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Title: Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product

Authors:
; ; ; ;
Publication Date:
Sponsoring Org.:
USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research
OSTI Identifier:
1703303
Grant/Contract Number:  
2016YFE0202300
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Remote Sensing of Environment
Additional Journal Information:
Journal Name: Remote Sensing of Environment Journal Volume: 235 Journal Issue: C; Journal ID: ISSN 0034-4257
Publisher:
Elsevier
Country of Publication:
United States
Language:
English

Citation Formats

Shao, Zhenfeng, Cai, Jiajun, Fu, Peng, Hu, Leiqiu, and Liu, Tao. Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product. United States: N. p., 2019. Web. https://doi.org/10.1016/j.rse.2019.111425.
Shao, Zhenfeng, Cai, Jiajun, Fu, Peng, Hu, Leiqiu, & Liu, Tao. Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product. United States. https://doi.org/10.1016/j.rse.2019.111425
Shao, Zhenfeng, Cai, Jiajun, Fu, Peng, Hu, Leiqiu, and Liu, Tao. Sun . "Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product". United States. https://doi.org/10.1016/j.rse.2019.111425.
@article{osti_1703303,
title = {Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product},
author = {Shao, Zhenfeng and Cai, Jiajun and Fu, Peng and Hu, Leiqiu and Liu, Tao},
abstractNote = {},
doi = {10.1016/j.rse.2019.111425},
journal = {Remote Sensing of Environment},
number = C,
volume = 235,
place = {United States},
year = {2019},
month = {12}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1016/j.rse.2019.111425

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