ramp Building Footprint Training Dataset - Muscat, Oman
This chipped training dataset is over Muscat 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 2,891 tiles and 30,652 individual buildings. The satellite imagery resolution is 40 cm and was sourced from Maxar ODP (10500100271BF800). Dataset keywords: Urban, Peri-urban, Mountainous, Coastal, Desert.
Dataset ID | ramp_muscat_oman |
DOI | 10.34911/rdnt.ddqkh5 |
Creator | DevGlobal |
Contact | info@dev.global |
Documentation
Tools & Applications
Citation
DevGlobal, (2022). ramp Building Footprint Training Dataset - Muscat, Oman, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.ddqkh5
Python Client example
from radiant_mlhub import Dataset
ds = Dataset.fetch('ramp_muscat_oman')
for c in ds.collections:
print(c.id)
Download Dataset
Source Imagery Collections
Description | ramp Building Footprint Training Dataset - Muscat, Oman - Source Imagery |
License | CC-BY-NC-4.0 |
Collection ID | ramp_muscat_oman_source |
Download | |
Labels Collections
Description | ramp Building Footprint Training Dataset - Muscat, Oman - Labels |
License | CC-BY-NC-4.0 |
Collection ID | ramp_muscat_oman_labels |
Download | |
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