Soil moisture retrieval using neural networks: Application to SMOS

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 11, 2015, Pages 5991-6007

  Rodríguez Fernández, Nemesio J ^a   Aires, Filipe ^b   Richaume, Philippe ^a   Kerr, Yann H ^a   Prigent, Catherine ^c   Kolassa, Jana ^b   Cabot, François ^a   Jiménez, Carlos ^c   Mahmoodi, Ali ^a   Drusch, Matthias ^d  

^a CNES   (France)

^b ESTELLUS ^*  (France)

^c OBSERVATOIRE DE PARIS   (France)

^d EUROPEAN SPACE AGENCY   (Netherlands)

Author keywords

Advanced Scatterometer (ASCAT); Artificial neural networks (NNs); European Centre for Medium Range Weather Forecasts (ECMWF); Moderate Resolution Imaging Spectroradiometer (MODIS); soil moisture (SM); Soil Moisture and Ocean Salinity (SMOS)

Indexed keywords

BACKSCATTERING; BALLOONS; FORECASTING; IMAGE RECONSTRUCTION; INPUT OUTPUT PROGRAMS; METEOROLOGICAL INSTRUMENTS; MOISTURE; NEURAL NETWORKS; RADIOMETERS; SATELLITE IMAGERY; SOIL MOISTURE; SOILS; SPECTROMETERS;

BACKSCATTERING COEFFICIENTS; EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; NORMALIZED DIFFERENCE VEGETATION INDEX; SCATTEROMETERS; SOIL MOISTURE AND OCEAN SALINITY (SMOS); STATISTICAL RELATIONSHIP; TEMPORAL AND SPATIAL VARIABILITY;

WEATHER FORECASTING;

ARTIFICIAL NEURAL NETWORK; ASCAT; BACKSCATTER; DATA ASSIMILATION; DATA SET; MODIS; NDVI; SATELLITE DATA; SMOS; SOIL MOISTURE; WEATHER FORECASTING;

EID: 85027941806     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2430845     Document Type: Article

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