SatBird: Bird Species Distribution Modeling with Remote Sensing and
  Citizen Science Data
Mélisande Teng Amna Elmustafa Benjamin Akera Yoshua Bengio Hager Radi Abdelwahed Hugo Larochelle David Rolnick
Biodiversity is declining at an unprecedented rate, impacting ecosystem
services necessary to ensure food, water, and human health and well-being.
Understanding the distribution of species and their habitats is crucial for
conservation policy planning. However, traditional methods in ecology for
species distribution models (SDMs) generally focus either on narrow sets of
species or narrow geographical areas and there remain significant knowledge
gaps about the distribution of species. A major reason for this is the limited
availability of data traditionally used, due to the prohibitive amount of
effort and expertise required for traditional field monitoring. The wide
availability of remote sensing data and the growing adoption of citizen science
tools to collect species observations data at low cost offer an opportunity for
improving biodiversity monitoring and enabling the modelling of complex
ecosystems. We introduce a novel task for mapping bird species to their
habitats by predicting species encounter rates from satellite images, and
present SatBird, a satellite dataset of locations in the USA with labels
derived from presence-absence observation data from the citizen science
database eBird, considering summer (breeding) and winter seasons. We also
provide a dataset in Kenya representing low-data regimes. We additionally
provide environmental data and species range maps for each location. We
benchmark a set of baselines on our dataset, including SOTA models for remote
sensing tasks. SatBird opens up possibilities for scalably modelling properties
of ecosystems worldwide.