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1 Introduction

This vignette introduces the weather_stations dataset, obtained from the GSODR package. These stations provide essential information for understanding long-term climate patterns, making them a valuable resource for ecotourism studies.

2 Preview of Weather Station Data

This is the glimpse of your data :

library(dplyr)
library(ecotourism)

data("weather_stations")
weather_stations |> glimpse()

Rows: 732
Columns: 7
$ ws_id     <chr> "941000-99999", "941020-99999", "941030-99999", "941050-9999…
$ stname    <chr> "KALUMBURU", "TROUGHTON ISLAND", "BROWSE ISLAND AWS", "NOONA…
$ stn_lat   <dbl> -14.300, -13.750, -14.117, -12.617, -14.717, -11.167, -11.55…
$ stn_lon   <dbl> 126.633, 126.150, 123.533, 131.050, 134.750, 132.483, 132.92…
$ address   <chr> "Drysdale River, Shire Of Wyndham-East Kimberley, Western Au…
$ stn_city  <chr> "Drysdale River", "Troughton Island Airport", "Shire Of Wynd…
$ stn_state <chr> "Western Australia", "Western Australia", "Western Australia…

3 Visualization: Map of Weather Stations

library(ggplot2)
library(ggthemes)

ggplot() +
  geom_sf(data = oz_lga) +
  geom_point(data = weather_stations, 
             aes(x = stn_lon, y = stn_lat, colour = stn_state),
             alpha = 0.6, size = 1) +
  theme_map() +
  theme(legend.position = "none")

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