Radiant MLHub

ramp Building Footprint Training Dataset - Wa, Ghana

This chipped training dataset is over Wa 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 7,615 tiles and 68,072 individual buildings. The satellite imagery resolution is 32 cm and was sourced from Maxar ODP (1040010056B6FA00). Dataset keywords: Urban, Peri-urban

Dataset ID

ramp_wa_ghana

DOI

10.34911/rdnt.6l9q5d

Creator

DevGlobal

Contact

info@dev.global

Documentation

Tools & Applications

Citation

DevGlobal, (2022). ramp Building Footprint Training Dataset - Wa, Ghana, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.6l9q5d

Python Client example

from radiant_mlhub import Dataset

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

Python Client quick-start guide

Download Dataset

Source Imagery Collections

Description

ramp Building Footprint Training Dataset - Wa, Ghana - Source Imagery

License

CC-BY-NC-4.0

Collection ID

ramp_wa_ghana_source

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Labels Collections

Description

ramp Building Footprint Training Dataset - Wa, Ghana - Labels

License

CC-BY-NC-4.0

Collection ID

ramp_wa_ghana_labels

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