Skip to content

Latest commit

 

History

History
150 lines (117 loc) · 4.24 KB

README.md

File metadata and controls

150 lines (117 loc) · 4.24 KB
Raw

Cell Towers Brazil

Rafael Lopes (@rafalpx)

Cell Towers

This is a repository to codes and plots of cell towers in Brazilian territories. From the opencellid.org you can download the data for the exact location of each cell tower by type. In this repository there is a copy of the data set the file ‘724.csv.gz’. Filtering this ‘.csv’ on the extent of the desired administrative cut you can plot easily the cell towers location on a map.

The Following sections gives examples on how to plot filter and plot on any Brazilian extent using the {r} package geobr.

Necessary Libraries

library(dplyr)
## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(readr)
library(ggplot2)
library(ggtext)
library(sf)
## Linking to GEOS 3.9.1, GDAL 3.4.0, PROJ 8.2.0; sf_use_s2() is TRUE

library(rnaturalearth)
library(rnaturalearthdata)
library(geobr)

#Functions to take the IBGE codes of State Capitals
source("Functions/functions.R")

Filtering on Cell Towers dataset

On the dataset filtering the extent of Brazil, before we set up the CRS of the celltowers dataframe:

## Setting the CRS for the celltowers dataset
celltowers <- read_csv("Data/724.csv.gz")|> 
  sf::st_as_sf(coords = c("lon", "lat"), crs = 4326)
## Rows: 1833130 Columns: 14

## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): radio
## dbl (13): mcc, net, area, cell, unit, lon, lat, range, samples, changeable, ...

## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## Getting the extent of Brasil
brasil <- ne_countries(scale = 'medium', type = 'map_units', returnclass = 'sf') |>
  filter(name == 'Brazil')

## Filtering towers by type
### 3G
UMTS <- celltowers |> 
  filter(radio == "UMTS") |>
  st_intersection(brasil)
## Warning: attribute variables are assumed to be spatially constant throughout all
## geometries

### 4G
LTE <- celltowers |> 
  filter(radio == "LTE") |>
  st_intersection(brasil)
## Warning: attribute variables are assumed to be spatially constant throughout all
## geometries

Plots

## A Quick plot of the extent
ggplot() + 
  geom_sf(data = brasil)

## A plot of celltowers on the map
ggplot() + 
  geom_sf(data = brasil, fill = "black", color = "white", size = 0.3) + 
  geom_sf(data = UMTS, shape = ".", color = "#4d88ff", alpha = 0.3) +
  geom_sf(data = LTE, shape = ".", color = "#cc0000", alpha = 0.5)

## Saving the plot
# ggsave("my_plot_br.png", height = 7, width = 7)

Plot with HTML

x <- ggplot() + 
  geom_sf(data = brasil, fill = "black", color = "white", size = 0.3) + 
  geom_sf(data = UMTS, shape = ".", color = "#4d88ff", alpha = 0.3) +
  geom_sf(data = LTE, shape = ".", color = "#cc0000", alpha = 0.5) +
  theme_void() +
  labs(
    title = "<span style='color: white; text-align: center;'>Cell tower distribution with <br> <span style='color: #cc0000'>4G</span> (LTE) and <span style='color: #4d88ff'>3G</span> (UMTS)</span>",
    caption = "<span style='color: white;'> Made by Rafael Lopes <b>&middot;</b> <br>Original plot by Dominic Royé and with codes by Etienne Bacher <b>&middot;</b> Data from opencellid.org </span></br>"
  ) +
  theme(
    plot.background = element_rect(fill = "black"),
    panel.background = element_rect(fill = "black"),
    plot.title = element_markdown(margin = margin(t = 40, b = -60, l = 10), size = 20),
    plot.caption = element_markdown(hjust = 0, margin = margin(l = 10, b = 20, t = -30)),
    text = element_text(family = "Roboto Condensed")
  )
x

ggsave("my_plot_br.png", plot = x, height = 7, width = 7)