This chipped training dataset is over Lubumbashi 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 2 dataset, meaning it has NOT been thoroughly reviewed and improved. This dataset was produced for the ramp project and contains 8,498 tiles and 148,459 individual buildings. The satellite imagery resolution is 30 cm and was sourced from Maxar ODP (1040010058041300). Dataset keywords: Urban, Peri-urban, Rural
Dataset ID | ramp_lubumbashi_drc |
DOI | 10.34911/rdnt.wmflve |
Creator | DevGlobal |
Contact | info@dev.global |
DevGlobal, (2022). ramp Building Footprint Training Dataset - Lubumbashi, Democratic Republic of the Congo, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.wmflve
from radiant_mlhub import Dataset ds = Dataset.fetch('ramp_lubumbashi_drc') for c in ds.collections: print(c.id)
Description | ramp Building Footprint Training Dataset - Lubumbashi, Democratic Republic of the Congo - Source Imagery |
License | CC-BY-NC-4.0 |
Collection ID | ramp_lubumbashi_drc_source |
Download | |
Description | ramp Building Footprint Training Dataset - Lubumbashi, Democratic Republic of the Congo - Labels |
License | CC-BY-NC-4.0 |
Collection ID | ramp_lubumbashi_drc_labels |
Download | |