Liang Wanga,b, Jiping Liua,b, Shenghua Xub, Jinjin Dongc, Yi Yangd
Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 391-398, 2018, DOI:10.1080/10798587.2017.1296660
Abstract Forest biomass is a significant indicator for substance accumulation and forest succession, and can
provide valuable information for forest management and scientific planning. Accurate estimations of
forest biomass at a fine resolution are important for a better understanding of the forest productivity
and carbon cycling dynamics. In this study, considering the low efficiency and accuracy of the existing
biomass estimation models for remote sensing data, Landsat 8 OLI imagery and field data cooperated
with the radial basis function artificial neural network (RBF ANN) approach is used to estimate the
forest Above Ground Biomass (AGB) in More >
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