The genus Phytobius Schoenherr,1833(Ceutorhynchinae:Phytobiini)from China was revised on the basis of morphological observations and barcode identification.The distribution of the type species P.leucogaster(Marsham,18...The genus Phytobius Schoenherr,1833(Ceutorhynchinae:Phytobiini)from China was revised on the basis of morphological observations and barcode identification.The distribution of the type species P.leucogaster(Marsham,1802)in China was confirmed for the first time,based on specimens collected from Beijing and Tianjin.Another species,P.friebi Wagner,1939 was found widely distributed along the east coast of China.The morphologically varied populations from the north(Heilongjiang)and south(Zhejiang)are suggested to be the same species based on the genetic divergence and phylogeny analysis of CO1 sequences.The plant association of the species with Polygonum hydropiper L.(Polygonaceae)was discovered.Habitus photographs,illustrations of important characters,distribution map,and a key to both species are provided.展开更多
High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in th...High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in the data, the data processing of HHR is a challenging work. In this paper, based on spectral mixture analysis theory, a new stack of parts description features were extracted, and then incorporated with a stack of morphology based spatial features. Partially supervised constrained energy minimization (CEM) and unsupervised nonnegative matrix factorization (NMF) were used to extract the part-features. The joint features were then integrated by SVM classifier. The advantages of this method are the representation of physical composition of the urban area by the parts-features and the show of multi-scale structure information by morphology profiles. Experiments with an airborne hyper-spectral data flightline over the Washington DC Mall were performed, and the performance of the proposed algorithm was evaluated in comparison with well-known nonparametric weighted feature extraction (NWFE) and feature selection method. The results shown that the proposed features-joint scheme consistently outperforms the traditional methods, and so can provide an effective option for processing HHR data in urban area.展开更多
基金supported by the National Natural Science Foundation of China(31472031)Zhejiang Provincial Natural Science Foundation(LY14C040001)
文摘The genus Phytobius Schoenherr,1833(Ceutorhynchinae:Phytobiini)from China was revised on the basis of morphological observations and barcode identification.The distribution of the type species P.leucogaster(Marsham,1802)in China was confirmed for the first time,based on specimens collected from Beijing and Tianjin.Another species,P.friebi Wagner,1939 was found widely distributed along the east coast of China.The morphologically varied populations from the north(Heilongjiang)and south(Zhejiang)are suggested to be the same species based on the genetic divergence and phylogeny analysis of CO1 sequences.The plant association of the species with Polygonum hydropiper L.(Polygonaceae)was discovered.Habitus photographs,illustrations of important characters,distribution map,and a key to both species are provided.
基金Supported by the Major State Basic Research Development Program(973Program)of China(No.2009CB723905)the National High TechnologyResearch and Development Program(863Program)of China(No.2009AA12Z114)the National Natural Science Foundation of China(Nos.40930532,40901213,40771139)
文摘High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in the data, the data processing of HHR is a challenging work. In this paper, based on spectral mixture analysis theory, a new stack of parts description features were extracted, and then incorporated with a stack of morphology based spatial features. Partially supervised constrained energy minimization (CEM) and unsupervised nonnegative matrix factorization (NMF) were used to extract the part-features. The joint features were then integrated by SVM classifier. The advantages of this method are the representation of physical composition of the urban area by the parts-features and the show of multi-scale structure information by morphology profiles. Experiments with an airborne hyper-spectral data flightline over the Washington DC Mall were performed, and the performance of the proposed algorithm was evaluated in comparison with well-known nonparametric weighted feature extraction (NWFE) and feature selection method. The results shown that the proposed features-joint scheme consistently outperforms the traditional methods, and so can provide an effective option for processing HHR data in urban area.
