| Title: | Collection of Data on Wildlife Sightings, Tourism Counts, and Weather from Australia |
|---|---|
| Description: | This is a collection of data files for exploring sightings of wild things, relative to weather and tourism patterns in Australia. |
| Authors: | Dianne Cook [aut] (ORCID: <https://orcid.org/0000-0002-3813-7155>), Lyn Cook [aut] (ORCID: <https://orcid.org/0000-0002-3172-4920>), Javad Vahdat Atashgah [aut, cre] (ORCID: <https://orcid.org/0009-0004-5845-2584>) |
| Maintainer: | Javad Vahdat Atashgah <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2026-05-21 08:49:10 UTC |
| Source: | https://github.com/vahdatjavad/ecotourism |
This dataset contains cleaned and enriched occurrence records for glowworms (*Arachnocampa tasmaniensis*) in Australia from 2014 to 2024. It includes spatial, temporal, taxonomic, and weather station metadata.
glowwormsglowworms
A tibble with 124 rows and 14 variables:
Latitude of the observation (decimal degrees)
Longitude of the observation (decimal degrees)
Observation date (YYYY-MM-DD)
Observation time (HH:MM:SS, character)
Observation year
Month of the observation
Day of the month
Hour of the day (0–23)
Day of the week (ordered factor)
Day of the year (1–366)
Scientific name of the observed species
Type of observation (e.g., HUMAN_OBSERVATION)
Australian state where the observation occurred
ID of the nearest weather station (e.g., "949610-99999")
Data was sourced via the 'galah' package from the Atlas of Living Australia, filtered and cleaned, then enriched by linking each record to the nearest weather station using geospatial methods.
Atlas of Living Australia via galah
data(glowworms) head(glowworms)data(glowworms) head(glowworms)
This dataset contains cleaned and processed occurrence records for the Gouldian Finch (*Chloebia gouldiae*) in Australia between 2014 and 2024. It includes spatial coordinates, temporal details, species information, and the ID of the nearest weather station for each observation.
gouldian_finchgouldian_finch
A tibble with 3,921 rows and 14 variables:
Latitude of the observation (decimal degrees)
Longitude of the observation (decimal degrees)
Date of the observation (YYYY-MM-DD)
Time of the observation (HH:MM:SS)
Year of the observation
Month (1–12)
Day of the month
Hour extracted from the time (0–23)
Day of the week (as ordered factor)
Day of the year (1–366)
Scientific name of the species
Type of observation (e.g., HUMAN_OBSERVATION)
Australian state where the observation was recorded
Nearest weather station ID (e.g., "948280-99999")
The data was retrieved from the Atlas of Living Australia using the galah package, then standardized, cleaned, and matched to the three closest weather stations using geospatial tools.
Atlas of Living Australia via galah
data(gouldian_finch) head(gouldian_finch)data(gouldian_finch) head(gouldian_finch)
This dataset contains occurrence records for the reef manta ray (*Mobula alfredi*) observed in Australian waters from 2014 to 2024. The data includes spatial and temporal metadata, species identifiers, and linked weather station IDs.
manta_raysmanta_rays
A tibble with 1,088 rows and 14 variables:
Latitude of the observation (decimal degrees)
Longitude of the observation (decimal degrees)
Date of the observation (YYYY-MM-DD)
Time of the observation (HH:MM:SS)
Year of the observation
Month (1–12)
Day of the month
Hour extracted from the time (0–23)
Day of the week (as ordered factor)
Day of the year (1–366)
Scientific name — all observations are Mobula alfredi
Type of observation (e.g., MACHINE_OBSERVATION)
Australian state where the observation occurred (may be missing)
Nearest weather station ID (e.g., "947800-99999")
Records were accessed using the galah package and filtered specifically for *Mobula alfredi*. Data has been cleaned and enriched with spatial proximity to weather stations for climate-related analysis.
Atlas of Living Australia via galah
data(manta_rays) head(manta_rays)data(manta_rays) head(manta_rays)
This dataset contains over 300,000 occurrence records of orchid species (*Orchidaceae*) in Australia from 2014 to 2024. The data includes spatial, temporal, and taxonomic details, as well as associated weather station metadata for ecological analysis.
orchidsorchids
A tibble with 302,123 rows and 14 variables:
Latitude of the observation (decimal degrees)
Longitude of the observation (decimal degrees)
Date of the observation (YYYY-MM-DD)
Time of the observation (HH:MM:SS)
Year of the observation
Month (1–12)
Day of the month
Hour extracted from the time (0–23)
Day of the week (as ordered factor)
Day of the year (1–366)
Scientific name of the observed orchid species
Type of observation (e.g., HUMAN_OBSERVATION, PRESERVED_SPECIMEN)
Australian state where the observation occurred (may be missing)
Nearest weather station ID linked to the observation
The data was collected using the galah package from the Atlas of Living Australia, cleaned, and linked to nearby weather stations for ecological and climatic studies. The records span multiple orchid genera and include a range of observation types.
Atlas of Living Australia via galah
glowworms, gouldian_finch, weather
data(orchids) head(orchids)data(orchids) head(orchids)
LGA polygons for Australia
oz_lgaoz_lga
A spatial polygon object
head(oz_lga)head(oz_lga)
A lookup table identifying the top 3 most frequently linked weather stations for each focal organism in the ecotourism package. These stations were selected based on the number of linked observations across a 10-year period (2014–2024).
top_stationstop_stations
A tibble with 12 rows and 2 variables:
Name of the organism (e.g., "glowworms", "orchids")
Weather station ID (e.g., "948720-99999")
This table was created by counting the frequency of 'ws_id' assignments within each organism dataset and selecting the top 3 stations per organism. These top stations are used for downloading daily weather data via the GSODR package.
data(top_stations) head(top_stations)data(top_stations) head(top_stations)
A dataset containing quarterly estimates of overnight tourism trips in Australia, broken down by trip purpose and tourism region.
tourism_quarterlytourism_quarterly
A data frame with 'r nrow(tourism_quarterly)' rows and 4 variables:
* **year**: The year of the tourism data
* **quarter**: Quarter number like 1, 2, 3, 4
* **purpose**: Purpose of visit category:
- '"Holiday"'
- '"Business"'
* **trips**: Number of overnight trips (in thousands).
* **region_id**: Unique integer identifier linking to the
tourism_region dataset.
* **ws_id**: Identifier of the nearest Bureau of Meteorology weather station
to the tourism region.
Tourism regions are formed through the aggregation of Statistical
Local Areas (SLAs) or similar ABS-defined geographies, as determined
by state and territory tourism authorities. This dataset is designed
for analysis of seasonal tourism patterns and can be joined to
tourism_region for spatial analysis.
Tourism Research Australia: https://www.tra.gov.au
data(tourism_quarterly) head(tourism_quarterly)data(tourism_quarterly) head(tourism_quarterly)
A dataset containing the locations of Australian tourism regions, their geographic coordinates, and the nearest Bureau of Meteorology weather station. Each region is assigned a unique identifier for linking to other tourism datasets.
tourism_regiontourism_region
A data frame with 'r nrow(tourism_region)' rows and 5 variables: * **region**: Name of the tourism region. Tourism regions are defined by Tourism Research Australia and generally formed through the aggregation of Statistical Local Areas (SLAs) or other ABS-defined geographies. * **lon**: Longitude of the tourism region representative point (WGS84). * **lat**: Latitude of the tourism region representative point (WGS84). * **region_id**: Unique integer identifier for the tourism region. Useful for joining with other tourism-related datasets. * **ws_id**: Identifier of the nearest Bureau of Meteorology weather station to the tourism region.
Coordinates for each tourism region are intended to represent a central location within the region (e.g., polygon centroid). The nearest weather station is determined using great-circle distance calculations based on the Bureau of Meteorology's official station list.
Tourism Research Australia: https://www.tra.gov.au Australian Bureau of Meteorology: http://www.bom.gov.au
data(tourism_region) head(tourism_region)data(tourism_region) head(tourism_region)
This dataset contains daily weather observations for the top weather stations associated with focal species in the ecotourism package. Data spans from 2014 to 2024 and includes temperature, humidity, precipitation, and wind measures.
weatherweather
A tibble with 35,527 rows and 18 variables:
Weather station ID (e.g., "948720-99999")
Latitude of the weather station
Longitude of the weather station
Observation date (YYYY-MM-DD)
Year of observation
Month of observation (1–12)
Day of the month
Day of the week (as ordered factor)
Day of the year (1–366)
Average temperature (°C)
Minimum temperature (°C)
Maximum temperature (°C)
Dew point temperature (°C)
Relative humidity (%)
Precipitation (mm)
Binary flag indicating whether PRCP > 5 mm (1 = rainy day)
Average wind speed (m/s)
Maximum sustained wind speed (m/s)
The weather data was retrieved from the Global Surface Summary of the Day (GSOD) dataset via the GSODR package for the top 3 weather stations per organism in the ecotourism project. This data supports climate-biodiversity interaction analyses.
GSOD via GSODR
top_stations, glowworms, gouldian_finch, weather_stations
data(weather) head(weather)data(weather) head(weather)
This dataset contains metadata for 732 weather stations across Australia, including coordinates, station names, and geocoded location details.
weather_stationsweather_stations
A tibble with 732 rows and 7 variables:
Weather station ID (e.g., "941000-99999")
Station name (e.g., "KALUMBURU")
Latitude of the station (decimal degrees)
Longitude of the station (decimal degrees)
Full geocoded address (from reverse geocoding)
Parsed city or locality name
Australian state or territory
This data was derived from the GSOD inventory using the GSODR package, filtered for Australian stations, and geocoded using OpenStreetMap APIs. It is used to match ecological observations with relevant local weather conditions.
GSOD inventory via GSODR; geocoded with OpenStreetMap
weather, top_stations, gouldian_finch
data(weather_stations) head(weather_stations)data(weather_stations) head(weather_stations)