shapefiles

---
background-image: url(https://media.giphy.com/media/kfLPQJRuivFwqGBxp3/giphy.gif)
background-size: contain

???

Gif credit: tenor.com
---

## Returning to my comfort zone

Used a `.csv` file instead:

```
## # A tibble: 6 x 2
*##     lat   lon
##   <dbl> <dbl>
## 1  31.3  34.8
## 2  31.3  34.8
## 3  31.3  34.8
## 4  31.3  34.8
## 5  31.3  34.8
## 6  31.3  34.8
```

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---
class: inverse, center, middle

# Exploring distances to the nearest ice-cream parlors

---
# Background

- Fiddled around but never really knew what I was doing

- Participated in several days of the [#30Daysmapchallenge](https://github.com/tjukanovt/30DayMapChallenge)

- Realized it's time to learn some spatial analysis

.footnote[The talk is based on an [earlier blog post on the topic.](https://amitlevinson.com/blog/exploring-ice-cream-locations/)
]

.center[]

.pull-left[
### Inspiration

Dominic Royé's blog post about [distances to the sea in Iceland](https://dominicroye.github.io/en/2019/calculating-the-distance-to-the-sea-in-r/)
]

.pull-right[
### Serendipitous resource

Michael Dorman's [Spatial data analysis workshop](https://michaeldorman.github.io/R-Spatial-Workshop-at-CBS-2021/main.html) at Israel's CBS

]

---

# Data

Where do you find ice-cream locations data?

---
class: bold-last-item

# Data collection

- [Scrape the data from the website](https://github.com/AmitLevinson/Datasets/blob/master/golda/golda-icecreams.R)

```
## [1] "\nאור עקיבא\n\nכשר\nהשקמים 8\n04-646-0705\n\n"
```

- Clean it

- Geocode the data to get lat & long from addresses

- Reverse geocode the long & lat and verify each address.

Final output looked like this (total of 79 addresses):

|city      |street   |number      |location            |      lon|      lat|google_address                    |
|:---------|:--------|:-----------|:-------------------|--------:|--------:|:---------------------------------|
|אור עקיבא |השקמים 8 |04-646-0705 |השקמים 8, אור עקיבא | 34.91794| 32.50436|Ha-Shikmim St 8, Or Akiva, Israel |

???
Notice we have long and lat, it's not yet even recognized as anything spatial.

Discrepancies were manually verified (though I probably verified everything anyway).

---
background-image: url(img/worst_day_top.jpg)
background-size: contain
---
background-image: url(img/worst_day_full.jpg)
background-size: contain

---

## How does our data look?

.center[
<iframe src='data/widgets/simple_map.html' width = 650, height = 500></iframe>
]

.footnote[If you can't see the iframe, please refresh the page.]

???

We haven't done any manipulation yet, notice the warning message

I wanted to enable users to interact with the map so leaflet was important here (and not, for example, ggplot)

---
class: inverse, center, middle

# Some spatial manipulations

---

## Transforming

We might want to be more explicit with our spatial data:

**Geographic**

```
## Simple feature collection with 1 feature and 0 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: 34.86002 ymin: 32.02051 xmax: 34.86002 ymax: 32.02051
*## Geodetic CRS:  WGS 84
## # A tibble: 1 x 1
##              geometry
##           <POINT [°]>
## 1 (34.86002 32.02051)
```

**Projected**

```
## Simple feature collection with 1 feature and 0 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: 186911.1 ymin: 658636.9 xmax: 186911.1 ymax: 658636.9
*## Projected CRS: Israel 1993 / Israeli TM Grid
## # A tibble: 1 x 1
##              geometry
##           <POINT [m]>
## 1 (186911.1 658636.9)
```

???
-- Essentially we might want to know what coordinate reference system were using
-- CRS as in how the coordinates in our geometries relate to the surface of the Earth.

- WGS World Geodetic System, מערכת גאודטית עולמית)

---

## Grids

We want to calculate distances to Golda, but **from where?**

.column[
.center[
#### Original map

<img src='img/plots/map.png' height = 400px>
]
]
--

.column[
.center[
#### Grid layout (2km<sup>2</sup>)

<img src='img/plots/squaregrid.png' height = 400px>
]
]

.column[
.center[
#### Israel as grid

]
]

???
The grids help overcoming the reactivity we might find in web based apps

---

## Distances

We have our grid cells, how do we identify the **nearest ice-cream location?**

.pull-left[

Example for 1 grid cell to several Goldas:

```r
example_distances <- st_distance(x = both_distances$geometry, y = both_distances$geometry.1[1])
# Print 10:
head(set_units(example_distances, "km"), 10)
```

```
## Units: [km]
##            [,1]
##  [1,] 218.88346
##  [2,] 272.69260
*##  [3,]  57.20938
##  [4,] 194.03313
##  [5,] 182.41663
##  [6,] 209.48198
##  [7,] 131.61719
##  [8,] 256.71129
##  [9,] 218.63946
## [10,] 225.91495
```

]

.pull-right[
<img src='img/plots/grid_example.png' height = 450px>
]

---

## Distances

---

## Cosmetics <svg viewBox="0 0 512 512" style="height:1em;position:relative;display:inline-block;top:.1em;fill:#3f51b5;" xmlns="http://www.w3.org/2000/svg">  <path d="M224 96l16-32 32-16-32-16-16-32-16 32-32 16 32 16 16 32zM80 160l26.66-53.33L160 80l-53.34-26.67L80 0 53.34 53.33 0 80l53.34 26.67L80 160zm352 128l-26.66 53.33L352 368l53.34 26.67L432 448l26.66-53.33L512 368l-53.34-26.67L432 288zm70.62-193.77L417.77 9.38C411.53 3.12 403.34 0 395.15 0c-8.19 0-16.38 3.12-22.63 9.38L9.38 372.52c-12.5 12.5-12.5 32.76 0 45.25l84.85 84.85c6.25 6.25 14.44 9.37 22.62 9.37 8.19 0 16.38-3.12 22.63-9.37l363.14-363.15c12.5-12.48 12.5-32.75 0-45.24zM359.45 203.46l-50.91-50.91 86.6-86.6 50.91 50.91-86.6 86.6z"></path></svg>

```
## Rows: 7,375
## Columns: 7
## $ geometry.x  <POLYGON [°]> POLYGON ((34.90188 29.49693..., POLYGON ((34.91766~
## $ distance_km <dbl> 7.871391, 7.332709, 6.613721, 7.363470, 6.918497, 5.722077~
## $ location_id <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3~
## $ city        <chr> "אילת", "אילת", "אילת", "אילת", "אילת", "אילת", "אילת", "א~
## $ street      <chr> "מתחם הספירל", "מתחם הספירל", "מתחם הספירל", "מתחם הספירל"~
## $ number      <chr> "08-9428989", "08-9428989", "08-9428989", "08-9428989", "0~
## $ geometry.y  <POINT [°]> POINT (34.95968 29.54952), POINT (34.95968 29.54952)~
```

```r
create_label_distances <- function(km, street, city){
  glue("
  <div style='text-align:left;'>
  You are <span style='font-size:13px;'><b>`{round(km, 1)}`</b></span> km from the nearest location at:</div>
  <div style='text-align:right;'>
       `{street}`, `{city}`</div>") %>% 
    HTML()}
```

```
## [[1]]
## <div style='text-align:left;'>
## You are <span style='font-size:13px;'><b>7.9</b></span> km from the nearest location at:</div>
## <div style='text-align:right;'>
##      מתחם הספירל, אילת</div>
```

---

## Et Voila

.center[
<iframe src='data/widgets/full_map.html' width = 650, height = 500></iframe>
]

.footnote[If you can't see the iframe, please refresh the page.]

---
class: inverse, center,middle

# How does this relate to open source

---

## Feedback

> Someone will always have what to say about your work

### Positive

???
- The person trying using the 2039, but that's the one for Israel!

- Micha provided the code for using a raster approach. I was and currently barley am familiar with raster, but this definitely opens up new avenues and glad to have received that feedback.

---

## Personal reasons

- GIS was available in an already used OS platform (R)

- Free

- Can use/change others' code freely

- Pushes to high standards knowing others see/read your code

- Get to contribute back

- **The community!**

---
class: inverse, center, middle

# Thank you!