Estimating the biomass of maize with hyperspectral and LiDAR data

Remote Sensing

Volumn 9, Issue 1, 2017, Pages

  Wang, Cheng ^a,b   Nie, Sheng ^b,c   Xi, Xiaohuan ^b   Luo, Shezhou ^b   Sun, Xiaofeng ^c  

^a CAPITAL NORMAL UNIVERSITY   (China)

^b INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

Airborne LiDAR; Biomass; Hyperspectral data; Maize; Partial least squares (PLS) regression

Indexed keywords

BIOMASS; CROPS; LEAST SQUARES APPROXIMATIONS; REGRESSION ANALYSIS; STATISTICAL METHODS;

AIRBORNE LIDAR; COEFFICIENT OF VARIATION; DIGITAL TERRAIN MODEL; HYPERSPECTRAL DATA; LEAVE-ONE-OUT CROSS-VALIDATION (LOOCV); LIGHT DETECTION AND RANGING; MAIZE; PARTIAL LEAST-SQUARES REGRESSION;

OPTICAL RADAR;

EID: 85010645191     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9010011     Document Type: Article

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