SpaceNet

SpaceNet is a corpus of commercial satellite imagery and labeled training data being made available at no cost to the public to foster innovation in the development of computer vision algorithms to automatically extract information from remote sensing data. The current SpaceNet corpus includes thousands of square kilometers of high resolution imagery collected from DigitalGlobe’s commercial satellites which includes 8-band multispectral data. This dataset is being made public to advance the development of algorithms to automatically extract geometric features such as roads, building footprints, and points of interest using satellite imagery. The currently available Areas of Interest (AOI) are Rio De Janeiro, Paris, Las Vegas, Shanghai and Khartoum. Please see the data catalog below for more information. The satellite imagery, along with training data, is provided via a collaboration between DigitalGlobe, CosmiQ Works, and NVIDIA.

Dataset Attributes

TasksSegmentation

CategoriesSatellite, Geographical, Maps, Roads

SensorSatellite Imagery

Class Labels

Road