Integrating a fuzzy <Emphasis Type="Italic">k</Emphasis>-means classification and a Bayesian approach for spatial prediction of landslide hazard     

Pece V.?GorsevskiEmail author  Paul E.?Gessler  Piotr?Jankowski 《Journal of Geographical Systems》2003,5(3):223-251

A robust method for spatial prediction of landslide hazard in roaded and roadless areas of forest is described. The method is based on assigning digital terrain attributes into continuous landform classes. The continuous landform classification is achieved by applying a fuzzy k-means approach to a watershed scale area before the classification is extrapolated to a broader region. The extrapolated fuzzy landform classes and datasets of road-related and non road-related landslides are then combined in a geographic information system (GIS) for the exploration of predictive correlations and model development. In particular, a Bayesian probabilistic modeling approach is illustrated using a case study of the Clearwater National Forest (CNF) in central Idaho, which experienced significant and widespread landslide events in recent years. The computed landslide hazard potential is presented on probabilistic maps for roaded and roadless areas. The maps can be used as a decision support tool in forest planning involving the maintenance, obliteration or development of new forest roads in steep mountainous terrain.  相似文献   

Using Bayesian belief networks to analyse the stochastic dependence between interevent time and size of earthquakes     

C. Agostinelli  R. Rotondi 《Journal of Seismology》2003,7(3):281-299

The purpose of this article is to show how Bayesian belief networks can beused in analysis of the sequence of the earthquakes which have occurred in a region, to study the interaction among the variables characterizing eachevent. These relationships can be represented by means of graphs consistingof vertices and edges; the vertices correspond to random variables, whilethe edges express properties of conditional independence. We have examinedItalian seismicity as reported in two data bases, the NT4.1.1 catalogue and the ZS.4 zonation, and taken into account three variables: the size of thequake, the time elapsed since the previous event, and the time before the subsequent one. Assigning different independence relationships among these variables, first two couples of bivariate models, and then eight trivariatemodels have been defined. After presenting the main elements constituting a Bayesian belief network, we introduce the principal methodological aspects concerning estimation and model comparison. Following a fully Bayesian approach, prior distributions are assigned on both parameters and structuresby combining domain knowledge and available information on homogeneous seismogenic zones. Two case studies are used to illustrate in detail the procedure followed to evaluate the fitting of each model to the data sets andcompare the performance of alternative models. All eighty Italian seismogenic zones have been analysed in the same way; the results obtained are reportedbriefly. We also show how to account for model uncertainty in predicting a quantity of interest, such as the time of the next event.  相似文献   

The optimum Bayesian probability procedure and the prediction of strong earthquakes felt in Mexico city     

Sergio G. Ferraes 《Pure and Applied Geophysics》1988,127(4):561-571

Bayes' theorem has possible application to earthquake prediction because it can be used to represent the dependence of the inter-arrival time (T) of thenext event on magnitude (M) of thepreceding earthquake (Ferraes, 1975;Bufe et al., 1977;Shimazaki andNakata, 1980;Sykes andQuittmeyer, 1981). First, we derive the basic formulas, assuming that the earthquake process behaves as a Poisson process. Under this assumption the likelihood probabilities are determined by the Poisson distribution (Ferraes, 1985) after which we introduce the conjugate family of Gamma prior distributions. Finally, to maximize the posterior Bayesian probabilityP(/M) we use calculus and introduce the analytical condition .Subsequently we estimate the occurrence of the next future large earthquake to be felt in Mexico City. Given the probabilistic model, the prediction is obtained from the data set that include all events withM7.5 felt in Mexico City from 1900 to 1985. These earthquakes occur in the Middle-America trench, along Mexico, but are felt in Mexico City. To see the full significance of the analysis, we give the result using two models: (1) The Poisson-Gamma, and (2) The Poisson-Exponential (a special case of the Gamma).Using the Poisson-Gamma model, the next expected event will occur in the next time interval =2.564 years from the last event (occurred on September 19, 1985) or equivalently, the expected event will occur approximately in April, 1988.Using the Poisson-Exponential model, the next expected damaging earthquake will occur in the next time interval =2.381 years from the last event, or equivalently in January, 1988.It should be noted that very strong agreement exists between the two predicted occurrence times, using both models.  相似文献   

概率方法应用于地震短期预测的探索   总被引：6，自引：1，他引：5  

张天中  王林瑛  刘庆芳  丁秋琴 《地震》1999,19(2):135-141

根据爆发地震平静两项活动性前兆的统计结果,对地震发生的背景概率、条件概率和概率增益进行了估计,给和北地震发生前发震概率逐步增加时间过程,由背景概率Ｐ（Ｅ）增至中期前兆Ａ出现后的条件概率Ｐ（Ｅ／Ａ）,再增至短期前铛Ｂ（平静）出现后的联合条件概率Ｐ（Ｅ／Ａ）。结果表明,在１９９７年１２月１７日后的一个月内,华北地区发生６级以上的条件这３８％,概率增益超过２０,对概率预测结果的使用进行了探讨,提出应充分  相似文献   

Numerical Taxonomy and Bayes Discriminant Analysis on 42 Fossil Species in Dicksoniaceae from China     

XIN Cunlin  WANG Jingjing  WANG Luhan  ZHANG Yamei 《《地质学报》英文版》2019,93(1):183-198

As the basal group of Polypodiales, the specific taxonomy of Dicksoniaceae is still being debated. As aquantitative analysis method, numerical taxonomy has been applied to the taxonomic study of many plant families andgenera in recent years due to its simplicity and high accuracy. However, the numerical analysis of the Dicksoniaceae fossilshas not been reported at present. In the present study, the pinnule morphological data of 42 Mesozoic fossil species of theDicksoniaceae were analyzed using cluster analysis, principal component analysis and correlation analysis. The resultsrevealed that 42 taxonomic units could be divided into six representative groups, which are consistent with the traditionaltaxonomy. After screening, an identification key on 28 fossil species of four genera with a definite taxonomic position wasestablished. According to the quantitative analysis, a Bayes discriminant model was established for the selected species.Lastly, the model was tested using the morphological data of the fossil pinnules in Dicksoniaceae from the YaojieFormation, suggesting that the discriminant model is accurate to a certain extent. As a result, the numerical taxonomy canbe applied to the classification of the Dicksoniaceae fossils.  相似文献   

无人车平台激光点云中线特征提取   总被引：1，自引：0，他引：1  

蔡斌斌  李必军 《测绘通报》2019,(2):32-38

随着无人平台的应用越来越广泛，由激光点云提取线特征构建高精度特征地图已成为研究的重点。本文基于深度图像中的二维线特征，提出了一种新的几何模型对其进行优化，得到准确的三维线特征，并使用贝叶斯滤波对多帧结果进行融合，提高了三维再线特征的精度和准确率。  相似文献   

CX-6(02)微纳卫星超分辨率成像   总被引：1，自引：0，他引：1  

谭政  相里斌  吕群波  孙建颖  李平付  高爽  尹增山 《遥感学报》2019,23(2):196-204

面向微纳卫星高分辨率对地遥感,将超分辨率成像应用于中国整星60公斤级的CX-6(02)微纳卫星设计中,解决因体积和重量限制导致传统长焦距、大口径成像载荷无法应用于微纳卫星的问题。图像获取上,采用高帧频面阵CMOS探测器对同一地物目标多次曝光的方式,利用卫星姿态控制偏差和地速补偿来获得多帧具有亚像元位移的图像;超分辨率重建算法上,在变分贝叶斯框架下提出加权双向差分模型,提高先验概率模型的方向约束性,削弱观测方程求解的病态性。CX-6(02)星成像数据实验结果表明,本文的图像采样方法可获得较为充分的亚像元信息;相比传统的L1范数先验和全变分先验的变分贝叶斯超分辨算法重建结果,本文重建结果对反卷积运算导致的噪声放大具有更好的抑制作用,可获得两倍分辨率提升,有效提高数据质量和应用价值。  相似文献   

GIS-based sustainable city compactness assessment using integration of MCDM,Bayes theorem and RADAR technology   总被引：1，自引：0，他引：1  

Saleh Abdullahi  Mustafa Neamah Jebur 《国际地球制图》2015,30(4):365-387

In recent decades, compact urban development and smart cities are recognised as most sustainable urban form in an effort to protect natural environment. Therefore, evaluation of existing compactness and sustainability of an area is an essential task before the real development takes place. In the literature, it is possible to see some studies on city’s compactness assessment and most of them have considered only a few aspects of compact development analysis. This paper aims to analyse urban sustainability of Kajang city (Malaysia) through a comprehensive city compactness assessment using geographical information system and radar remote sensing technology. To measure building density, a RADAR image of the study area was used to extract built-up areas with the aid of pixel-based and object-based classification schemes. Mixed land use development, urban density and intensity were the main indicators of the analysis. Finally, multicriteria decision-making and Bayes theorems were applied for overall compactness assessment. Building density analysis was validated using standard confusion matrix, which showed more than 90% accuracy. Similarly, the root-mean squared error showed 0.35 for object-based classification. The results classified the zones of the Kajang city in the range of least to most compact zones with the compactness value of 0.00273–0.0146, respectively. The results obtained in this study can help local government to improve the compactness of least compact zones to make Kajang city more sustainable. Furthermore, the results revealed that efficient public transportation and proper community facilities are the key factors to achieve sustainable urban development.  相似文献   

基于GIS的Bayes统计推断技术在区域斜坡稳定性评价中的应用   总被引：1，自引：1，他引：0  

李雪平  唐辉明 《地质科技情报》2005,24(3):85-88

为探讨Bayes理论在区域斜坡稳定性评价中的应用,将巫山县城新址西区作为研究区,综合应用GIS技术和多元统计技术建立了区域斜坡稳定性分析的2个Logistic多元回归模型,即趋势表面模型和因子模型.趋势表面模型的自变量是位置坐标,因子模型的自变量是影响斜坡稳定的因子,包括地形坡度、高程、坡向、岩性、坡形、距有影响构造线的距离.将趋势表面模型结果作为Bayes模型中的先验信息,将因子模型结果作为Bayes模型中的样本信息,通过Bayes基本原理,得到Bayes综合模型.结果表明,在研究区内,因子模型的拟合度为80.33%,Bayes模型的拟合度为80.61%,后者得出的滑坡发生样本的判对率比前者提高了约7%,说明Bayes模型可用于区域斜坡稳定性概率评价.  相似文献   

应用贝叶斯动态模型的地基沉降概率分析与预测   总被引：1，自引：0，他引：1  

魏冠军  党亚民  章传银 《测绘科学》2012,37(2):52-53,90

考虑到地基沉降预测模型中参数的时变特性及预测结果的可靠性,本文提出地基沉降概率预测方法:运用贝叶斯动态模型建立地基沉降过程的状态方程和观测方程,利用参数先验信息并结合含有噪声的前期沉降观测数据,对沉降状态参数进行Bayes后验概率推断,通过不断的"概率预测-修正"递推运算,获得最优沉降状态概率估计来预测地基沉降量。数值实例结果表明,与其他预测方法相比较,本文的方法是可行有效的。  相似文献