This chipped training dataset is over Mesopotamia and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 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 3,013 tiles and 33,139 individual buildings. The satellite imagery resolution is 40 cm and was sourced from Maxar ODP (10500100236CC900). Dataset keywords: Coastal, Urban, Peri-urban.
DevGlobal, (2022). ramp Building Footprint Training Dataset - Mesopotamia, St. Vincent, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.yhk0md
from radiant_mlhub import Dataset ds = Dataset.fetch('ramp_mesopotamia_st_vincent') for c in ds.collections: print(c.id)
ramp Building Footprint Training Dataset - Mesopotamia, St. Vincent - Source Imagery
ramp Building Footprint Training Dataset - Mesopotamia, St. Vincent - Labels