#SPACENET GYM SERIES#

See here for more details about the dataset.Īs noted in previous blogs the task of identifying buildings and tracking unique building identifiers (i.e. This is the first SpaceNet challenge to explicitly include the time dimension, and accordingly used a new medium resolution satellite imagery dataset from Planet that encompasses over 100 locations around the globe and 24 consecutive monthly observations that cover multiple seasons and significant construction in most locations. In the following sections we detail the winners of the challenge, and provide a prelude of some of the insights gleaned from this challenge (further analysis will have to wait for subsequent blogs). Our public baseline model achieved a score of 17 (out of 100) on the final test set, yet the winning submission more than doubled this score, with a score of 41. We are happy to report that this challenging task was met with a high degree of ingenuity by the top competitors. The Multi-temporal Urban development Challenge staked out an ambitious goal: identify and track building footprint change over a deep temporal stack.

#SPACENET GYM SERIES#

The 7th iteration of the SpaceNet Challenge Series is officially in the books, and our top 5 winners have been determined. SpaceNet is run in collaboration by co-founder and managing partner CosmiQ Works, co-founder and co-chair Maxar Technologies, and our partners including Amazon Web Services (AWS), Capella Space, Topcoder, IEEE GRSS, the National Geospatial-Intelligence Agency and Planet. Preface: SpaceNet LLC is a nonprofit organization dedicated to accelerating open source, artificial intelligence applied research for geospatial applications, specifically foundational mapping (i.e., building footprint & road network detection). The SpaceNet 7 Multi-Temporal Urban Development Challenge: Announcing the Winners

Spacenet gym