ramp Building Footprint Training Dataset - Shanghai, China

This chipped training dataset is over Shanghai and includes 30cm high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 or smaller 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 3,574 tiles and 7,118 buildings. The original dataset was sourced from the SpaceNet 2 Dataset before the imagery was tiled down from 650x650 pixel chips and labels were revised to be consistent with the ramp datasets notion of rooftop as the building footprint. Dataset keywords: Urban, Dense.

Dataset ID	ramp_shanghai_china
DOI	10.34911/rdnt.grvh9e
Creator	DevGlobal
Contact	info@dev.global

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Tools & Applications

Chippy Checker Editor

Citation

DevGlobal, (2022). ramp Building Footprint Training Dataset - Shanghai, China, Version 1.0, [Date Accessed]. Radiant MLHub. https://doi.org/10.34911/rdnt.grvh9e

Python Client example

from radiant_mlhub import Dataset

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

Python Client quick-start guide

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Source Imagery Collections

Description	ramp Building Footprint Training Dataset - Shanghai, China - Source Imagery
License	CC-BY-SA-4.0
Collection ID	ramp_shanghai_china_source
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