Análisis de redes espaciales con sfnetworks

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# Análisis de redes espaciales con <code>sfnetworks</code>
## R-Ladies Guayaquil
### Lorena Abad, Lucas van der Meer, Andrea Gilardi, Robin Lovelace
### 2022-06-08

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### Sobre mí...

Investigadora en la [Universidad de Salzburg](https://www.plus.ac.at/risk-hazard-climate/) 🛰

Amo codificar en R, aunque ahora trabajo también en Python 🐍

Si no estoy programando, me encuentran en la montaña en bici o de senderismo ⛰

![:scale 30%](https://dgtzuqphqg23d.cloudfront.net/JtVzfcASWgycVOcxPF_9w22mglBk42rCOKk_LpY4IKg-2048x1536.jpg)

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## ¡Comenzamos!

Link a la presentación: https://sfnetworks.github.io/rladies-gye/slides

Link al repositorio: https://github.com/sfnetworks/rladies-gye

[![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sfnetworks/rladies-gye/main?urlpath=rstudio)

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## Redes espaciales *tidy* en R

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![](figs/river_network.png)
]
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Nodos y aristas se encuentran en el espacio geográfico

Nodos se asocian a geometrías de puntos: **POINT**

Aristas se asocian a geometías de líneas: **LINESTRING**

La topología de la red no contiene *toda* la información de una red espacial

La topología **_y_** la información espacial son esenciales para su análisis

]

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## Redes espaciales *tidy* en R

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```r
library(tidyverse)
library(sfnetworks)
roxel |>
  as_tibble() |>
  select(name, type)
```

```
# A tibble: 851 x 2
 name type 
 <chr> <fct> 
 1 Havixbecker Strasse residential
 2 Pienersallee secondary 
 3 Schulte-Bernd-Strasse residential
 4 <NA> path 
 5 Welsingheide residential
 6 <NA> footway 
 7 <NA> footway 
 8 <NA> path 
 9 <NA> track 
10 <NA> track 
# ... with 841 more rows
```
]
]

.pull-right-30[

![:scale 15%](https://raw.githubusercontent.com/tidyverse/tidyverse/master/man/figures/logo.png)

**Tidyverse**

Colección de paquetes de R para ciencia de datos

Comparten una filosofía de estructura

Aplican estructura de datos *tidy*

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## Redes espaciales *tidy* en R

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```r
library(sf)
roxel
```

<PRE class="fansi fansi-output"><CODE>Simple feature collection with 851 features and 2 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 7.522594 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
Geodetic CRS: WGS 84
# A tibble: 851 x 3
 name type geometry
 * &lt;chr&gt; &lt;fct&gt; &lt;LINESTRING [°]&gt;
 1 Havixbecker Strasse residential (7.533722 51.95556, 7.533461 51.~
 2 Pienersallee secondary (7.532442 51.95422, 7.53236 51.9~
 3 Schulte-Bernd-Strasse residential (7.532709 51.95209, 7.532823 51.~
 4 NA path (7.540063 51.94468, 7.539696 51.~
 5 Welsingheide residential (7.537673 51.9475, 7.537614 51.9~
 6 NA footway (7.543791 51.94733, 7.54369 51.9~
 7 NA footway (7.54012 51.94478, 7.539931 51.9~
 8 NA path (7.53822 51.94546, 7.538131 51.9~
 9 NA track (7.540063 51.94468, 7.540338 51.~
10 NA track (7.5424 51.94599, 7.54205 51.946~
# ... with 841 more rows
</CODE></PRE>
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![:scale 15%](https://user-images.githubusercontent.com/520851/34887433-ce1d130e-f7c6-11e7-83fc-d60ad4fae6bd.gif)

**El paquete sf**

Paquete de R para ciencia de datos espaciales

Almacenamiento estandarizado de elementos geográficos (puntos, líneas, polígonos)

Operaciones geométricas (intersecciones, uniones, ..)

Compatible con tidyverse

Nuevos *verbos* específicos para datos espaciales

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## Redes espaciales *tidy* en R

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```r
library(tidygraph)
nodes = tibble(name = letters[1:4])
edges = tibble(from = c(1,2,3,4), to = c(2,3,4,1))
tbl_graph(nodes, edges)
```

```
# A tbl_graph: 4 nodes and 4 edges
#
# A directed simple graph with 1 component
#
# Node Data: 4 x 1 (active)
 name 
 <chr>
1 a 
2 b 
3 c 
4 d 
#
# Edge Data: 4 x 2
 from to
 <int> <int>
1 1 2
2 2 3
3 3 4
# ... with 1 more row
```
]
]

.pull-right-30[

![:scale 15%](https://raw.githubusercontent.com/thomasp85/tidygraph/master/man/figures/logo.png)

**El paquete tidygraph**

Interfaz *tidy* al paquete `igraph` para análisis de redes

Modela la red como una colección de dos tibbles

Soporta algoritmos de redes (centralidad, clustering, ruteo, ..)

Compatible con tidyverse

Nuevos *verbos* específicos para estructuras de redes

]

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## ¿Redes espaciales *tidy* en R?

<center><blockquote class="twitter-tweet">One of the biggest reasons we still have ArcGIS licenses is for Network Analysis (drive times, service areas etc). Does anyone have <a href="https://twitter.com/hashtag/foss4g?src=hash&amp;ref_src=twsrc%5Etfw">#foss4g</a> tools for this they like? Last time we tried pgRouting (yrs ago) it didn&#39;t feel fully formed yet, <a href="https://twitter.com/hashtag/gischat?src=hash&amp;ref_src=twsrc%5Etfw">#gischat</a>&mdash; Zev Ross (@zevross) <a href="https://twitter.com/zevross/status/1089908839816794118?ref_src=twsrc%5Etfw">January 28, 2019</a></blockquote></center> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

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## ¡Redes espaciales *tidy* en R!

.pull-left[
![](https://user-images.githubusercontent.com/520851/34887433-ce1d130e-f7c6-11e7-83fc-d60ad4fae6bd.gif)
]

.pull-right[
![:scale 38%](https://raw.githubusercontent.com/thomasp85/tidygraph/master/man/figures/logo.png)
]

.center[
![:scale 20%](https://raw.githubusercontent.com/luukvdmeer/sfnetworks/master/man/figures/logo.png)
]

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## ¡Redes espaciales *tidy* en R!

`tidygraph`: 
 
 > "... una cercana aproximación de datos *ordenados* para datos relacionales son dos *tidy data frames*, uno que describa los *nodos* y otro describiendo las *aristas*."
--
 
 
 
 
`sfnetworks`:

> “Una cercana aproximación de datos *ordenados* para datos relacionales .orange[*geoespaciales*] son dos .orange[*objetos sf*], uno que describa los *nodos* y otro describiendo las *aristas*”

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## Objeto `sfnetwork`

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```r
roxel |> 
  st_geometry() |>
  plot()
```
]

.pull-right-60[
<img src="slides_files/figure-html/unnamed-chunk-3-1.png" width="864" />
]

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## Objeto `sfnetwork`

.pull-left-40[

```r
roxel |> 
  as_sfnetwork() |>
  plot()
```
]

.pull-right-60[
<img src="slides_files/figure-html/unnamed-chunk-5-1.png" width="864" />
]

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## Objeto `sfnetwork`

.pull-left-40[

```r
roxel
```
]

.pull-right-60[

```
Simple feature collection with 851 features and 2 fields
Geometry type: LINESTRING
Dimension: XY
Bounding box: xmin: 7.522594 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
Geodetic CRS: WGS 84
# A tibble: 851 x 3
 name type geometry
 * <chr> <fct> <LINESTRING [°]>
 1 Havixbecker Strasse residential (7.533722 51.95556, 7.533461 51.~
 2 Pienersallee secondary (7.532442 51.95422, 7.53236 51.9~
 3 Schulte-Bernd-Strasse residential (7.532709 51.95209, 7.532823 51.~
 4 <NA> path (7.540063 51.94468, 7.539696 51.~
 5 Welsingheide residential (7.537673 51.9475, 7.537614 51.9~
 6 <NA> footway (7.543791 51.94733, 7.54369 51.9~
 7 <NA> footway (7.54012 51.94478, 7.539931 51.9~
 8 <NA> path (7.53822 51.94546, 7.538131 51.9~
 9 <NA> track (7.540063 51.94468, 7.540338 51.~
10 <NA> track (7.5424 51.94599, 7.54205 51.946~
# ... with 841 more rows
```
]

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## Objeto `sfnetwork`

.pull-left-40[

```r
roxel |> 
  as_sfnetwork()
```
]

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```
# A sfnetwork with 701 nodes and 851 edges
#
# CRS: EPSG:4326 
#
# A directed multigraph with 14 components with spatially explicit edges
#
# Node Data: 701 x 1 (active)
# Geometry type: POINT
# Dimension: XY
# Bounding box: xmin: 7.522622 ymin: 51.94151 xmax: 7.546705 ymax:
# 51.9612
 geometry
 <POINT [°]>
1 (7.533722 51.95556)
2 (7.533461 51.95576)
3 (7.532442 51.95422)
4 (7.53209 51.95328)
5 (7.532709 51.95209)
6 (7.532869 51.95257)
# ... with 695 more rows
#
# Edge Data: 851 x 5
# Geometry type: LINESTRING
# Dimension: XY
# Bounding box: xmin: 7.522594 ymin: 51.94151 xmax: 7.546705 ymax:
# 51.9612
 from to name type geometry
 <int> <int> <chr> <fct> <LINESTRING [°]>
1 1 2 Havixbecker Strasse residential (7.533722 51.95556, 7.53~
2 3 4 Pienersallee secondary (7.532442 51.95422, 7.53~
3 5 6 Schulte-Bernd-Strasse residential (7.532709 51.95209, 7.53~
# ... with 848 more rows
```
]

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## Objeto `sfnetwork`

.pull-left-40[

```r
roxel |> 
  as_sfnetwork() |>
  activate(nodes) |>
  st_as_sf()
```
]

.pull-right-60[

```
Simple feature collection with 701 features and 0 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 7.522622 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
Geodetic CRS: WGS 84
# A tibble: 701 x 1
 geometry
 <POINT [°]>
 1 (7.533722 51.95556)
 2 (7.533461 51.95576)
 3 (7.532442 51.95422)
 4 (7.53209 51.95328)
 5 (7.532709 51.95209)
 6 (7.532869 51.95257)
 7 (7.540063 51.94468)
 8 (7.53822 51.94546)
 9 (7.537673 51.9475)
10 (7.537614 51.94562)
# ... with 691 more rows
```
]

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## Objeto `sfnetwork`

.pull-left-40[

```r
roxel |> 
  as_sfnetwork() |>
  activate(edges) |>
  st_geometry()
```
]

.pull-right-60[

```
Geometry set for 851 features 
Geometry type: LINESTRING
Dimension:     XY
Bounding box:  xmin: 7.522594 ymin: 51.94151 xmax: 7.546705 ymax: 51.9612
Geodetic CRS:  WGS 84
First 5 geometries:
```

```
LINESTRING (7.533722 51.95556, 7.533461 51.95576)
```

```
LINESTRING (7.532442 51.95422, 7.53236 51.95377...
```

```
LINESTRING (7.532709 51.95209, 7.532823 51.9523...
```

```
LINESTRING (7.540063 51.94468, 7.539696 51.9447...
```

```
LINESTRING (7.537673 51.9475, 7.537614 51.94562)
```
]

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## Live demo!

Link al repositorio: https://github.com/sfnetworks/rladies-gye

[![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sfnetworks/rladies-gye/main?urlpath=rstudio)

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### ¿Qué podemos hacer?

#### Pre-procesamiento y limpieza de redes

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### Pre-procesamiento y limpieza de redes

#### Red inicial

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### Pre-procesamiento y limpieza de redes

#### Simplificar aristas

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### Pre-procesamiento y limpieza de redes

#### Subdividir aristas

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### Pre-procesamiento y limpieza de redes

#### Remover pseudo-nodos

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### Pre-procesamiento y limpieza de redes

#### Simplificar intersecciones

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### ¿Qué podemos hacer?

#### Snapping

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count: false
### Snapping 
 #### Mover puntos al nodo más cercano
<img src="slides_files/figure-html/snap_user_01_output-1.png" width="864" />

---
count: false
### Snapping 
 #### Mover puntos al nodo más cercano
<img src="slides_files/figure-html/snap_user_02_output-1.png" width="864" />

---
count: false
### Snapping 
 #### Mover puntos al nodo más cercano
<img src="slides_files/figure-html/snap_user_03_output-1.png" width="864" />

---
count: false
### Snapping 
 #### Mover puntos al nodo más cercano
<img src="slides_files/figure-html/snap_user_04_output-1.png" width="864" />

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count: false
### Snapping 
 #### Integrar puntos a la red
<img src="slides_files/figure-html/blend_user_01_output-1.png" width="864" />

---
count: false
### Snapping 
 #### Integrar puntos a la red
<img src="slides_files/figure-html/blend_user_02_output-1.png" width="864" />

---
count: false
### Snapping 
 #### Integrar puntos a la red
<img src="slides_files/figure-html/blend_user_03_output-1.png" width="864" />

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### ¿Qué podemos hacer?

#### Ruteo

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count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_01_output-1.png" width="864" />

---
count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_02_output-1.png" width="864" />

---
count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_03_output-1.png" width="864" />

---
count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_04_output-1.png" width="864" />

---
count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_05_output-1.png" width="864" />

---
count: false
### Ruteo 
 #### Calcular el camino más corto
<img src="slides_files/figure-html/plotpath_user_06_output-1.png" width="864" />

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### Ruteo

#### Obtener una matriz origen/destino

```r
st_network_cost(
  net, 
  from = c(p1, p2, p3),
  to = c(p1, p2, p3)
)
```

```
         [,1]     [,2]     [,3]
[1,]    0.000 1614.252 2094.555
[2,] 1614.252    0.000 1315.965
[3,] 2094.555 1315.965    0.000
```

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## Live demo!

Link al repositorio: https://github.com/sfnetworks/rladies-gye

[![Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/sfnetworks/rladies-gye/main?urlpath=rstudio)

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### ¿Qué más?

#### Mucho más...!

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## Instalación:

Desde CRAN:

```r
install.packages("sfnetworks")
```

Versión en desarrollo en GitHub:

```r
remotes::install_github("luukvdmeer/sfnetworks")
```

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### ¿Quieren más?

Dense una vuelta por las [viñetas del paquete](https://luukvdmeer.github.io/sfnetworks/index.html)

### ¿Tienen sus propios ejemplos o ideas?

Únanse a la  [Discusión en GitHub](https://github.com/luukvdmeer/sfnetworks/discussions)

### ¿Encontraron un bug?

Hágannos saber en un [issue aquí](https://github.com/luukvdmeer/sfnetworks/issues)!

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### Gracias por su atención!

.note[
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Projecto financiado por: ![:scale 50%](https://raw.githubusercontent.com/RConsortium/artwork/main/r_consortium/R_Consortium-logo-horizontal-color.png)
]

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Slides powered by [xaringan](https://github.com/yihui/xaringan), [xaringanthemer](https://github.com/gadenbuie/xaringanthemer) and [flipbookr](https://github.com/EvaMaeRey/flipbookr) 
]
]
.pull-right-30[
![:scale 50%](figs/rladies.jpg)
]
]