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1.
Artificial neural networks and cluster analysis in landslide susceptibility zonation 总被引：14，自引：1，他引：13
A landslide susceptibility analysis is performed by means of Artificial Neural Network (ANN) and Cluster Analysis (CA). This kind of analysis is aimed at using ANNs to model the complex non linear relationships between mass movements and conditioning factors for susceptibility zonation, in order to identify unstable areas. The proposed method adopts CA to improve the selection of training, validation, and test records from data, managed within a Geographic Information System (GIS). In particular, we introduce a domain-specific distance measure in cluster formation. Clustering is used in data pre-processing to select non landslide records and is performed on the whole dataset, excluding the test set landslides. Susceptibility analysis is carried out by means of ANNs on the so-generated data and compared with the common strategy to select random non-landslide samples from pixels without landslides. The proposed method has been applied in the Brembilla Municipality, a landslide-prone area in the Southern Alps, Italy. The results show significant differences between the two sampling methods: the classification of the test set, previously separated and excluded from the training data, is always better when the non-landslide patterns are obtained using the proposed cluster sampling. The case study validates that, by means of a domain-specific distance measure in cluster formation, it is possible to introduce expert knowledge into the black-box modelling method, implemented by ANNs, to improve the predictive capability and the robustness of the models obtained. 相似文献
2.
Two approximate methods for weighted principal components analysis (WPCA) were devised and testedin numerical experiments using either empirical variances (obtained from replicated data) or assumedvariances (derived from unreplicated data). In the first ('spherical') approximation each data vector wasassigned a weight proportional to the geometrical mean of its variances in all dimensions. Thearithmetical mean of variances was used instead in the other approximation. Both the numericalexperiments with artificial data containing random errors of various kinds (constant, proportional,constant plus proportional, Poisson) and the analysis of two sets of Raman spectra clearly indicated thenecessity of introducing statistical weights. The spherical approximation was found to be slightly betterthan the arithmetical one. The application of statistical weighting was found to improve the performanceof PCA in estimation problems. 相似文献
3.
雅鲁藏布江中部流域沙地植被的分类和排序 总被引：6，自引：1，他引：5
选用模糊聚类分析方法,利用群落组种的相对盖度作为优势度指标,将该区沙地植被划分为22个群系,群系下又划分出了不同的群丛。同时,采用主分量分析(PCA)模型,对10个常见的群落类型进行了二维排序,比较直观和真实地反映了不同群落类型在土壤砾石化程度和土壤潜在肥力2个环境梯度上的分布情况。 相似文献
4.
在讨论以往生态经济分区研究方法与理论的基础上,提出了新的研究思路--基于网格的生态经济分区。利用GIS格网技术和相关统计软件,从甘肃省生态与经济两大系统耦合发展的历程分析入手,选取2010年甘肃省的26个生态经济指标,以6 km×6 km的规则格网,将整个甘肃省分为12 243个研究单元。经过分析比较,甘肃省被分为4个生态经济区即西北干旱区(Ⅰ)、陇中冷温带半湿润区(Ⅱ)、甘南高寒带湿润区(Ⅲ)、陇南暖温带湿润区(Ⅳ)和21个生态经济亚区。结合DEM,进一步对研究区进行分区,以期为促进形成甘肃省可持续发展格局提供科学依据。研究表明,格网技术提高了分区的精度和速度,是进行生态经济分区的有效方式之一。 相似文献
5.
戈壁地表砾石粒径与遥感多光谱数据、植被指数及地学因子存在相关关系,但这些因子间可能存在着多重相关性,如利用这些因子直接建模估测戈壁地表砾石粒径,则可能出现病态模型。利用主成分分析法筛选因子,既可保留多个相关因子的主要信息,又可避免因子间共线性的问题,达到降维、简化模型的效果。因此,本文以新疆哈密市境内山前洪积扇戈壁地表砾石为研究对象,以2010年Landsat TM遥感影像及30 m分辨率DEM为基本数据源,采用主成分分析法,从选择的43个遥感及地学因子（主要包括影像各波段信息、DEM、NDVI、 GEMI,影像经K-T变换得到SBI、GVI、WVI三个分量,通过纹理分析得到的各个波段的均值、方差、信息熵、相关性及对比度等纹理因子,以及利用DEM提取的粗糙度等）中,筛选提取其主成分。结果表明,第一主成分至第五主成分的累计贡献率达98.0%,以前5个主成分作为自变量,借助SPSS软件中的多元回归分析功能,建立戈壁地表砾石粒径估测的回归模型,模型经方差分析及相关性检验,达到显著相关水平。基于建立的估测模型,进行了戈壁地表砾石粒径估测,经验证,实测值与估算值紧密相关。研究可帮助我们了解戈壁的特征,为戈壁区改造利用,认识沙粒迁移、沙漠扩展提供技术支持。 相似文献
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7.
选取南洛河上游洛南盆地10 种植被类型下40 处样点表土苔藓开展孢粉与植被关系的研究.结果表明,表土中孢粉组成能很好地反映植被类型.森林表土中乔木植物花粉含量平均值大于40%,且有较高含量的中华卷柏孢子;疏林草原、灌丛群落中乔木植物花粉平均含量分别为13.2%和16.6%,灌木植物花粉相对草丛群落含量较高;草丛群落和农田中乔木花粉平均含量均<10%,草本植物花粉>80%,灌木植物花粉<1%.洛南盆地表土孢粉总浓度平均为1.42×105粒/g,与植被覆盖度关系较弱,而与植被类型有一定联系,能辅助植被类型的辨识.聚类分析和PCA分析都能较好区分森林和非森林植被,前者能较好地区分松林和混交林,后者能较好地区分农田和灌、草丛植被,且比聚类分析更加稳定.松属、栎属等乔木花粉具有较强的扩散能力,能指示区域植被,松属没有表现出很强的超代表性,栎属具有低代表性;蒿属花粉与植被覆盖度间的相关关系较差,具有明显的超代表性,其大量出现与人类的干扰有一定的联系,禾本科花粉具有很好的植被指示性和低代表性,藜科花粉的高含量主要指示了高强度的人类活动;中华卷柏孢子在地层中的大量出现具有指示森林或松林环境的意义. 相似文献
8.
波段数目多和波段宽度窄是高光谱分辨率遥感的两个显著特点 ,常规的用于分析的波段组合方法在信息的利用上是不充分的。笔者利用六种植物的冠层测量数据作为试验样本 ,使用了系统聚类分析的方法 ,找出具有信息相似性的波段 ,将这些波段划分为同一种通道类型 ,它们对于植被冠层中的同一种生化成分是敏感的 ,并使用主成分分析的方法进行降维、合并处理 ,得出可以用于实际分析的波段线性组合方法。最后利用前两个主成分的相对得分图 ,进行不同物种类别的划分 ,达到识别的目的。 相似文献
9.
祁连山及周边区域地形复杂,降水分布极不均匀,如何科学地分区分型,对把握研究区域降水分布特征具有极为重要的意义。利用该区域31个国家基本站1961—2020年5—9月降水量资料,采用主成分分析方法（PCA）对该区域降水量进行分析,再通过聚类分析（CAST）对该结果进行显著性检验,最后将分区分型结果应用于人工增雨作业效果评估。结果表明：（1） 祁连山及周边可分成7个区域（Z1~Z7）,累积方差贡献率超过78%。（2） 这7个区域分别以乐都、海晏、野牛沟、武威、高台、临泽、刚察为中心点,划分结果与降水量、地理地形、海拔高度显著关联。（3） 依托区域历史回归统计方法对人工增雨作业效果进行评价,发现1992—2020年石羊河流域5—9月绝对增雨量、相对增雨率分别为8.91 mm、6.51%,其中7月最高（6.30 mm、21.86%）,8月次之（5.44 mm、16.11%）。基于地面降水量的作业效果评价往往受对比区选择的影响,聚类检验方法不仅有助于复杂地形下降水量的分区研究,还为科学选择对比区提供了客观依据。 相似文献
10.
Javier Roca-Pardiñas Tomás R. Cotos-Yáñez Rubén Pérez-Álvarez 《International journal of geographical information science》2017,31(4):676-693
We propose a method to evaluate the existence of spatial variability in the covariance structure in a geographically weighted principal components analysis (GWPCA). The method, that is extensive to locally weighted principal components analysis, is based on performing a statistical hypothesis test using the eigenvectors of the PCA scores covariance matrix. The application of the method to simulated data shows that it has a greater statistical power than the current statistical test that uses the eigenvalues of the raw data covariance matrix. Finally, the method was applied to a real problem whose objective is to find spatial distribution patterns in a set of soil pollutants. The results show the utility of GWPCA versus PCA. 相似文献
11.
水质评价对决策者决定水的使用功效尤为重要。水质综合评价系统中涉及到大量因子与指标,因子之间相互作用,致使水质的评价工作相对困难。主成分分析法可以消除因子间的相关性,因而被广泛应用于水质评价,但其忽略了数据离散程度的问题。熵值法则考虑了数据的离散特点。为更好地进行水质的综合评价,本文提出把主成分分析法和熵值法结合起来确定指标权重的方法,建立了水质评价模型,并采用该模型对郑州市金水河再生水2009年的水质情况进行评价,将评价结果与单独采用主成分分析或熵值法的结果进行了比较。结果表明了该方法的可行性与实用性,能够为非常规水资源利用提供理论依据和决策参考。 相似文献
12.
RENé HENRION 《地理学报(英文版)》1993,(6)
In contrast with conventional PCA,a direct superposition and joint interpretation of loading plots is notpossible in three-way PCA,since there may be data variance which is described by unequal componentsof different modes.The contributions to variance of all possible combinations of components aredescribed in the core matrix.Body diagonalization,which is achieved by appropriate rotation ofcomponent matrices,is an essential tool for simplifying the core matrix structure.The maximum degreeof body diagonality which may be obtained from such transformations is analysed from both themathematical and simulation viewpoints.It is shown that,at least in the average case,high degrees canbe expected,which makes the procedure reasonable for many practical applications.Furthermore,simulation as well as theoretical derivation show that the success of body diagonality depends on the so-called polarity of the core array.The methodology is illustrated by a three-way data example fromenvironmental chemistry. 相似文献
13.
差分主成分分析法在辽河三角洲景观变化中的应用 总被引：7，自引：0，他引：7
差分主成分分析法是应用遥感数据检测景观变化的一种新方法。为了提高检测精度,我们利用TM卫星遥感数据,改进了主成分分析法和图像差值法,提出了差分主成分分析法。并以辽河三角洲地区为例,对该方法进行了验证。研究结果表明：(1) 与传统的检测法-分类后比较法相比,差分主成分分析法具有较高的检测精度,总检测精度为0.89,Kappa指数为0.82;(2) 在1984~2000年的16年间,辽河三角洲地区有近22%的景观发生了变化,主要包括芦苇湿地的减少、水稻田的增加以及城镇用地的增加。 相似文献
14.
Thirteen different components of six samples belonging to stained medieval glass windows and twelvesimilar samples found in the archives of Girona Cathedral(Catalonia,Spain)during restoration workwere determined by x-ray fluorescence analysis.The use of display and cluster analysis methods,principal components analysis,non-linear mapping,minimal spanning tree and agglomerativehierarchical clustering applied to these results,together with those of nine samples from the samecathedral previously studied,showed the presence of a quite compact cluster formed by the soda-typesamples,indicating a probably similar origin and confirming the peculiarities of this Mediterranean area.The potash-type glasses were highly scattered with little similarity among them,suggesting a likelydifferent source of these samples.The twelve glasses of strictly unknown origin were found to have a highdegree of resemblance to the samples of known context,thus excluding the possibility of them beingsamples made in a very different age or site.Three of them were classified into the same group as thewell-defined soda-type glasses by the pattern recognition method SIMCA. 相似文献
15.
Pattern recognition techniques(PCA,Bayesian analysis,LDA and KNN)are applied to a set of datacomposed of cancer patients and controls.A rather good separation between different populations isobtained using four tumor markers determined for each patient. 相似文献
16.
基于动态约束的元胞自动机与复杂城市系统的模拟 总被引：2，自引：0，他引：2
为获得复杂城市系统更理想的模拟效果,提出时空动态约束的城市元胞自动机(CA)模型。用不同区域、不同时间新增加的城市用地总量作为CA模型的约束条件,形成时空动态约束的CA模型,并利用该模型模拟1988—2010年东莞市和深圳市城市扩张过程。结果表明,利用CA模型模拟的1993年城市用地总精度比静态CA模型提高了5.86%,而且模型中的动态约束条件可以反映城市发展的时空差异性。 相似文献
17.
针对陕西省关中区域1978—2017年的农业生产数据,在分析关中40 a农业粮食生产的趋势变化后,运用主成分分析法,对影响关中农业生产中的地理环境和生产投入等主要因素进行了评价研究。结果表明：（1） 关中农业粮食生产的趋势变化呈现周期为3～7 a的循环增长方式,平均每周期峰值增长率为4.5%。（2） 主成分分析研究后得出,第一主成分全是地理因素指标,方差贡献率达到0.554,对关中地区农业粮食生产起着非常显著的决定影响作用,包括受灾农田面积（不含病虫害）、主要粮食作物播种面积、成灾农田面积（不含病虫害）、有效灌溉耕地面积、耕地面积;第二主成分方差贡献率为0.25,是影响粮食生产的重要因素和农业生产的生命补给。包括农业用电量、化肥、农用机械等生产资料投入和主要粮食作物稳产面积、劳动力投入因素指标;第三主成分为农药应用量,方差贡献率为0.068,影响较小。主成分累计方差贡献为0.872。通过对关中地区农业粮食生产变化的影响因素分析,可以为政府部门提出数据支撑和相关性的建议。 相似文献
18.
YU-LONG XIE JI-HONG WANG YI-ZENG LIANG LI-XIAN SUN XIN-HUA SONG RU-QIN YU Department of Chemistry Chemical Engineering Hunan University Changsh People''s Republic of China 《地理学报(英文版)》1993,(6)
Principal component analysis (PCA) is a widely used technique in chemometrics.The classical PCAmethod is,unfortunately,non-robust,since the variance is adopted as the objective function.In thispaper,projection pursuit (PP) is used to carry out PCA with a criterion which is more robust than thevariance.In addition,the generalized simulated annealing (GSA) algorithm is introduced as anoptimization procedure in the process of PP calculation to guarantee the global optimum.The resultsfor simulated data sets show that PCA via PP is resistant to the deviation of the error distribution fromthe normal one.The method is especially recommended for use in cases with possible outlier(s) existingin the data. 相似文献
19.
N. J. Anderson 《Journal of Paleolimnology》1990,4(1):43-59
The variability of diatom distribution in an acidified, upland wind-stressed lake (Loch Fleet, Galloway, S. W. Scotland) was assessed by analysis of 28 surface sediment samples and 11 cores. Correspondence analysis (CA) and cluster analysis were used to illustrate the variability of the surface sediment and core samples. There was reasonable uniformity of taxa in most of the surface sediment samples, although 7 samples, as indicated by both CA and cluster analyses were atypical. Most cores recorded clearly the acidification of the lake, although percentages of individual taxa varied up to 20% between cores. Two cores had old, preacidification diatom assemblages (of indeterminate age) close to the sediment surface. These old sediments were probably the source of the re-worked diatoms found in the atypical surface sediment assemblages. Diatom trends, as CA ordinations and pH profiles, were less variable than the surface sediment assemblages. It is argued that non-uniform sediment accumulation rates and diatom deposition cause variability in surface sediment diatom samples. This variability may be reduced in core profiles by homogenization during further resuspension/deposition cycles and burial. Cores, and the associated time component they offer, may be useful in assessing the variability of surface sediment assemblages. 相似文献
20.
Kristian Bjarnøe Brandsegg Erik Hammer Richard Sinding-Larsen 《Natural Resources Research》2010,19(1):45-62
Multivariate analysis is employed to investigate the structure of variations within highly heterogeneous data. Traditionally,
principal component analysis (PCA) is run by analyzing the entire wireline log and using PCA scores to characterize variability
within and between lithologies. In this paper, we propose a technique using only specific subsets of all well records to quantify
reservoir heterogeneity due to second order lithological variability. These subsets are chosen from uniform lithofacies parts
of the wireline log in order to reduce the variability in the correlation matrix that otherwise would cause lithological changes.
The purpose is to assess the efficiency of structured PCA in analyzing small-scale heterogeneity that is captured by wireline
logs but often masked by traditional PCA approaches. This paper shows that a structured PCA procedure based upon special lithological
units is superior to an unstructured PCA, when the focus is within lithology variations. This structured procedure is applied
to data from the Heidrun field, offshore mid-Norway. The results demonstrate clear benefits from added insight into the variability
of a complex fluviodeltaic heterolithic sequence that poses great challenges to hydrocarbon development. 相似文献