| 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: | 2026-10-22 08:37:50 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)
Simplified 2021 Statistical Area Level 2 (SA2) polygon boundaries for the SA2 codes used in Tourism Research Australia exports. Representative interior-point coordinates are included for analyses that need one point per SA2.
oz_sa2oz_sa2
An sf data frame with 2,350 rows and 4 variables:
* **sa2_code_tra**: Integer SA2 identifier used by Tourism Research
Australia. This field can be joined to tourism_reason,
tourism_activity, and tourism_region.
* **lat**: Latitude of a representative point located within the SA2,
in decimal degrees.
* **lon**: Longitude of a representative point located within the SA2,
in decimal degrees.
* **geometry**: Simplified SA2 polygon or multipolygon geometry in GDA2020
(EPSG:7844).
Boundaries were obtained from the Australian Bureau of Statistics ASGS Edition 3 digital boundary files. Full-resolution polygons were matched to TRA codes by state and SA2 name. Representative points were calculated from the full-resolution geometry in Australian Albers (EPSG:3577), using a point guaranteed to lie on the SA2 surface. Polygon geometry was simplified with rmapshaper, retaining five percent of removable vertices while preserving shapes and shared boundaries.
Australian Bureau of Statistics, ASGS Edition 3 digital boundary files.
Australian Bureau of Statistics. Australian Statistical Geography Standard (ASGS), Edition 3, July 2021–June 2026.
tourism_region, tourism_reason,
tourism_activity
data(oz_sa2) head(oz_sa2)data(oz_sa2) head(oz_sa2)
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)
Estimated domestic overnight trips to Australian SA2 areas by month and stopover activity. The data contain only observations with non-zero trip estimates and non-zero survey sample sizes.
tourism_activitytourism_activity
A tibble with 320,188 rows and 6 variables:
* **year**: Calendar year, from 2014 to 2024.
* **month**: Ordered factor giving the month returned from the trip.
* **sa2_code_tra**: Integer SA2 code used by Tourism Research Australia.
This can be joined to tourism_region.
* **stop_activity**: Integer activity code that can be joined to
tourism_activity_name.
* **trips**: Estimated number of overnight trips, in thousands.
* **n_sample**: Number of survey responses supporting the estimate.
Records for which either trips or n_sample equals zero are
excluded. Estimates with small sample sizes should be interpreted with
appropriate caution.
Tourism Research Australia: https://www.tra.gov.au
tourism_activity_name,
tourism_reason, tourism_region
data(tourism_activity) head(tourism_activity)data(tourism_activity) head(tourism_activity)
A lookup table matching the stopover activity codes in
tourism_activity to descriptive names.
tourism_activity_nametourism_activity_name
A tibble with 8 rows and 2 variables: * **stop_activity**: Integer stopover activity code. * **name**: Descriptive name of the stopover activity.
Tourism Research Australia: https://www.tra.gov.au
data(tourism_activity_name) tourism_activity_namedata(tourism_activity_name) tourism_activity_name
Estimated domestic overnight trips to Australian SA2 areas by month and stopover reason. The data contain only observations with non-zero trip estimates and non-zero survey sample sizes.
tourism_reasontourism_reason
A tibble with 196,044 rows and 6 variables:
* **year**: Calendar year, from 2014 to 2024.
* **month**: Ordered factor giving the month returned from the trip.
* **sa2_code_tra**: Integer SA2 code used by Tourism Research Australia.
This can be joined to tourism_region.
* **stop_reason**: Integer reason code that can be joined to
tourism_reason_name.
* **trips**: Estimated number of overnight trips, in thousands.
* **n_sample**: Number of survey responses supporting the estimate.
Records for which either trips or n_sample equals zero are
excluded. Estimates with small sample sizes should be interpreted with
appropriate caution.
Tourism Research Australia: https://www.tra.gov.au
tourism_reason_name,
tourism_activity, tourism_region
data(tourism_reason) head(tourism_reason)data(tourism_reason) head(tourism_reason)
A lookup table matching the stopover reason codes in
tourism_reason to descriptive names.
tourism_reason_nametourism_reason_name
A tibble with 7 rows and 2 variables: * **stop_reason**: Integer stopover reason code. * **name**: Descriptive name of the stopover reason.
Tourism Research Australia: https://www.tra.gov.au
data(tourism_reason_name) tourism_reason_namedata(tourism_reason_name) tourism_reason_name
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 tibble with 2,353 rows and 7 variables: * **state**: Australian state or territory abbreviation. * **region**: Name of the tourism region. Tourism regions are defined by Tourism Research Australia and generally formed through the aggregation of Statistical Area Level 2 (SA2) geographies. * **sa2**: Name of the SA2 area. * **lon**: Longitude of the SA2 representative point (WGS84). * **lat**: Latitude of the SA2 representative point (WGS84). * **ws_id**: Identifier of the nearest Bureau of Meteorology weather station to the SA2 area. * **sa2_code_tra**: Character SA2 code used by Tourism Research Australia. Join this field to the identically named field in the detailed tourism datasets after harmonising its type.
Coordinates for each SA2 are intended to represent a central location within the area (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.
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)