Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)
SHI, Jiancheng
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
ZHAO, Tianjie
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
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State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
SHI, Jiancheng
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
ZHAO, Tianjie
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
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State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Language
en
Article de revue
This item was published in
Remote Sensing. 2017, vol. 9, n° 8, p. 1 p.
MDPI
English Abstract
Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)
Rebuilding long time series global soil moisture products using the neural network adopting the microwave vegetation index (Correction)Read less <
Keywords
télédétection
indice de végétation
analyse de données
radiomètre
English Keywords
data analysis
radiometer
remote sensing
Origin
Hal imported