Enhanced biomass prediction by assimilating satellite data into a crop growth model

Environmental Modelling and Software

Volumn 62, Issue , 2014, Pages 437-453

  Machwitz, Miriam ^a   Giustarini, Laura ^a   Bossung, Christian ^b   Frantz, David ^b   Schlerf, Martin ^a   Lilienthal, Holger ^c   Wandera, Loise ^a   Matgen, Patrick ^a   Hoffmann, Lucien ^a   Udelhoven, Thomas ^a,b  

^a LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY   (Luxembourg)

^b UNIVERSITY OF TRIER   (Germany)

^c INSTITUTE FOR EPIDEMIOLOGY AND PATHOGEN DIAGNOSTICS   (Germany)

Author keywords

APSIM; Crop grow modelling; Data assimilation; Maize; Particle filter; RapidEye; Remote sensing

Indexed keywords

BIOMASS; COMPUTER SIMULATION; CROPS; ERRORS; MONTE CARLO METHODS; RADIATIVE TRANSFER; REMOTE SENSING; UNCERTAINTY ANALYSIS;

APSIM; DATA ASSIMILATION; MAIZE; PARTICLE FILTER; RAPIDEYE;

ECOLOGY;

AGRICULTURAL MODELING; BIOMASS; DATA ASSIMILATION; ERROR ANALYSIS; GROWTH MODELING; MAIZE; PREDICTION; RADIATIVE TRANSFER; SATELLITE DATA; SPATIAL VARIATION;

ZEA MAYS;

EID: 84912066760     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2014.08.010     Document Type: Article

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