Predict species for a given location and time — predict_species_at_location_and

Uses the BirdNET Species Range Model to estimate the presence of bird species at a specified location and time of year.

Usage

predict_species_at_location_and_time(
  model,
  latitude,
  longitude,
  week = NULL,
  min_confidence = 0.03
)

# S3 method for class 'birdnet_model_meta'
predict_species_at_location_and_time(
  model,
  latitude,
  longitude,
  week = NULL,
  min_confidence = 0.03
)

Arguments

model: birdnet_model_meta. An instance of the BirdNET model returned by birdnet_model_meta().
latitude: numeric. The latitude of the location for species prediction. Must be in the interval [-90.0, 90.0].
longitude: numeric. The longitude of the location for species prediction. Must be in the interval [-180.0, 180.0].
week: integer. The week of the year for which to predict species. Must be in the interval [1, 48] if specified. If NULL, predictions are not limited to a specific week.
min_confidence: numeric. Minimum confidence threshold for predictions to be considered valid. Must be in the interval [0, 1.0).

Value

A data frame with columns: label, confidence. Each row represents a predicted species, with the confidence indicating the likelihood of the species being present at the specified location and time.

Details

The BirdNET Species Range Model leverages eBird checklist frequency data to estimate the probability of bird species occurrences based on latitude, longitude, and time of year. It integrates actual observations and expert-curated data, making it adaptable to regions with varying levels of data availability. The model employs circular embeddings and a classifier to predict species presence and migration patterns, achieving higher accuracy in data-rich regions and lower accuracy in underrepresented areas like parts of Africa and Asia. For more details, you can view the full discussion here: https://github.com/kahst/BirdNET-Analyzer/discussions/234

Examples

if (FALSE) { # interactive()
# Predict species in Chemnitz, Germany, that are present all year round
model <- birdnet_model_meta(language = "de")
predict_species_at_location_and_time(model, latitude = 50.8334, longitude = 12.9231)
}