  We introduce the French Land cover from Aerospace ImageRy (FLAIR), an
extensive dataset from the French National Institute of Geographical and Forest
Information (IGN) that provides a unique and rich resource for large-scale
geospatial analysis. FLAIR contains high-resolution aerial imagery with a
ground sample distance of 20 cm and over 20 billion individually labeled pixels
for precise land-cover classification. The dataset also integrates temporal and
spectral data from optical satellite time series. FLAIR thus combines data with
varying spatial, spectral, and temporal resolutions across over 817 km2 of
acquisitions representing the full landscape diversity of France. This
diversity makes FLAIR a valuable resource for the development and evaluation of
novel methods for large-scale land-cover semantic segmentation and raises
significant challenges in terms of computer vision, data fusion, and geospatial
analysis. We also provide powerful uni- and multi-sensor baseline models that
can be employed to assess algorithm's performance and for downstream
applications. Through its extent and the quality of its annotation, FLAIR aims
to spur improvements in monitoring and understanding key anthropogenic
development indicators such as urban growth, deforestation, and soil
artificialization. Dataset and codes can be accessed at
https://ignf.github.io/FLAIR/
