Published July 20, 2023
| Version v1
Dataset
Open
Preferential information extraction from space-based passive microwave measurements enables accurate characterization of snow depth variability at continental scales
Description
This is a repository contains
1)training data (x_data, y_data, snow_max)
2) Developed Deep Learning model (snow_model.py)
3) Training weights (*.hdf files)
for publication " Preferential information extraction from space-based passive microwave measurements enables accurate characterization of snow depth variability at continental scales"
Files
Files
(25.7 MB)
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md5:e029437b0fe34d2a932bbeaa58ff3dc3
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206 Bytes | Download |
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md5:b15272cca69462dfbb5fa23ca5ebe80b
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7.9 kB | Download |
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md5:bbbb9bf0769af1defe67a70945460430
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608.6 kB | Download |
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md5:2c01a519395028d2b003baaf3f523cae
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608.8 kB | Download |
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md5:21848ee2d0758de0ada848ba2968147e
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608.9 kB | Download |
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md5:fefe937c6f67ccdaa9d770a10b132c87
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608.9 kB | Download |
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md5:a712a5cd4ad7319cbfed64dab5c27b6b
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608.9 kB | Download |
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md5:e69da6c232072f2c6ce6e12673e949d9
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22.6 MB | Download |