Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 134, Issue , 2017, Pages 43-58

  Maimaitijiang, Maitiniyazi ^a,b   Ghulam, Abduwasit ^a,b   Sidike, Paheding ^a,b   Hartling, Sean ^a,b   Maimaitiyiming, Matthew ^a,b   Peterson, Kyle ^a,b   Shavers, Ethan ^a,b   Fishman, Jack ^b   Peterson, Jim ^c   Kadam, Suhas ^e   Burken, Joel ^d   Fritschi, Felix ^e  

^a SAINT LOUIS UNIVERSITY   (United States)

^b Saint Louis University   (United States)

^c SOUTHEAST MISSOURI STATE UNIVERSITY   (United States)

^d Architectural and Environmental Engineering   (United States)

^e UNIVERSITY OF MISSOURI   (United States)

Author keywords

Data Fusion; Extreme Learning Machine (ELM); Extreme Learning Machine based Regression (ELR); Phenotyping; Remote sensing; Unmanned Aerial System (UAS)

Indexed keywords

AGRICULTURE; AMINO ACIDS; BIOPHYSICS; CHLOROPHYLL; COST ESTIMATING; COSTS; CROPS; DATA FUSION; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; NITROGEN; NITROGEN FIXATION; REGRESSION ANALYSIS; REMOTE SENSING; UNMANNED AERIAL VEHICLES (UAV); VEGETATION;

EXTREME LEARNING MACHINE; HIGH-THROUGHPUT PHENOTYPING; MULTISENSOR DATA FUSION; NITROGEN CONCENTRATIONS; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); PHENOTYPING; SUPPORT VECTOR REGRESSION (SVR); UNMANNED AERIAL SYSTEMS;

SENSOR DATA FUSION;

AGRICULTURAL MODELING; BIOCHEMISTRY; BIOMASS; BIOPHYSICS; DATA ASSIMILATION; LEAF AREA INDEX; MACHINE LEARNING; PHENOTYPE; REGRESSION ANALYSIS; REMOTE SENSING; SATELLITE IMAGERY; SENSOR; SOYBEAN; SPATIAL RESOLUTION; STATISTICAL ANALYSIS; UNMANNED VEHICLE;

COLUMBIA [MISSOURI]; MISSOURI; UNITED STATES;

GLYCINE MAX;

EID: 85032392082     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2017.10.011     Document Type: Article

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