Fundamental of Data Science for EESS

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# Fundamental of Data Science for EESS

---

## R session 06 - Data mapping

2021-02-24

---
layout: false
class: middle, inverse

# Outline

---
exclude: true

## Resources used
* Simple maps : https://www.r-spatial.org/r/2018/10/25/ggplot2-sf.html

## Other resources
* Global maps : https://github.com/e-cavan/spatial_mapping_R
* Ocean maps: https://www.researchgate.net/profile/Robert_Bauer9/publication/315494507_oceanmap_Mapping_oceanographic_data/links/58d2987292851cd76d346f65/oceanmap-Mapping-oceanographic-data.pdf

---

# Installation and Resources

## Packages

### New
* sf
* rnaturalearth
* rnaturalearthdata
* leaflet

### Previously used
* ggplot2
* stringr
* dplyr

]

#### Reading list
* [Geocomputation with R - Chapter 2](https://geocompr.robinlovelace.net/spatial-class.html)
* [Geocomputation with R - Chapter 8](https://geocompr.robinlovelace.net/adv-map.html)

#### Other resources
* [Spatial data science](https://keen-swartz-3146c4.netlify.com/index.html)
* [Modern geospatial analysis with R](http://files.zevross.com/workshops/spatial/slides/html/0-deck-list.html)

]

---

# What we want to do...

---
layout: true

# Simple Features (sf)

---

* https://github.com/r-spatial/sf

---

* Simple features is an open standard developed and endorsed by the Open Geospatial Consortium (OGC). 
* Simple features is a hierarchical data model that represents a wide range of geometry types.

---

* A **point** is simply a coordinate in 2D (can be also 3D or 4D space)
    * POINT (5 2)

* A **linestring** is a sequence of points with a straight line connecting the points
    * LINESTRING (1 5, 4 4, 4 1, 2 2, 3 2)

* A **polygon** is a sequence of points that form a closed, non-intersecting ring. 
    * POLYGON (1 5, 2 2, 4 1, 4 4, 1 5)

---

* MULTIPOINT (5 2, 1 3, 3 4, 3 2)
  * MULTILINESTRING ((1 5, 4 4, 4 1, 2 2, 3 2), (1 2, 2 4))
  * MULTIPOLYGON (((1 5, 2 2, 4 1, 4 4, 1 5), (0 2, 1 2, 1 3, 0 3, 0 2)))

---

* A **geometry collection** can contain any combination of geometries including (multi)points and linestrings
    * GEOMETRYCOLLECTION (MULTIPOINT (5 2, 1 3, 3 4, 3 2), LINESTRING (1 5, 4 4, 4 1, 2 2, 3 2))

---

* Simple feature objects in R are stored in a data frame
* Geographic data occupying a special column, usually named `geom` or `geometry`.

Three classes of sf objects
* **sfg** : geometry
* **sfc** : column - set of geometry plus coordinates system
* **sf** : information about each geometry

---

## sf geometry (sfg) class

```r
library(sf)
```

```
Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
```

--
* Creating a point from a vector

```r
sf::st_point(c(5, 2))
```

```
POINT (5 2)
```

--
* For line, we need to create a **matrix** with rbind

```r
multipoint_matrix = rbind(c(5, 2), c(1, 3), c(3, 4), c(3, 2))
st_multipoint(multipoint_matrix)
```

```
MULTIPOINT ((5 2), (1 3), (3 4), (3 2))
```

---

## sf geometry (sfg) class

* For multiline, we need to create a **list of matrices**

```r
multilinestring_list = list(rbind(c(1, 5), c(4, 4), c(4, 1), c(2, 2), c(3, 2)), 
                            rbind(c(1, 2), c(2, 4)))
st_multilinestring((multilinestring_list))
```

```
MULTILINESTRING ((1 5, 4 4, 4 1, 2 2, 3 2), (1 2, 2 4))
```

--
* Idem for geometry collection

```r
geometrycollection_list = list(sf::st_multipoint(multipoint_matrix),
                              sf::st_multilinestring(multilinestring_list))
st_geometrycollection(geometrycollection_list)
```

```
GEOMETRYCOLLECTION (MULTIPOINT ((5 2), (1 3), (3 4), (3 2)), MULTILINESTRING ((1 5, 4 4, 4 1, 2 2, 3 2), (1 2, 2 4)))
```

---

## sf column (sfc) class

List of sfg obkects that also contains also information about the coordinate system

```r
point1 = st_point(c(5, 2))
point2 = st_point(c(1, 3))
points_sfc = st_sfc(point1, point2)
points_sfc
```

```
Geometry set for 2 features 
geometry type:  POINT
dimension:      XY
bbox:           xmin: 1 ymin: 2 xmax: 5 ymax: 3
CRS:            NA
```

```
POINT (5 2)
```

```
POINT (1 3)
```

---

## sf column (sfc) class

Now add Coordinate Reference System (crs)

```r
st_sfc(point1, point2, crs = 4326)
```

```
Geometry set for 2 features 
geometry type:  POINT
dimension:      XY
bbox:           xmin: 1 ymin: 2 xmax: 5 ymax: 3
geographic CRS: WGS 84
```

```
POINT (5 2)
```

```
POINT (1 3)
```

---

## sf class

Add some information about the geometry.

```r
lnd_point = st_point(c(0.1, 51.5))                 # sfg object
lnd_geom = st_sfc(lnd_point, crs = 4326)           # sfc object
lnd_attrib = data.frame(                           # data.frame object
  name = "London",
  temperature = 25,
  date = as.Date("2017-06-21")
  )
st_sf(lnd_attrib, geometry = lnd_geom)
```

```
Simple feature collection with 1 feature and 3 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 0.1 ymin: 51.5 xmax: 0.1 ymax: 51.5
geographic CRS: WGS 84
    name temperature       date         geometry
1 London          25 2017-06-21 POINT (0.1 51.5)
```

---
layout: true

# Static maps

---

## Load necessary libraries

```r
library("readxl") # Import the data from Excel file
library("dplyr")  # filter and reformat data frames

library("ggplot2") # graphics
library("sf") # simple features
library("rnaturalearth") 
library("rnaturalearthdata")
```

---

## Read the world map data

* `scale` can be 'small', 'medium', 'large'
* `returnclass` can be 'sp' or 'sf' - sf (simple features) is an evolution of sp

```r
world <- rnaturalearth::ne_countries(scale = "medium", returnclass = "sf")
```

---

The world data are returned as a sf (simple feature) dataframe which contains
* normal fields
* one field called geometry which contains points, lines or polygon coordinate information

```r
colnames(world)
```

```
 [1] "scalerank"  "featurecla" "labelrank"  "sovereignt" "sov_a3"    
 [6] "adm0_dif"   "level"      "type"       "admin"      "adm0_a3"   
[11] "geou_dif"   "geounit"    "gu_a3"      "su_dif"     "subunit"   
[16] "su_a3"      "brk_diff"   "name"       "name_long"  "brk_a3"    
[21] "brk_name"   "brk_group"  "abbrev"     "postal"     "formal_en" 
[26] "formal_fr"  "note_adm0"  "note_brk"   "name_sort"  "name_alt"  
[31] "mapcolor7"  "mapcolor8"  "mapcolor9"  "mapcolor13" "pop_est"   
[36] "gdp_md_est" "pop_year"   "lastcensus" "gdp_year"   "economy"   
[41] "income_grp" "wikipedia"  "fips_10"    "iso_a2"     "iso_a3"    
[46] "iso_n3"     "un_a3"      "wb_a2"      "wb_a3"      "woe_id"    
[51] "adm0_a3_is" "adm0_a3_us" "adm0_a3_un" "adm0_a3_wb" "continent" 
[56] "region_un"  "subregion"  "region_wb"  "name_len"   "long_len"  
[61] "abbrev_len" "tiny"       "homepart"   "geometry"  
```

---

* The field `name` contains the name of the countries, `continent` the continent, etc...
* The field `geometry` contains the country outline
<table class="table table-striped table-hover table-condensed" style="font-size: 9px; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;"> name </th>
   <th style="text-align:left;"> continent </th>
   <th style="text-align:left;"> geometry </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Aruba </td>
   <td style="text-align:left;"> North America </td>
   <td style="text-align:left;"> MULTIPOLYGON (((-69.89912 1... </td>
  </tr>
</tbody>
</table>
--

```r
world$geometry[1]
```

```
Geometry set for 1 feature 
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -70.06611 ymin: 12.423 xmax: -69.8957 ymax: 12.61411
CRS:            +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0
```

---

## A simple world map

```r
# Set the black and white theme
theme_set(theme_bw())

ggplot(data = world) +
    geom_sf() 
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-22-1.png" width="80%" style="display: block; margin: auto;" />
]

---

## A simple world map

```r
ggplot(data = world) +
    geom_sf() +
    coord_sf(expand = FALSE)
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-23-1.png" width="80%" style="display: block; margin: auto;" />
]

---

## Color continents

```r
ggplot(data = world) +
    geom_sf(color="white", fill="blue")+
    coord_sf(expand = FALSE) 
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-24-1.png" width="80%" style="display: block; margin: auto;" />
]

---
## Plot population

```r
ggplot(data = world) +
    geom_sf(aes(fill= pop_est))+
    coord_sf(expand = FALSE)
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-25-1.png" width="80%" style="display: block; margin: auto;" />
]

---
## Plot population

```r
ggplot(data = world) +
    geom_sf(aes(fill= pop_est)) +
    coord_sf(expand = FALSE) +
    scale_fill_viridis_c(trans = "log10")
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-26-1.png" width="80%" style="display: block; margin: auto;" />
]

---
## Modify projections
.left-code[
* Specify coordinate system: https://geocompr.robinlovelace.net/spatial-class.html#crs-intro

* Lambert projection
    * From the North Pole
    * "+proj=laea +lat_0=90 +lon_0=0 "

```r
ggplot(data = world) +
    geom_sf() +
    coord_sf(expand = FALSE,
             crs = "+proj=laea +lat_0=90 +lon_0=0 ")
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-27-1.png" width="70%" style="display: block; margin: auto;" />
]

---
## Zoom
.left-code[
* Centered on Singapore

```r
ggplot(data = world) +
    geom_sf() +
    coord_sf(xlim=c(90,110), 
             ylim=c(-10,10))
```
.warning[Resolution is not optimal]
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-28-1.png" width="70%" style="display: block; margin: auto;" />
]

---
## Add country names

* Must first define coordinates centroid of each country (X and Y)

```r
world_centroids<- st_coordinates(st_centroid(world$geometry))
```
--
* Bind the 2 tables

```r
world_centroids <- cbind(world, world_centroids)
```

---
## Add country names

```r
ggplot(data = world_centroids) +
    geom_sf() +
    coord_sf(xlim=c(70,130), 
             ylim=c(-20,20)) +
    geom_text(aes(x = X, y=Y, label=name), 
              size=5) +
    xlab("Longitude") +
    ylab("Latitude")
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-32-1.png" width="80%" style="display: block; margin: auto;" />
]

---
layout: true

# Plot data

---

## Read the data

```r
bolido <- readxl::read_excel("data/bolido.xlsx")
```

<table class="table table-striped table-hover table-condensed" style="font-size: 9px; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;"> cruise </th>
   <th style="text-align:left;"> station_id </th>
   <th style="text-align:left;"> date </th>
   <th style="text-align:left;"> depth_level </th>
   <th style="text-align:right;"> depth </th>
   <th style="text-align:right;"> latitude </th>
   <th style="text-align:right;"> longitude </th>
   <th style="text-align:left;"> oceanic_region </th>
   <th style="text-align:right;"> temperature </th>
   <th style="text-align:right;"> salinity </th>
   <th style="text-align:right;"> reads_total </th>
   <th style="text-align:right;"> bolido_reads </th>
   <th style="text-align:right;"> bolido_pct </th>
   <th style="text-align:left;"> species_dominant </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 430 </td>
   <td style="text-align:left;"> 2009-08-18 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 71.1300 </td>
   <td style="text-align:right;"> -136.420 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> -0.804 </td>
   <td style="text-align:right;"> 25.935 </td>
   <td style="text-align:right;"> 10495 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 0.0381134 </td>
   <td style="text-align:left;"> Parmales_env_3B_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 460 </td>
   <td style="text-align:left;"> 2009-08-19 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 70.4000 </td>
   <td style="text-align:right;"> -136.030 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> 0.076 </td>
   <td style="text-align:right;"> 25.384 </td>
   <td style="text-align:right;"> 9591 </td>
   <td style="text-align:right;"> 4 </td>
   <td style="text-align:right;"> 0.0417058 </td>
   <td style="text-align:left;"> Parmales_env_3B_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 540 </td>
   <td style="text-align:left;"> 2009-08-17 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 70.4500 </td>
   <td style="text-align:right;"> -137.530 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> -0.610 </td>
   <td style="text-align:right;"> 26.246 </td>
   <td style="text-align:right;"> 9900 </td>
   <td style="text-align:right;"> 14 </td>
   <td style="text-align:right;"> 0.1414141 </td>
   <td style="text-align:left;"> Parmales_env_3B_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 620 </td>
   <td style="text-align:left;"> 2009-08-11 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 70.6800 </td>
   <td style="text-align:right;"> -139.627 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> 1.231 </td>
   <td style="text-align:right;"> 22.522 </td>
   <td style="text-align:right;"> 7557 </td>
   <td style="text-align:right;"> 11 </td>
   <td style="text-align:right;"> 0.1455604 </td>
   <td style="text-align:left;"> Parmales_env_3B_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 670 </td>
   <td style="text-align:left;"> 2009-08-10 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 69.7980 </td>
   <td style="text-align:right;"> -138.441 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> 3.740 </td>
   <td style="text-align:right;"> 23.560 </td>
   <td style="text-align:right;"> 8348 </td>
   <td style="text-align:right;"> 22 </td>
   <td style="text-align:right;"> 0.2635362 </td>
   <td style="text-align:left;"> Parmales_env_3B_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> MALINA </td>
   <td style="text-align:left;"> 760 </td>
   <td style="text-align:left;"> 2009-08-12 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 3 </td>
   <td style="text-align:right;"> 70.3300 </td>
   <td style="text-align:right;"> -140.470 </td>
   <td style="text-align:left;"> Beaufort Sea </td>
   <td style="text-align:right;"> 0.511 </td>
   <td style="text-align:right;"> 22.455 </td>
   <td style="text-align:right;"> 8319 </td>
   <td style="text-align:right;"> 6 </td>
   <td style="text-align:right;"> 0.0721241 </td>
   <td style="text-align:left;"> Parmales_env_3A_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CASES </td>
   <td style="text-align:left;"> CA15 </td>
   <td style="text-align:left;"> 2003-10-01 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 29 </td>
   <td style="text-align:right;"> 71.5367 </td>
   <td style="text-align:right;"> -126.955 </td>
   <td style="text-align:left;"> Arctic Ocean </td>
   <td style="text-align:right;"> -0.780 </td>
   <td style="text-align:right;"> 30.620 </td>
   <td style="text-align:right;"> 12354 </td>
   <td style="text-align:right;"> 211 </td>
   <td style="text-align:right;"> 1.7079488 </td>
   <td style="text-align:left;"> Parmales_env_1_X_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CASES </td>
   <td style="text-align:left;"> 200 </td>
   <td style="text-align:left;"> 2003-11-01 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 35 </td>
   <td style="text-align:right;"> 69.9290 </td>
   <td style="text-align:right;"> -126.489 </td>
   <td style="text-align:left;"> Arctic Ocean </td>
   <td style="text-align:right;"> -1.460 </td>
   <td style="text-align:right;"> 31.500 </td>
   <td style="text-align:right;"> 12797 </td>
   <td style="text-align:right;"> 544 </td>
   <td style="text-align:right;"> 4.2509963 </td>
   <td style="text-align:left;"> Parmales_env_1_X_sp. </td>
  </tr>
  <tr>
   <td style="text-align:left;"> ArcticNet </td>
   <td style="text-align:left;"> CA18 </td>
   <td style="text-align:left;"> 2005-09-01 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 32 </td>
   <td style="text-align:right;"> 70.6663 </td>
   <td style="text-align:right;"> -122.993 </td>
   <td style="text-align:left;"> Arctic Ocean </td>
   <td style="text-align:right;"> -1.040 </td>
   <td style="text-align:right;"> 32.040 </td>
   <td style="text-align:right;"> 9531 </td>
   <td style="text-align:right;"> 43 </td>
   <td style="text-align:right;"> 0.4511594 </td>
   <td style="text-align:left;"> Triparma_laevis_clade </td>
  </tr>
  <tr>
   <td style="text-align:left;"> CFL </td>
   <td style="text-align:left;"> 405 </td>
   <td style="text-align:left;"> 2007-11-01 </td>
   <td style="text-align:left;"> surface </td>
   <td style="text-align:right;"> 10 </td>
   <td style="text-align:right;"> 70.6217 </td>
   <td style="text-align:right;"> -123.001 </td>
   <td style="text-align:left;"> Arctic Ocean </td>
   <td style="text-align:right;"> -1.650 </td>
   <td style="text-align:right;"> 30.130 </td>
   <td style="text-align:right;"> 13471 </td>
   <td style="text-align:right;"> 20 </td>
   <td style="text-align:right;"> 0.1484671 </td>
   <td style="text-align:left;"> Parmales_env_1_X_sp. </td>
  </tr>
</tbody>
</table>

---

## A bit of biology... Bolidophyceae and Parmales

.pull-left[
### _Triparma_
<img src="img/2011-Ichinomya-Triparma.png" width="70%" style="display: block; margin: auto;" />
* Covered with silica
]

.pull-right[
### _Bolidomonas_
<img src="img/1999-Guillou-Bolidomonas_drawing.png" width="50%" style="display: block; margin: auto;" />
* 1.5 µm
]

.footnote[_Guillou, L., Chrétiennot-Dinet, M.-J., Medlin, L.K., Claustre, H., Loiseaux-de Goër, S. & Vaulot, D. 1999. J. Phycol. 35:368–81.  
Ichinomiya, M., Yoshikawa, S., Kamiya, M., Ohki, K., Takaichi, S. & Kuwata, A. 2011. J. Phycol. 47:144–51.  
Ichinomiya, M., dos Santos, A.L., Gourvil, P., Yoshikawa, S., Kamiya, M., Ohki, K., Audic, S. et al. 2016. ISME J. 10:2419–34._
]

---

## Plot the stations where Bolidophyceae found

```r
ggplot(data = world) +
    geom_sf()+
    coord_sf(expand = FALSE) +
    geom_point(data=filter(bolido, 
                           bolido_pct >0), 
               aes(x=longitude, 
                   y=latitude), 
               size=3)
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-37-1.png" width="90%" style="display: block; margin: auto;" />
]

---

## Percentage of Bolidophyceae

```r
ggplot(data = world) +
    geom_sf()+
    coord_sf(expand = FALSE) +
    geom_point(data=filter(bolido, 
                           bolido_pct >0), 
               aes(x=longitude, 
                   y=latitude, 
                   size=bolido_pct),
               color="blue")
```
]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-38-1.png" width="90%" style="display: block; margin: auto;" />
]

---

## Dominant species of _Triparma_

```r
ggplot(data = world) +
    geom_sf()+
    coord_sf(expand = FALSE) +
    geom_point(data=filter(bolido, 
                           bolido_pct >0,
                           stringr::str_detect(species_dominant, "Triparma")), 
               aes(x=longitude, 
                   y=latitude,
                   color=species_dominant),
               size = 4) +
   scale_colour_viridis_d() +
   theme(legend.position="bottom") +
   guides(color=guide_legend(nrow=2,
                             byrow=TRUE))
```

]

.right-plot[
<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-39-1.png" width="90%" style="display: block; margin: auto;" />
]

---

# Interactive maps

---

## Leaflet

.pull-left[
* Javascript: https://leafletjs.com/
* Leaflet for R : https://rstudio.github.io/leaflet/
* All functions from `leaflet` package

```r
library("leaflet") 
```
]

---

## Create an empty map

```r
leaflet(width = 750, height = 500)
```

]

.right-plot[
<div id="htmlwidget-374249350da8652dc877" style="width:750px;height:500px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-374249350da8652dc877">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}}},"evals":[],"jsHooks":[]}</script>
]

---

## Add background (tiles)

```r
leaflet(width = 750, height = 500)%>%
  addTiles()
```

]

.right-plot[
<div id="htmlwidget-6ebfed771af2f5a95e67" style="width:750px;height:500px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-6ebfed771af2f5a95e67">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addTiles","args":["//{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",null,null,{"minZoom":0,"maxZoom":18,"tileSize":256,"subdomains":"abc","errorTileUrl":"","tms":false,"noWrap":false,"zoomOffset":0,"zoomReverse":false,"opacity":1,"zIndex":1,"detectRetina":false,"attribution":"© <a href=\"http://openstreetmap.org\">OpenStreetMap<\/a> contributors, <a href=\"http://creativecommons.org/licenses/by-sa/2.0/\">CC-BY-SA<\/a>"}]}]},"evals":[],"jsHooks":[]}</script>
]

---

## Set limits and zoom

```r
leaflet(width = 750, height = 500)%>%
  addTiles() %>%
  setView(lng=0, lat=0, zoom=2)
```

]

.right-plot[
<div id="htmlwidget-fb2f782c8ebe8b1f1718" style="width:750px;height:500px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-fb2f782c8ebe8b1f1718">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addTiles","args":["//{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",null,null,{"minZoom":0,"maxZoom":18,"tileSize":256,"subdomains":"abc","errorTileUrl":"","tms":false,"noWrap":false,"zoomOffset":0,"zoomReverse":false,"opacity":1,"zIndex":1,"detectRetina":false,"attribution":"© <a href=\"http://openstreetmap.org\">OpenStreetMap<\/a> contributors, <a href=\"http://creativecommons.org/licenses/by-sa/2.0/\">CC-BY-SA<\/a>"}]}],"setView":[[0,0],2,[]]},"evals":[],"jsHooks":[]}</script>
]

---

## Adding data points

```r
leaflet(width = 750, height = 500)%>%
  addTiles() %>%
  setView(lng=0, lat=0, zoom=2) %>% 
  addCircleMarkers(data = bolido, 
                   lat = ~ latitude, 
                   lng = ~ longitude,
               radius = 5,
         label = ~ station_id,
         labelOptions = labelOptions(textsize = "10px", 
                                     noHide = T),
         clusterOptions = markerClusterOptions())
```

]

.right-plot[
<div id="htmlwidget-eed36c51dc0ee197bee0" style="width:750px;height:500px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-eed36c51dc0ee197bee0">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addTiles","args":["//{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",null,null,{"minZoom":0,"maxZoom":18,"tileSize":256,"subdomains":"abc","errorTileUrl":"","tms":false,"noWrap":false,"zoomOffset":0,"zoomReverse":false,"opacity":1,"zIndex":1,"detectRetina":false,"attribution":"© <a href=\"http://openstreetmap.org\">OpenStreetMap<\/a> contributors, <a href=\"http://creativecommons.org/licenses/by-sa/2.0/\">CC-BY-SA<\/a>"}]},{"method":"addCircleMarkers","args":[[71.13,70.4,70.45,70.68,69.798,70.33,71.5367,69.929,70.6663,70.6217,71.3297,70.6645,-62.2038,-62.2042,-62.2066,-62.211,-62.2164,-62.2113,-62.2161,-62.2204,-62.2239,-62.228,78.8292,78.8288,78.7538,78.8327,78.824,78.6102,79.0643,79.7397,81.4935,83.9227,83.5882,82.1657,77.3968,81.8758,85.159,87.9245,50.151,41.8398,35.35,32.7418,32.646,32.7747,69.0233,65.9449,39.1404,38.7573,38.6769,40.1451,40.6599,38.6667,34.41,39.1343,39.4151,37.167,51.7423,29.4667,32.822,34.3244,55.0331,66.0069,66.0078,65.4886,65.8172,43.1758,66.1316,42.2449,32.0694,-33.8971,42.49,60.1612,31.3836,31.9828,21.2688,51.3614,78.4533,8.5216,53.5809,-34.37,-34.6759,-34.42,44.6936,36.9977,44.6667,59.8162,59.8996,59.622,37.4328,48.359,43.6861,56.9631,58.957,60.1433,57.8498,43.4325,65.7064,38.4133,51.7961,51.4347,51.2695,51.3073,51.3749,51.441,51.4716,51.3348,51.2777,51.1857,51.5803,35.3637,51.4584,51.7483,51.6829,51.4816,38.8855,-64.774,35,48.7778,64.2083,45.08,43.2264,35.1927,35.0864,35.82,16.8026,27.4694,54.1819,59.8822,31.216,38.6792,39.3322,26.1029,24.7449,32.7524,40.808,48.0405,38.2686,32.867,27.6158,30.2484,45.502,45.4125,45.3256,43.3333,9.3485,33.9126,33.907,43.8444,43.8604,21.2888,21.2866,34.7181,35.661,41.6666,33.3231,41.5245,53.2254,45.3144,46.4416,-36.2928,45.4568,-17.2894,45.4142,-45.7442,54.8333,41.6835,41.1416,43.9475,43.8514,43.57,32.16,74.31,37.0051,38.4843,-50.05,-52.93,-60.82,-66.39,-69.09,-69.38,78.8403,78.832,78.8348,78.8332,78.8333],[-136.42,-136.03,-137.53,-139.627,-138.441,-140.47,-126.955,-126.489,-122.993,-123.001,-133.766,-122.998,-58.9361,-58.9267,-58.9178,-58.907,-58.9017,-58.9537,-58.9498,-58.948,-58.9427,-58.9325,7.0223,4.0085,-12.7862,-4.5963,-3.939,5.068,3.3328,4.5053,30.1722,60.6552,87.4518,126.97,118.196,130.878,123.359,61.125,-4.13,-83.1899,25.29,-16.7113,-16.9102,-16.8287,-105.343,-22.4192,-9.38011,-8.96633,-9.01239,-8.86933,-8.70376,-9.4367,-9.51,-9.38478,-9.21883,-7.504,-8.3112,34.9291,32.954,135.121,-1.43278,-18.1965,-18.1953,-18.0608,-18.1018,27.9086,-18.7902,27.4008,34.843,18.3868,3.15,5.11504,-80.8667,-81.0167,-157.722,3.11886,-2.82967,81.0521,8.14864,-54.16,-54.2752,-54.16,-63.6403,-7.97312,-1.16666,10.5986,10.72,10.6282,-25.19,-4.552,7.31567,-2.1031,-2.9726,-1.2825,-5.6495,2.89966,-18.1181,27.0342,1.01296,2.81087,2.9047,2.84933,3.21833,3.13995,3.05917,2.50215,2.6135,2.70167,2.7897,33.2896,2.35047,2.698,2.4152,2.45148,-76.5416,-64.0529,33,-3.9375,-22.015,13.61,5.74583,-2.88005,-2.21466,-5.75,-88.0816,-80.2834,7.9,23.2538,29.966,-76.1742,-75.4699,-80.0931,-80.7838,-79.8995,14.25,-123.026,15.6371,-117.257,-82.7259,-88.7483,12.4176,12.5265,13.3319,-1.925,-82.266,27.0253,27.0415,-69.6409,-69.5781,-156.864,-157.844,-76.6707,24.99,2.8,-79.1676,-70.6722,-4.15903,12.5083,30.7759,174.819,12.2605,-149.54,12.4378,170.771,10,-8.8341,-8.6668,12.935,13.0731,13.595,-64.5,-20.3043,-7.97312,21.3169,-178.41,-178.41,-170.93,-166.01,-164.88,-164.86,-11.9727,-8.006,-4.93217,-3.89483,-0.508333],5,null,null,{"interactive":true,"className":"","stroke":true,"color":"#03F","weight":5,"opacity":0.5,"fill":true,"fillColor":"#03F","fillOpacity":0.2},{"showCoverageOnHover":true,"zoomToBoundsOnClick":true,"spiderfyOnMaxZoom":true,"removeOutsideVisibleBounds":true,"spiderLegPolylineOptions":{"weight":1.5,"color":"#222","opacity":0.5},"freezeAtZoom":false},null,null,null,["430","460","540","620","670","760","CA15","200","CA18","405","BFB5","405","A1","A2","A3","A4","A5","G1","G2","G3","G4","G5","27","53","114","130","132","176","183","185","209","235","250","287","311","329","341","357","1","10","100","101","102","103","105","106","107","108","109","110","111","113","114","115","116","117","118","122","123","124","125","126","127","128","129","13","130","131","132","133","14","141","142","143","144","145","146","147","148","149","150","151","152","153","154","155","156","157","158","159","15","162","163","164","165","166","167","168","169","17","170","171","172","173","174","175","176","177","178","18","182","183","184","185","186","187","19","2","20","21","22","24","25","26","28","29","3","30","34","35","36","37","38","39","4","41","42","43","45","46","47","48","49","50","51","52","53","54","55","56","57","58","5","6","60","61","62","63","64","65","69","7","70","71","72","73","74","76","77","78","8","80","81","90","6","8","16","22","25","26","T1","T5","T6","T7","T9"],{"interactive":false,"permanent":true,"direction":"auto","opacity":1,"offset":[0,0],"textsize":"10px","textOnly":false,"className":"","sticky":true},null]}],"setView":[[0,0],2,[]],"limits":{"lat":[-69.38,87.9245],"lng":[-178.41,174.819]}},"evals":[],"jsHooks":[]}</script>
]

---

## Adding background

```r
leaflet(width = 750, height = 500)%>%
  addTiles() %>%
  setView(lng=0, lat=0, zoom=2) %>% 
  addCircleMarkers(data = bolido, 
                   lat = ~ latitude, 
                   lng = ~ longitude,
               radius = 5,
         label = ~ station_id,
         labelOptions = labelOptions(textsize = "10px", noHide = T),
         clusterOptions = markerClusterOptions()) %>% 
  addProviderTiles(providers$Esri.OceanBasemap)
```
* https://leaflet-extras.github.io/leaflet-providers/preview/

]

.right-plot[
<div id="htmlwidget-a573dac887d6a71345b1" style="width:750px;height:500px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-a573dac887d6a71345b1">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addTiles","args":["//{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",null,null,{"minZoom":0,"maxZoom":18,"tileSize":256,"subdomains":"abc","errorTileUrl":"","tms":false,"noWrap":false,"zoomOffset":0,"zoomReverse":false,"opacity":1,"zIndex":1,"detectRetina":false,"attribution":"© <a href=\"http://openstreetmap.org\">OpenStreetMap<\/a> contributors, <a href=\"http://creativecommons.org/licenses/by-sa/2.0/\">CC-BY-SA<\/a>"}]},{"method":"addCircleMarkers","args":[[71.13,70.4,70.45,70.68,69.798,70.33,71.5367,69.929,70.6663,70.6217,71.3297,70.6645,-62.2038,-62.2042,-62.2066,-62.211,-62.2164,-62.2113,-62.2161,-62.2204,-62.2239,-62.228,78.8292,78.8288,78.7538,78.8327,78.824,78.6102,79.0643,79.7397,81.4935,83.9227,83.5882,82.1657,77.3968,81.8758,85.159,87.9245,50.151,41.8398,35.35,32.7418,32.646,32.7747,69.0233,65.9449,39.1404,38.7573,38.6769,40.1451,40.6599,38.6667,34.41,39.1343,39.4151,37.167,51.7423,29.4667,32.822,34.3244,55.0331,66.0069,66.0078,65.4886,65.8172,43.1758,66.1316,42.2449,32.0694,-33.8971,42.49,60.1612,31.3836,31.9828,21.2688,51.3614,78.4533,8.5216,53.5809,-34.37,-34.6759,-34.42,44.6936,36.9977,44.6667,59.8162,59.8996,59.622,37.4328,48.359,43.6861,56.9631,58.957,60.1433,57.8498,43.4325,65.7064,38.4133,51.7961,51.4347,51.2695,51.3073,51.3749,51.441,51.4716,51.3348,51.2777,51.1857,51.5803,35.3637,51.4584,51.7483,51.6829,51.4816,38.8855,-64.774,35,48.7778,64.2083,45.08,43.2264,35.1927,35.0864,35.82,16.8026,27.4694,54.1819,59.8822,31.216,38.6792,39.3322,26.1029,24.7449,32.7524,40.808,48.0405,38.2686,32.867,27.6158,30.2484,45.502,45.4125,45.3256,43.3333,9.3485,33.9126,33.907,43.8444,43.8604,21.2888,21.2866,34.7181,35.661,41.6666,33.3231,41.5245,53.2254,45.3144,46.4416,-36.2928,45.4568,-17.2894,45.4142,-45.7442,54.8333,41.6835,41.1416,43.9475,43.8514,43.57,32.16,74.31,37.0051,38.4843,-50.05,-52.93,-60.82,-66.39,-69.09,-69.38,78.8403,78.832,78.8348,78.8332,78.8333],[-136.42,-136.03,-137.53,-139.627,-138.441,-140.47,-126.955,-126.489,-122.993,-123.001,-133.766,-122.998,-58.9361,-58.9267,-58.9178,-58.907,-58.9017,-58.9537,-58.9498,-58.948,-58.9427,-58.9325,7.0223,4.0085,-12.7862,-4.5963,-3.939,5.068,3.3328,4.5053,30.1722,60.6552,87.4518,126.97,118.196,130.878,123.359,61.125,-4.13,-83.1899,25.29,-16.7113,-16.9102,-16.8287,-105.343,-22.4192,-9.38011,-8.96633,-9.01239,-8.86933,-8.70376,-9.4367,-9.51,-9.38478,-9.21883,-7.504,-8.3112,34.9291,32.954,135.121,-1.43278,-18.1965,-18.1953,-18.0608,-18.1018,27.9086,-18.7902,27.4008,34.843,18.3868,3.15,5.11504,-80.8667,-81.0167,-157.722,3.11886,-2.82967,81.0521,8.14864,-54.16,-54.2752,-54.16,-63.6403,-7.97312,-1.16666,10.5986,10.72,10.6282,-25.19,-4.552,7.31567,-2.1031,-2.9726,-1.2825,-5.6495,2.89966,-18.1181,27.0342,1.01296,2.81087,2.9047,2.84933,3.21833,3.13995,3.05917,2.50215,2.6135,2.70167,2.7897,33.2896,2.35047,2.698,2.4152,2.45148,-76.5416,-64.0529,33,-3.9375,-22.015,13.61,5.74583,-2.88005,-2.21466,-5.75,-88.0816,-80.2834,7.9,23.2538,29.966,-76.1742,-75.4699,-80.0931,-80.7838,-79.8995,14.25,-123.026,15.6371,-117.257,-82.7259,-88.7483,12.4176,12.5265,13.3319,-1.925,-82.266,27.0253,27.0415,-69.6409,-69.5781,-156.864,-157.844,-76.6707,24.99,2.8,-79.1676,-70.6722,-4.15903,12.5083,30.7759,174.819,12.2605,-149.54,12.4378,170.771,10,-8.8341,-8.6668,12.935,13.0731,13.595,-64.5,-20.3043,-7.97312,21.3169,-178.41,-178.41,-170.93,-166.01,-164.88,-164.86,-11.9727,-8.006,-4.93217,-3.89483,-0.508333],5,null,null,{"interactive":true,"className":"","stroke":true,"color":"#03F","weight":5,"opacity":0.5,"fill":true,"fillColor":"#03F","fillOpacity":0.2},{"showCoverageOnHover":true,"zoomToBoundsOnClick":true,"spiderfyOnMaxZoom":true,"removeOutsideVisibleBounds":true,"spiderLegPolylineOptions":{"weight":1.5,"color":"#222","opacity":0.5},"freezeAtZoom":false},null,null,null,["430","460","540","620","670","760","CA15","200","CA18","405","BFB5","405","A1","A2","A3","A4","A5","G1","G2","G3","G4","G5","27","53","114","130","132","176","183","185","209","235","250","287","311","329","341","357","1","10","100","101","102","103","105","106","107","108","109","110","111","113","114","115","116","117","118","122","123","124","125","126","127","128","129","13","130","131","132","133","14","141","142","143","144","145","146","147","148","149","150","151","152","153","154","155","156","157","158","159","15","162","163","164","165","166","167","168","169","17","170","171","172","173","174","175","176","177","178","18","182","183","184","185","186","187","19","2","20","21","22","24","25","26","28","29","3","30","34","35","36","37","38","39","4","41","42","43","45","46","47","48","49","50","51","52","53","54","55","56","57","58","5","6","60","61","62","63","64","65","69","7","70","71","72","73","74","76","77","78","8","80","81","90","6","8","16","22","25","26","T1","T5","T6","T7","T9"],{"interactive":false,"permanent":true,"direction":"auto","opacity":1,"offset":[0,0],"textsize":"10px","textOnly":false,"className":"","sticky":true},null]},{"method":"addProviderTiles","args":["Esri.OceanBasemap",null,null,{"errorTileUrl":"","noWrap":false,"detectRetina":false}]}],"setView":[[0,0],2,[]],"limits":{"lat":[-69.38,87.9245],"lng":[-178.41,174.819]}},"evals":[],"jsHooks":[]}</script>
]

---

# Other packages

---
## Thematic maps (tmap)

* https://cran.r-project.org/web/packages/tmap/vignettes/tmap-getstarted.html

---

## Raster

* https://cran.r-project.org/web/packages/raster/vignettes/Raster.pdf

---
layout: true

# Your turn

---

* Use four shapes files
    * world
    * world_centroids
    * bathymetry 0 m 
    * bathymetry 200 m
    
* https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-bathymetry/
* Files can be read with  `sf::read_sf`

```r
bathy_0 <- read_sf("data/ne_10m_bathymetry_L_0.shp")
bathy_200 <- read_sf("data/ne_10m_bathymetry_K_200.shp")
```

]
.right-plot[

<img src="R-session-06-mapping_files/figure-html/unnamed-chunk-50-1.png" width="80%" style="display: block; margin: auto;" />
]

---

exclude = true

```r
# Very tricky must use the Windows file convention (backslash and not slash) !!!
bathy_0 <- read_sf("data/ne_10m_bathymetry_L_0.shp")
bathy_200 <- read_sf("data/ne_10m_bathymetry_K_200.shp")

theme_set(theme_bw())

ggplot() +
    geom_sf(data = world, fill="grey90", color="grey90") +
    geom_sf(data = bathy_0, fill="deepskyblue", color="deepskyblue") +
    geom_sf(data=bathy_200, fill="white", color="white")+
    coord_sf(xlim=c(-20,40), 
             ylim=c(30,70)) +
    geom_point(data=filter(bolido, 
                           bolido_pct >0), 
               aes(x=longitude, 
                   y=latitude, 
                   size=bolido_pct),
               color="red")+
    geom_text(data = world_centroids, aes(x = X, y=Y, label=name), 
              size=3) +
    xlab("Longitude") + ylab("Latitude") + labs(size = "Bolido %")
```

---
layout: false
class: middle, inverse

# Recap

.font150[
* Simple features
* Static maps
* Plotting your data
* Interactive map
]
---
background-image: url(img/course-logo.png)
background-position: right top 30px 
background-size: 45%
class: inverse

# Topics to explore on your own

* Strings and date manipulation
* Text mining
* Web mining
* Markdown: books, web sites, presentations
* Creating Packages
* Interface to Databases (MySQL)

]
---
layout: false
background-image: url(img/course-logo.png)
background-position: center bottom 30px 
background-size: 45%
class: center, inverse