Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation

Ecological Modelling

Volumn 270, Issue , 2013, Pages 30-42

  Zhao, Yanxia ^a   Chen, Sining ^a,b,c   Shen, Shuanghe ^c  

^a STATE KEY LABORATORY OF SEVERE WEATHER   (China)

^b Tianjin Climate Center   (China)

^c NANJING UNIVERSITY OF INFORMATION SCIENCE AND TECHNOLOGY   (China)

Author keywords

Data assimilation; Ensemble Kalman Filter (EnKF); PyWOFOST; Remote sensing; Yield estimation

Indexed keywords

DATA ASSIMILATION; DETERMINATION COEFFICIENTS; ENSEMBLE KALMAN FILTER; FIELD OBSERVATIONS; PYWOFOST; REMOTE SENSING DATA; REMOTE SENSING INFORMATION; YIELD ESTIMATION;

CROPS; DATA PROCESSING; ERRORS; ESTIMATION; KALMAN FILTERS; RADIOMETERS; REMOTE SENSING; UNCERTAINTY ANALYSIS;

COMPUTER SIMULATION;

AGRICULTURAL MODELING; CROP YIELD; DATA ASSIMILATION; ENSEMBLE FORECASTING; GROWTH MODELING; KALMAN FILTER; LEAF AREA INDEX; MAIZE; MODIS; REMOTE SENSING;

CHINA;

EID: 84885237989     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2013.08.016     Document Type: Article

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