自然灾害调查数据的多尺度异常检测方法研究及应用

大范围自然灾害调查,涉及区域环境差异大,数据获取方式多样,参与人员多,各级汇总成果中存在一些异常调查单元,需要人工判读其合理性,但单纯依靠人工从海量数据中有效识别异常是不现实的。本文设计了一种自然灾害调查数据的多尺度异常检测方法,综合运用离群检测方法和空间数据挖掘算法,分别进行异常值和异常空间分布模式检测,能够从海量调查数据中快速提取各级尺度的异常值和异常调查单元,支撑人工判读工作。将该方法应用于全国山洪灾害调查评价汇总数据的审核中,以全国历史山洪灾害点和防治区乡镇面积审核为例,分别快速提取了县乡两级区划中的山洪灾害点密度异常单元和面积值异常的乡镇单元,通过对检测结果进行分析,发现是填报口径不一致、单位错误、记录重复等原因造成的。最后分析了该方法在大范围自然灾害调查中的适用条件和方法。     

基于模糊聚类的声呐图像多区域分割

图像分割是图像识别中的主要问题,同时它又是一个经典难题;声呐图像恶劣的品质使图像的分割变得更为困难。文章将模糊聚类应用于声呐图像的多区域分割,实验证明这种方法简便而有效。     

On the Optimal Estimation of the Cumulative Distribution Function in Presence of Spatial Dependence

For spatial analysis of data, the optimal prediction of the cumulative distribution function (c.d.f.) is made difficult by the presence of spatial dependence, particularly when data are clustered. Several methods have been proposed in the literature to correct for the redundancy which is present when the observed values are correlated. Most of them are based on an unequal weighting of the values for the computation of the c.d.f. The methodology is extended by defining weights which depend both on the spatial correlation and on the threshold value. If a parametric multivariate distribution is assumed, optimal weights can be obtained conditionally to the choice of this distribution, and a nonparametric indicator estimate of the c.d.f. can be defined a posteriori. The method can be extended in order to provide kernel smoothed estimates of the c.d.f., by replacing the indicator functions by other functions taken here as complementary differentiable c.d.f., whose parameters are defined in order to preserve the unbiasedness and minimum variance property of the estimate, conditionally to the choice of the a priori distribution. A simulation study is conducted in order to emphasize the properties of the various methods. It is found that, even for bounded and positively skewed distributions, a simplified version of the method seems to perform quite well without significant loss of efficiency, and provides smooth estimates of the c.d.f. which can be differentiated in order to obtain density estimates. These estimates do not depend highly on the choice of the parameters for the a priori distribution, and yet they respect major characteristics of the a priori c.d.f., such as lower and upper bounds, which are mainly dictated by the nature of the variable under study. A practical case study is conducted on cobalt concentrations for various rock types in the Swiss Jura, illustrating the applicability of the methodology for real datasets.     

Spatial analysis using clustering methods: Evaluating central point and median approaches

Spatial analysis is an important area of research which continues to make major contributions to the exploratory capabilities of geographical information systems. The use and application of classic clustering methods is being pursued as an exploratory approach for the analysis of spatially referenced data. Numerous potential clustering approaches exist, so research assessing the relative differences of these approaches is important. This paper evaluates the median and central points optimization based clustering approaches for use in the context of exploratory spatial data analysis. Functional and visual comparisons using three spatial applications across a range of cluster values are carried out. The empirical results suggest that these two clustering approaches identify very similar groupings. The significance of this finding is that the development of clustering tools for exploratory analysis may be limited to the median based approach given relative computational and solvability considerations. Received: 28 September 1998/Accepted: 9 August 1999     

德兴铜矿大坞河流域土壤Cu元素形态的聚类分析

在研究重金属元素对德兴铜矿地区环境污染情况的过程中,采用了连续提取法对低品位矿石堆浸场等地的土壤样品进行测量,并以Cu元素存在形态作为指标,综合德兴铜矿地区的特点对Cu元素形态进行了深入的聚类分析研究,得出了Cu在当地土壤中主要以有机态和硅酸盐态存在,但是碳酸盐态等其他四种形态所含比例较大,并且在酸性或氧化环境下具有一定的迁移转化能力,对环境具有潜在危害的结论,为进一步研究其他重金属的迁移转化提供了参考,并为矿区的环境治理和复垦提供了有价值的科学依据.     

Non-stationary spatial covariance structure estimation in oversampled domains by cluster differences scaling with spatial constraints

In the analysis of spatiotemporal processes underlying environmental studies, the estimation of the non-stationary spatial covariance structure is a well known issue in which multidimensional scaling (MDS) provides an important methodological approach (Sampson and Guttorp in J Am Stat Assoc 87:108–119, 1992). It is also well known that approximating dispersion by a non-metric MDS procedure offers, in general, low precision when accurate differences in spatial dispersion are needed for interpolation purposes, specially if a low dimensional configuration is employed besides a high number of stations in oversampled domains. This paper presents a modification, consisting of including geographical spatial constraints, of Heiser and Groenen’s (Psychometrika 62:63–83, 1997) cluster differences scaling algorithm by which not the original stations but the cluster centres can be represented, while the stations and clusters retain their spatial relationships. A decomposition of the sum of squared dissimilarities into contributions from several sources of variation can be employed for an exploratory diagnosis of the model. Real data are analyzed and differences between several cluster-MDS strategies are discussed.     

Long-term rainfall trends and change points in hot and cold arid regions of India

This study examined trends and change points in 100-year annual and seasonal rainfall over hot and cold arid regions of India. Using k-means clustering, 32 stations were classified into two clusters: the coefficient of variation for annual and seasonal rainfall was relatively high for Cluster-II compared to Cluster-I. Short-term and long-term persistence was more dominant in Cluster-II (entirely arid) and Cluster-I (partly arid), respectively. Trend tests revealed prominent increasing trends in annual and wet season rainfall of Cluster-II. Dry season rainfall increased by 1.09 mm year^?1 in the cold arid region. The significant change points in annual and wet season rainfall mostly occurred in the period 1941–1955 (hot and cold), and in the dry season in the period 1973–1975 (hot arid) and in 1949 (cold arid). The findings are useful for managing a surplus or deficiency of rainwater in the Indian arid region.

EDITOR A. Castellarin; ASSOCIATE EDITOR S. Kanae     

Delineation of precipitation regions in two Canadian study areas: the role of the temporal resolution of the precipitation data

The identification of homogeneous precipitation regions has value in many water resources engineering applications (infrastructure planning, design, operations; climate forecasting, modelling). The objective of this paper is to assess the sensitivity of precipitation regions to the temporal resolution (monthly, seasonal, annual and the annual maximum series) of the data. The presented method uses the fuzzy c-means clustering algorithm to partition climate sites into statistically homogeneous precipitation regions. The regions are validated using an approach based on L-moment statistics. The method is conducted in two climatically different study areas in western and eastern Canada. There does not appear to be a relationship between the spatial distributions of the regions formed using different temporal resolutions of the precipitation data. It is recommended to delineate precipitation regions that are specific to the task at hand, and to select a temporal resolution that is consistent with the final application of the regional precipitation dataset.

EDITOR A. Castellarin; ASSOCIATE EDITOR T. Kjeldsen     

河北南部及邻近地区中小地震震源机制特征分析

利用P波初动和振幅相结合的广义极性振幅技术法(GPAT),反演2007-2016年河北南部及邻近地区发生的368个ML≥2.0中小地震震源机制解,利用统计方法和系统聚类方法,分析震源机制解参数特征。结果表明,河北南部及邻区中小地震以走滑地震为主;正断层和逆断层相对较少,断层面以倾斜或直立为主,断层运动表现为左旋走滑和右旋走滑,应力作用以水平和近水平推扭方式为主。     

Process inference from topographic fractal characteristics in the tectonically active Northwest Himalaya,India

Topography evolves under the coupled effect of exogenic and endogenic governing factors, and their scale-(in)variant dynamics. This results in a self-affine topography across a finite range, with a characteristic fractal dimension. Fractal analysis has been used to classify geological terrains having distinct litho-tectonic settings. However, process-based understanding of the fractal behaviour of a natural landscape is still limited. The current study aims to substantiate and expand upon the present knowledge of topographic response to the complex actions of the governing factors using fractal characteristics. We examined the association between the litho-tectonic, climatic settings and the fractal characteristics of the topography in the tectonically active Northwest Himalaya. Our analysis was carried out in three separate sectors having diverse litho-tectonic settings. We used the roughness–length method to calculate the fractal parameters (fractal dimension, D; ordinate intercept, q). The Higher and the Lesser Himalaya were found to be characterized by low D and high q, while the tectonically active Sub Himalaya was found to have moderate D and low q. The southernmost foreland alluvial plains were characterized by high D and low q. Clusters of the fractal parameters were found to be consistent in spatial pattern across the three sectors. Our results showed that the geological–geomorphological settings and the associated processes (e.g. uplift, erosion and diffusion) can be well inferred using the fractal characteristics of the topography. Further, our results implied first-order control of lithology in sustaining and shaping the topographic geometry (both its amplitude and texture) in the tectonically active Northwest Himalaya. The spatial distribution of the fractal parameters also suggested the secondary control of tectonic uplift and, to a much lesser extent, mean annual rainfall on the topographic geometry. These results collectively point to the role of complex actions of the governing factors in the landscape evolution process. © 2020 John Wiley & Sons, Ltd.