NASA Flood Extent Detection
This dataset contains synthetic aperture radar (SAR) raster imagery for various flood events acquired from the European Space Agencys Sentinel-1A and Sentinel-1B missions, providing C-Band dual-polarized imagery that spans geographical areas of interest in the United States and Bangladesh. The main emphasis was on the labeling of open water areas where specular reflection of the radar signal off of the relatively still, flat open water surface results in reduced backscatter, low amplitude, and an overall darkened appearance within the image. The labels for the water surface reflectance are also provided in GeoTiff rasterized file format in scenes aligned with the SAR source raster imagery.
Dataset ID | nasa_floods_v1 |
DOI | 10.34911/rdnt.ebk43x |
Creator | University of Alabama in Huntsville |
Contact | ig0004@uah.edu |
Documentation
Citation
Gahlot, S., Gurung, I., Molthan, A., Maskey, M., & Ramasubramanian, M. (2021) "Flood Extent Data for Machine Learning", Version 1.0, Radiant MLHub. [Date Accessed] https://doi.org/10.34911/rdnt.ebk43x
Python Client example
from radiant_mlhub import Dataset
ds = Dataset.fetch('nasa_floods_v1')
for c in ds.collections:
print(c.id)
Download Dataset
Source Imagery Collections
Description | NASA Flood Extent Source Imagery |
License | CC-BY-4.0 |
Collection ID | nasa_floods_v1_source |
Download | |
Labels Collections
Description | NASA Flood Extent Labels |
License | CC-BY-4.0 |
Collection ID | nasa_floods_v1_labels |
Download | |
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