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
< Leer menos
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth
Idioma
en
Article de revue
Este ítem está publicado en
Remote Sensing. 2017, vol. 9, n° 8, p. 1 p.
MDPI
Resumen en inglés
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)< Leer menos
Palabras clave
télédétection
indice de végétation
analyse de données
radiomètre
Palabras clave en inglés
data analysis
radiometer
remote sensing
Orígen
Importado de HalCentros de investigación