基于遥感的辽河口岸线动态变化及成因分析

受人类活动和全球气候变化影响,河流入海口区域成为地表生态系统最脆弱地带。以美国国家航空航天局提供1986、1997和2008年Landsat ETM+影像及2017年Landsat OLI影像为数据源,基于目视解译法和谱间关系法,提取辽河口地区及部分河道岸线信息并分析其时空变化特征。研究表明,辽河口岸线经侵蚀-扩张-侵蚀过程,上游河道向两岸扩张,河道内部出现多个河心岛,主要为辽河口各种工程项目开展等人类活动所致。

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Estimation of structural modal parameters by fourier transform with an optimal window

An adaptive Fourier Transform （FT） with an optimal window has been proposed for the time-frequency analysis of nonstationary time series. The method allows for a good estimation of both frequency and amplitude of the spectrum and can be easily applied to the general case of time-varying signals. The evaluation of the proposed approach has been performed on measured time-varying signals from a suspension bridge model and a steel frame model whose data have the typical non-stationary characteristics. The numerical results show that the proposed approach can overcome some of the difficulties encountered in the classic Fourier transform technique and can achieve higher computation accuracy.

Cage and ladder structures of silsesquioxanes characterized by UV-MALDI-TOF mass spectrometry

The molar mass distribution of SSO in the first generation derived from the hydrolytic condensation oftwo trialkoxysilanes, [ 3- ( Methacryloxy ) propyl ] trimethoxysilane ( MPMS ) and vinyltrimethoxysilane ( VMS ) ,are determined by UV-MALDI-TOF MS. The comparisons of theoretical masses with experimental masses arecalculated using the proposed compounds, which are assigned to formulas Tn (OH)m, Tn (OMe)y orTn(OH)x(OMe)y[T=RSiO1.5 (x+y)/2n, R=--(CH2)3OOCCH(CH3)CH2 and--CHCH2]. Both theproposed cage and ladder structures of SSO derived from similar sol-gel process of monomers are illustrated. Thecauses for the difference in structures between SSO M and SSO V is discussed as well.

Study of oxidization of coal–pitch by O_3

For the purpose of obtaining small molecular and oxygen-containing aromatic compounds, taking a toluene-extracted coal pitch as the research object, the oxidation of coal-pitch by ozone （03） in formic acid was studied. The coal-pitch sample and the oxidized pitch residue were characterized by elementary analysis and Fourier transform infrared spectroscopy （FTIR）, while the small molecular products were analyzed by a gas chromatography-mass spectrometer （GC-MS）. The results show that the highest oxygen content of oxidized coal pitch had been acquired at a reaction temperature of 50℃C, an 03 flow rate of 6300 mg/h and a reaction time of 4 h. Quite a lot of hydroxyls and carbonyls were introduced into the structure of the oxidized coal-pitch, while the small molecules produced mainly involve nonpolar aro- matic compounds, aromatic anhydride and quinone compounds. It is speculated that the mechanism is direct electrophilic oxidation in which the molecules of 03 directly attack the aromatic ring at its carbon atoms with high electron density, and then generate hydroxyl or carbonyl until the aromatic ring cracks. This study shows that 03 can make the fused aromatic ring of coal-pitch become oxidized and depoly- merized, and hence the ozonization of coal-pitch can be a potential method for obtaining oxygen- containing aromatic compounds.

Unsupervised linear spectral mixture analysis with AVIRIS data

A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction （MNF） transformation and independent component analysis （ICA）. The modified MNF transformation is used to reduce noise and remove correlation between neighboring bands. Then the ICA is applied to unmix hyperspectral images, and independent endmembers are obtained from unmixed images by using post-processing which includes image segmentation based on statistical histograms and morphological operations. The experimental results demonstrate that this algorithm can identify endmembers resident in mixed pixels. Meanwhile, the results show the high computational efficiency of the modified MNF transformation. The time consumed by the modified method is almost one fifth of the traditional MNF transformation.

SINGULAR SPECTRUM ANALYSIS:METHODOLOGY AND APPLICATION TO ECONOMICS DATA

This paper describes the methodology of singular spectrum analysis (SSA) and demonstratethat it is a powerful method of time series analysis and forecasting,particulary for economic time series.The authors consider the application of SSA to the analysis and forecasting of the Iranian nationalaccounts data as provided by the Central Bank of the Islamic Republic of Iran.

ESTIMATING MULTI-COUNTRY PROSPERITY INDEX: A TWO-DIMENSIONAL SINGULAR SPECTRUM ANALYSIS APPROACH

With the development of the global economy, interaction among different economic entities from one region is intensifying, which makes it significant to consider such interaction when constructing composite index for each country from one region. Recent advances in signal extraction and time series analysis have made such consideration feasible and practical. Singular spectrum analysis （SSA） is a well-developed technique for time series analysis and proven to be a powerful tool for signal extraction. The present study aims to introduce the usage of the SSA technique for multi-country business cycle analysis. The multivariate SSA （MSSA） is employed to construct a model-based composite index and the two dimensional SSA （2D-SSA） is employed to establish the multi-country composite index. Empirical results performed on Chinese economy demonstrate the accuracy and stability of MSSA-based composite index, and the 2D-SSA based composite indices for Asian countries confirm the efficiency of the technique in capturing the interaction among different countries.

Spatiotemporal spectrum and momentum flux of the stratospheric gravity waves generated by a typhoon

The simulation results of Typhoon Matsa （2005） by using the Weather Research and Forecasting （WRF） model show that pro- nounced stratospheric gravity waves （GWs） are generated in the vicinity of the typhoon. Using the model output, we investi- gate the spatial structures and the temporal variations of the GWs through a three dimensional （3-d） spectral analysis, i.e. the spectrum with respect to two horizontal wavenumbers and frequency. We further derive the momentum flux carried by the GWs. Spectral investigation results show that the power spectral density （PSD） of the GWs exhibits a single-peaked spectrum, which consists primarily of a distinct spectrum at horizontal wavelength of -1000 km, time period of 12-18 h, and vertical wavelength of 7-9 kin. This spectrum is different from the spectra of GWs generated by deep convections disclosed by the previous researches. Both the PSD and momentum flux spectrum are prominent in positive kh portion, which is consistent with the fact that the GWs propagate in the upstream of mean flow. Large momentum flux is found to be associated with the GWs, and the net zonal momentum flux is 0.7845×10-3 Pa at 20 km height, which can account for -26% of the momentum flux that is required in driving the QBO phenomenon.

Prospects for petroleum mass spectrometry and chromatography

Several recently developed analytical techniques, based on high-end mass spectrometry and chromatography, for dealing with challenges in petroleum characterization are reported. Folded flight path time-of-flight mass spectrometry provides resolving power up to 100000, enabling accurate mass measurement for molecular formula determination with high confidence. Atmos- pheric pressure chemical ionization （APCI） can be used in both gas chromatography （GC, as APGC） and liquid chromatog- raphy （LC） for analyzing non-polar hydrocarbons as well as polar compounds. The improvement in chromatography facilitates the mass spectrometric analysis through online coupling. Comprehensive two-dimensional gas chromatography （GCxGC） re- solves overlapping components, rendering accurate identification and quantitation. Supercritical fluid extraction has been de- veloped as an alternative method to replace traditional solvent extraction methods and eliminate the use of large volumes of solvents that can be harmful to health and environment. Supercritical fluid chromatography （SFC） has been developed as a convergence of GC and LC chromatographic techniques. The use of SFC for heavy oils and residua has been demonstrated. Prospective developments in the use of mass spectrometric and chromatographic methods for petroleum characterization are also described.

EXCHANGE RATE FORECASTING WITH OPTIMUM SINGULAR SPECTRUM ANALYSIS

Forecasting exchange rate is undoubtedly an attractive and challenging issue that has been of interest in different domains for many years. The singular spectrum analysis （SSA） technique has been used as a promising technique for time series forecasting including exchange rate series. The SSA technique is based upon two main choices： Window length, L, and the number of singular values, r. These values are very important for the reconstruction stage and forecasting purposes. Here the authors consider an optimum version of the SSA technique for forecasting exchange rates. The forecasting performances of the SSA technique for one-step-ahead forecast of six exchange rate series are used to find the best L and r.

COMBINING SINGULAR SPECTRUM ANALYSIS AND PAR(p) STRUCTURES TO MODEL WIND SPEED TIME SERIES

Singular spectrum analysis （SSA） is a technique that decomposes a time series into a set of components, such as, trend, harmonics, and residuals. Leaving out the residual components and adding up the others, the time series can be smoothed. This procedure has been used to model Brazilian electricity consumption and flow series. The PAR（p）, periodic autoregressive models, has been broadly used in modelling energy series in Brazil. This paper presents an approach of this decomposition method, by fitting the PAR（p）, considering its multivariate version known as multivariate SSA （MSSA）. The method was applied to a vector of two wind speed series recorded at two locations in the Brazilian Northeast region. The obtained results, when compared to the univariate decomposition of each series, were far superior, showing that the spatial correlation between the two series were considered by MSSA decomposition stage.