This chipped training dataset is over Shanghai and includes 30cm high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 or smaller pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 3,574 tiles and 7,118 buildings. The original dataset was sourced from the SpaceNet 2 Dataset before the imagery was tiled down from 650x650 pixel chips and labels were revised to be consistent with the ramp datasets notion of rooftop as the building footprint. Dataset keywords: Urban, Dense.
DevGlobal, (2022). ramp Building Footprint Training Dataset - Shanghai, China, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.grvh9e
from radiant_mlhub import Dataset ds = Dataset.fetch('ramp_shanghai_china') for c in ds.collections: print(c.id)
ramp Building Footprint Training Dataset - Shanghai, China - Source Imagery
ramp Building Footprint Training Dataset - Shanghai, China - Labels