横断山脉地区大气环流演变特征分析

应用Lamb-Jenkinson大气环流分型方法对横断山脉地区的8个经度×10个纬度范围内1948-2012年逐日平均的海平面气压场进行环流分型,由日平均海平面气压场算出6个环流指数（u、v、V、ξu、ξv、ξ）,并由此划分出27种不同的环流型。分型结果表明：横断山脉地区主要环流分型为E型、NE型、SE型、N型和C型,其频率分别为：21.4%、14.6%、13.7%、9.8%和9.5%;E和NE型环流频率逐渐增加,C型环流型频率逐渐减少。春季横断山脉地区主导环流比较繁琐;NE、N型为夏季的主要环流型,但E型环流在夏季的频率也相当大;秋季和冬季横断山脉地区的主导环流型都为E型和SE型。夏季主导环流型持续时间较长,冬季也是主导环流持续的时间较长,个别年份主导环流型持续时间超过了一个月,这主要与横断山脉地区复杂的地形有联系。     

Inverse Analysis of Deep Excavation Using Differential Evolution Algorithm

This paper presents the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems. A computer code, named Python‐based DE, is developed and incorporated into the commercial finite element software ABAQUS, with a parallel computing technique to run an FE analysis for all trail vectors of one generation in DE in multiple cores of a cluster, which dramatically reduces the computational time. A synthetic case and a well‐instrumented real case, that is, the Taipei National Enterprise Center (TNEC) project, are used to demonstrate the capability of the proposed back‐analysis procedure. Results show that multiple soil parameters are well identified by back analysis using a DE optimization algorithm for highly nonlinear problems. For the synthetic excavation case, the back‐analyzed parameters are basically identical to the input parameters that are used to generate synthetic response of wall deflection. For the TNEC case with a total of nine parameters to be back analyzed, the relative errors of wall deflection for the last three stages are 2.2, 1.1, and 1.0%, respectively. Robustness of the back‐estimated parameters is further illustrated by a forward prediction. The wall deflection in the subsequent stages can be satisfactorily predicted using the back‐analyzed soil parameters at early stages. Copyright © 2014 John Wiley & Sons, Ltd.     

Improvement of user’s accuracy through classification of principal component images and stacked temporal images

The classification accuracy of the various categories on the classified remotely sensed images are usually evaluated by two different measures of accuracy, namely, producer’s accuracy (PA) and user’s accuracy (UA). The PA of a category indicates to what extent the reference pixels of the category are correctly classified, whereas the UA of a category represents to what extent the other categories are less misclassified into the category in question. Therefore, the UA of the various categories determines the reliability of their interpretation on the classified image and is more important to the analyst than the PA. The present investigation has been performed in order to determine if there occurs improvement in the UA of the various categories on the classified image of the principal components of the original bands and on the classified image of the stacked image of two different years. We performed the analyses using the IRS LISS III images of two different years, i.e., 1996 and 2009, that represent the different magnitude of urbanization and the stacked image of these two years pertaining to Ranchi area, Jharkhand, India, with a view to assessing the impacts of urbanization on the UA of the different categories. The results of the investigation demonstrated that there occurs significant improvement in the UA of the impervious categories in the classified image of the stacked image, which is attributable to the aggregation of the spectral information from twice the number of bands from two different years. On the other hand, the classified image of the principal components did not show any improvement in the UA as compared to the original images.     

Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors ： an input vector and a class codebook vector. When a training sample is input into the model, Kohonen＇s competitive learning rule is applied to selecting the winning neuron from the Kohouen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training sam- ples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.     

低通滤波器在高光谱影像分类中的应用

研究了低通滤波器对类别可分性的改善原理,指出将其应用于高光谱影像分类有利于获取更为准确的类别分布信息,进而提高影像分类精度。最后通过实验对低通滤波器在高光谱影像分类中的表现进行了验证。     

计算数据域特征值的两种算法

设计两种计算数据域特征值的算法。此特征值通常是用线性反馈移位寄存器（ＬＦ－ＳＲ）组成的特征分析器得到的．在数据已按字节存放和速度要求不高的场合下，本算法将是十分方便和有用的．     

Ecological classification of European transitional waters in the North-East Atlantic eco-region

A new methodology to classify European North-East Atlantic transitional waters into ecological types has been developed based on the most important hydrological and morphological features that are likely to determine the ecology of aquatic systems in transitional waters. Hydrological indicators help identifying if a transitional water area is dominated by fresh or sea water and/or by intertidal or subtidal areas, while morphological indicators allow an estimation of the complexity of the transitional water and the diversity of the habitats involved. Twelve transitional waters of the southern Bay of Biscay were classified using this methodology and the five hydro-morphological types obtained were validated with benthic macro-invertebrate data. Transitional waters with a complex morphology showed the highest values of species diversity, while those with a smaller tidal influence showed lower species diversity. The ‘Scrobicularia’ and ‘Abra’ assemblages, previously identified in the study area, were found to be related to different types of transitional waters. The ‘Abra’ assemblage only appeared in estuaries with a complex morphology and dominated by tidal influences, while the ‘Scrobicularia’ assemblage was detected in all the transitional waters except for a single coastal lagoon. This classification of transitional waters may therefore be useful to establish the biological reference conditions needed for European Directives.     

Deltaic soil behavior classification using CPTu records—Proposed approach and applied to fifty-four case histories

For the past four decades, the CPT has played a key role in onshore and offshore soil investigations. One of the main applications of cone penetration test (CPT) is the soil behavioral classification. Most of the developed methods for soil identification using CPT and CPTu (piezocone) data are well categorized for common soils, such as clays, silts, and sands. Soils with low resistance or more compressibility generally involve problems in geotechnical engineering practice and construction projects. Consequently, these unusual deposits require further evaluation and more detailed data. Five major groups of problematic soils including: liquefiable, sensitive, peaty, collapsible, and expansive soils have been considered in this study. One hundred and forty CPT and CPTu test records were collected from fifteen countries. Sixty-one of the records are related to difficult soils. A brief comparison is performed for currently used soil behavioral classification charts, such as by Campanella et al. (1985 Campanella, R. G., P. K. Robertson, D. Gillespie, and J. Greig. 1985. Recent developments in in-situ testing of soils. Proceedings of 11th International Conference on Soil Mechanics and Foundation Engineering, ICSMFE, San Francisco, Vol. 2, 849–54. [Google Scholar]), Robertson (1990 Robertson, P. K. 1990. Soil classification using the cone penetration test. Canadian Geotechnical Journal 27 (1):151–58. doi:10.1139/t90–014[Crossref], [Web of Science ®] , [Google Scholar]), Jefferies and Davies (1991 Jefferies, M. G., and M. P. Davies. 1991. Soil classification using the cone penetration test: Discussion. Canadian Geotechnical Journal 28 (1):173–76. doi:10.1139/t91–023[Crossref], [Web of Science ®] , [Google Scholar]) and Eslami and Fellenius (1997 Eslami, A., and B. H. Fellenius. 1997. Pile capacity by direct CPT and CPTu methods applied to 102 case histories. Canadian Geotechnical Journal 34 (6):886–904. doi:10.1139/cgj-34–6-886[Crossref], [Web of Science ®] , [Google Scholar]). Analysis based on CPT data indicates that a few commonly used charts recognize relatively well problematic deposits. However, further studies are needed to increase the accuracy and capability of methods. Existing charts have some problems due to the limitations of the nature of rectangular charts based on two axes. A new format of classification chart, i.e., triangular form containing cone tip resistance (q_c), sleeve friction (f_s), and pore pressure (u₂) is proposed for soil identification which can be realized in practice. The proposed chart with more accuracy and less scattering of data than the previous charts is able to identify soil types particularly for deltaic soils.     

New Zealand estuary benthic health indicators summarised nationally and by estuary type

ABSTRACT

Ecological data are often collected at small geographic scales. However, analysing data collectively over wider scales can reveal results and patterns not shown in the smaller-scale data. We summarised data for intertidal benthic ecological (physico-chemical and biological) health indicators from New Zealand estuaries and compared the results against thresholds above which ecological impacts are expected to occur. Values for the sediment physico-chemical indicators mud and nutrients (nitrogen and phosphorus collectively) were above thresholds for at least 50% and at 31% of sites measured respectively. Sediment organic content and metal concentrations were generally low, with only maximum values exceeding the thresholds. Scores for biological indicators were within (or better than) the moderate health category for either at least 50%, or at least 75%, of sites. When compared across estuary types (based on a geomorphic classification system) we found statistically significant differences for thirteen of the sixteen indicators. Differences (among mean values) for highly significant results were relatively large compared to the range of values observed nationally for those indicators. However, the differences, except those for mud, were smaller than their respective ecological health threshold values. Our summary provides a reference for future comparisons of estuary indicators nationally and across estuary types.