Laboratory assessment of three quantitative methods for estimating the organic matter content of soils in China based on visible/near-infrared reflectance spectra

Geoderma

Volumn 202-203, Issue , 2013, Pages 161-170

  Tian, Yongchao ^a   Zhang, Juanjuan ^a,b   Yao, Xia ^a   Cao, Weixing ^a   Zhu, Yan ^a  

^a NANJING AGRICULTURAL UNIVERSITY   (China)

^b HENAN AGRICULTURAL UNIVERSITY   (China)

Author keywords

Backpropagation neural network; DI(NDR554, NDR1398); First derivative spectra; Hyperspectral reflectance; Norris smoothing filter; Soil organic matter

Indexed keywords

BACK PROPAGATION NEURAL NETWORKS; DI(NDR554, NDR1398); FIRST DERIVATIVE; HYPERSPECTRAL REFLECTANCE; NORRIS SMOOTHING; SOIL ORGANIC MATTERS;

BIOGEOCHEMISTRY; BIOLOGICAL MATERIALS; CALIBRATION; ESTIMATION; FINITE DIFFERENCE METHOD; NEURAL NETWORKS; ORGANIC COMPOUNDS; PRINCIPAL COMPONENT ANALYSIS; REFLECTION; REGRESSION ANALYSIS; SOILS;

GEOLOGIC MODELS;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CALIBRATION; ECOZONE; FILTER; LABORATORY METHOD; MODEL VALIDATION; NEAR INFRARED; NUMERICAL MODEL; QUANTITATIVE ANALYSIS; SENSOR; SOIL ANALYSIS; SOIL ECOSYSTEM; SOIL ORGANIC MATTER; SOIL TYPE; SPECTRAL REFLECTANCE; VISIBLE SPECTRUM;

CHINA;

EID: 84876739026     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2013.03.018     Document Type: Article

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