We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empiri...We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation （70.94%） were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution （29.06%）,with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.展开更多
An efficient despeclding algorithm is proposed based on stationary wavelet transform （SWT） for synthetic aperture radar （SAR） images. The statistical model of wavelet coefficients is analyzed and its performance i...An efficient despeclding algorithm is proposed based on stationary wavelet transform （SWT） for synthetic aperture radar （SAR） images. The statistical model of wavelet coefficients is analyzed and its performance is modeled with a mixture density of two zero-mean Gaussian distributions. A fuzzy shrinkage factor is derived based on the minimum mean square error （MMSE） criteria with Bayesian estimation. In the case above, the ideas of region division and fuzzy shrinkage arc adopted according to the interscale dependencies among wavelet coefficients. The noise-free wavelet coefficients are estimated accurately. Experimental results show that the algorithm proposed is superior to the refined Lee filter, wavelet soft thresbolding shrinkage and SWT shrinkage algorithms in terms of smoothing effects and edges preservation.展开更多
In this paper, a fast and accurate work-piece detection and measurement algorithm is proposed based on top-down feature extraction and bottom-up saliency estimation. Firstly, a top-down feature extraction method based...In this paper, a fast and accurate work-piece detection and measurement algorithm is proposed based on top-down feature extraction and bottom-up saliency estimation. Firstly, a top-down feature extraction method based on the prior knowledge of work- pieces is presented, in which the contour of a work-piece is chosen as the major feature and the corresponding template of the edges is created. Secondly, a bottom-up salient region estimation algorithm is proposed, where the image boundaries are labelled as background queries, and the salient region can be detected by computing contrast against image boundary. Finally, the calibration method for vision system with telecentric lens is discussed, and the dimensions of the work-pieces are measured. In addition, strategies such as image pyramids and a stopping criterion are adopted to speed-up the algorithm. An automatic system embedded with the proposed detection and measurement algorithm combining top-down and bottom-up saliency （DM-TBS） is designed to pick out defective work-pieces without any manual auxiliary. Experiments and results demonstrate the effectiveness of the proposed method.展开更多
基金supported by the Major Research Development Program of China(2016YFC0502704)National Science Foundation of China(31670645,31470578 and 31200363)+4 种基金National Forestry Public Welfare Foundation of China(201304205)Fujian Provincial Department of S&T Project(2013YZ0001-1,2015Y0083,2016Y0083,2016T3037 and 2016T3032)Key Laboratory of Urban Environment and Health of CAS(KLUEH-C-201701)Youth Innovation Promotion Association CAS(2014267)Key Program of the Chinese Academy of Sciences(KFZDSW-324)
文摘We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation （70.94%） were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution （29.06%）,with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.
基金A Postdoctoral Science Foundation of China (J63104020156) National Defence Foundation of China
文摘An efficient despeclding algorithm is proposed based on stationary wavelet transform （SWT） for synthetic aperture radar （SAR） images. The statistical model of wavelet coefficients is analyzed and its performance is modeled with a mixture density of two zero-mean Gaussian distributions. A fuzzy shrinkage factor is derived based on the minimum mean square error （MMSE） criteria with Bayesian estimation. In the case above, the ideas of region division and fuzzy shrinkage arc adopted according to the interscale dependencies among wavelet coefficients. The noise-free wavelet coefficients are estimated accurately. Experimental results show that the algorithm proposed is superior to the refined Lee filter, wavelet soft thresbolding shrinkage and SWT shrinkage algorithms in terms of smoothing effects and edges preservation.
基金supported by National Natural Science Foundation of China(Nos.61379097,91748131,61771471,U1613213 and 61627808)National Key Research and Development Plan of China(No.2017YFB1300202)Youth Innovation Promotion Association Chinese Academy of Sciences(CAS)(No.2015112)
文摘In this paper, a fast and accurate work-piece detection and measurement algorithm is proposed based on top-down feature extraction and bottom-up saliency estimation. Firstly, a top-down feature extraction method based on the prior knowledge of work- pieces is presented, in which the contour of a work-piece is chosen as the major feature and the corresponding template of the edges is created. Secondly, a bottom-up salient region estimation algorithm is proposed, where the image boundaries are labelled as background queries, and the salient region can be detected by computing contrast against image boundary. Finally, the calibration method for vision system with telecentric lens is discussed, and the dimensions of the work-pieces are measured. In addition, strategies such as image pyramids and a stopping criterion are adopted to speed-up the algorithm. An automatic system embedded with the proposed detection and measurement algorithm combining top-down and bottom-up saliency （DM-TBS） is designed to pick out defective work-pieces without any manual auxiliary. Experiments and results demonstrate the effectiveness of the proposed method.
