Radiant MLHub

ramp Building Footprint Training Dataset - Lubumbashi, Democratic Republic of the Congo

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

Documentation

Tools & Applications

Citation

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

Python Client example

from radiant_mlhub import Dataset

ds = Dataset.fetch('ramp_lubumbashi_drc')
for c in ds.collections:
    print(c.id)

Python Client quick-start guide

Download Dataset

Source Imagery Collections

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

Labels Collections

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

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