An adaptive unimodal subclass decomposition (AUSD) learning system for land use and land cover classification using high-resolution remote sensing

Land use and land cover classification is an important application of remote-sensing images. The performances of most classification models are largely limited by the incompleteness of the calibration set and the complexity of spectral features. It is difficult for models to realize continuous learning when the study area is transferred or enlarged. This paper proposed an adaptive unimodal subclass decomposition (AUSD) learning system, which comprises two-level iterative learning controls: The inner loop separates each class into several unimodal Gaussian subclasses; the outer loop utilizes transfer learning to extend the model to adapt to supplementary calibration set collected from enlarged study areas. The proposed model can be efficiently adjusted according to the variability of spectral signatures caused by the increasingly high-resolution imagery. The classification result can be obtained using the Gaussian mixture model by Bayesian decision theory. This AUSD learning system was validated using simulated data with the Gaussian distribution and multi-area SPOT-5 high-resolution images with 2.5-m resolution. The experimental results on numerical data demonstrated the ability of continuous learning. The proposed method achieved an overall accuracy of over 90% in all the experiments, validating the effectiveness as well as its superiority over several widely used classification methods.     

A model for dilatation, densification, and static liquefaction of loose sands

Utilizing basic balance laws of saturated granular media, a theoretical model for describing the phenomena of dilatation and densification of dry sand, as well as the increase of pore water pressure of saturated sand during shear loading, is developed. An expression for the free-energy function of loose sands is postulated, and the problem of static shearing of a sand sample is analyzed. Predictions of the model for pore water pressure are compared with those obtained experimentally for dry pluviated and moist vibrated samples of fine Ottawa sand and solid-glass beads and discussed.     

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.     

线性/非线性光谱混合模型估算白刺灌丛植被覆盖度

及时监测干旱与半干旱区光合/非光合植被覆盖度时空变化,可以为指导荒漠化防治工程及植被衰退机制研究提供重要信息。本文以甘肃民勤典型植被白刺灌丛为研究对象,通过地面控制性光谱实验获取混合光谱、端元光谱与丰度信息,开展线性与非线性光谱混合模型(包括核函数非线性和双线性混合模型)估算光合和非光合植被覆盖度的对比研究,采用全限制最小二乘法进行模型解混,分别获取各样本数据中各类端元丰度及其精度信息,通过模型分解的均方根误差(RMSE)与地面验证精度确定用于光合和非光合植被覆盖度估算的最佳光谱混合模型,其中参考端元丰度采用神经网络(NNC)分类算法对数字影像进行分类获取。结果表明:(1)引入阴影端元的四端元模型相对于传统的三端元模型(光合/非光合植被与裸土)能有效提高光谱解混的精度,并提高光合和非光合植被覆盖度估算精度;(2)对白刺灌丛来说,光合植被、非光合植被、裸土及阴影间多重散射混合效应存在,但混合效应不够显著;考虑非线性参数的核函数非线性光谱混合模型表现略低于线性光谱混合模型,因此非线性光谱混合模型在估算白刺灌丛光合和非光合植被覆盖度时相对于线性光谱混合模型没有明显优势;(3)基于光合/非光合植被、裸土与阴影四端元的线性光谱混合模型可以实现白刺灌丛光合和非光合植被覆盖度的准确估算,光合植被覆盖度估算RMSE为0.11 77,非光合植被覆盖度估算RMSE为0.0835。     

归脾合剂治疗新型冠状病毒感染后心脾两虚型不寐30例

目的：观察归脾合剂治疗新型冠状病毒感染后心脾两虚型不寐的临床疗效。方法：将新型冠状病毒感染后心脾两虚型不寐患者60例随机分为2组,每组各30例。对照组口服阿普唑仑片,治疗组在对照组基础上联合口服归脾合剂,连续治疗15 d。评价2组患者临床疗效、匹兹堡睡眠质量指数量表（PSQI）评分、中医证候积分及不良反应发生情况。结果：总有效率治疗组为96.67%（29/30）,明显高于对照组的80.00%（24/30）,2组比较,差异有统计学意义（P<0.05）;2组PSQI评分、中医证候积分治疗前后组内比较及治疗后组间比较,差异均有统计学意义（P<0.05）;不良反应发生率治疗组为9.99%（3/30）,对照组为13.32%（4/30）,2组比较,差异无统计学意义（P>0.05)。结论：归脾合剂治疗新型冠状病毒感染后心脾两虚型不寐的疗效优于单用西药治疗,可提高临床疗效,改善患者睡眠质量,且不增加不良反应。     

Effects of periodic saturation on K0 for a sandstone-mudstone particle mixture

Abstract

Sandstone-mudstone particle mixture (SMPM) is one of the main materials, which has been widely used for filling in and around reservoirs for water conservation projects. During the periodic rising and falling of the water level, the fill material for the embankments, dam, and other waterfront features will also undergo drainage-saturation cycles. The deformation and coefficient of lateral pressure at rest K₀ may be affected by periodic saturation. In this study, a device is modified for testing the K₀ for gravel-soil under periodic saturation. In order to investigate the effects of periodic saturation on K₀, a series of experiments were performed for SMPM under different vertical stress and saturation cycling. K₀^N values of SMPM containing 20% mudstone particles under periodic saturation were obtained. The results shows that the K₀^N initially increased, but eventually reached a stable value with the increasing number of periodic saturation cycles. The magnitude of the coefficient increment was also found to be related to the stress condition. K₀^N is a logarithmic function of the saturation cycling time. By calculating K₀^N with the proposed empirical formula, the deformation and stress distribution of the SMPM filler in waterfront engineering works can be calculated with greater precision.     

Discriminating lava flows of different age within Nyamuragira’s volcanic field using spectral mixture analysis

In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2 m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ∼15 years after eruption and occupies over 50% of the lava surfaces ∼40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization over time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons.     

土石混合料的结构分类

探讨了振动三参数：离心力、激振频率和名义振幅对土石混合料振动压实效果的影响,提出了两种对比工艺。并根据土石混合料在同一振动工艺下的压实特性,指出土石混合料具有三种结构类型,以最大干密度为判据,含石量为指标进行了结构分类,给出了分类区间。     

A comparison of variational formats for porous media subjected to dynamic loading

This paper presents a comparison of two variational formats for fully saturated porous media subjected to dynamic loading, whereby the general situation of relative fluid acceleration is considered: (1) the classical three‐field ( u , p, w )‐format and (2) a novel two‐field ( u , p)‐format, where the seepage velocity w is a spatially ‘local’ field whose treatment resembles that of internal variables in material models. The limited numerical comparison shows that the ( u , p)‐format competes well with the ( u , p, w )‐format. Indeed, it is consistent with the general acceleration modeling in the full range of permeabilities. Moreover, in the low permeability regime (where the magnitude of w is insignificant), the new format reflects the situation pertinent to ‘added‐mass’ and is more efficient than the classical ( u , p, w )‐format. Finally, the ( u , p)‐formatcan conveniently be implemented in existing FE‐codes based on the ‘added mass’ formulation. Copyright © 2010 John Wiley & Sons, Ltd.     

A different intensity recording for reducing the uncertainty in its assessment: An application to the completeness analysis of earthquake catalogues

The purpose of this paper is to emphasize the consequences of the ordinal and qualitative nature of seismic intensity regarding its recording. The classical way of recording by an integer value implies that on many occasions it can be difficult to associate only one intensity degree to an event. Therefore, we propose to record the intensity in a new way so that the expert is no longer restricted to indicating only one value, but can express his belief that the considered event belongs to any one of the intensity classes in the scale. Following this approach, as an example, we study the completeness of the Sannio-Matese catalogue and show how the degree of completeness changes according to the degree of uncertainty in intensity assessment.