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1.
Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.  相似文献   
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Hydrologists use the generalized Pareto (GP) distribution in peaks-over-threshold (POT) modelling of extremes. A model with similar uses is the two-parameter kappa (KAP) distribution. KAP has had fewer hydrological applications than GP, but some studies have shown it to merit wider use. The problem of choosing between GP and KAP arises quite often in frequency analyses. This study, by comparing some discrimination methods between these two models, aims to show which method(s) is (are) recommended. Three specific methods are considered: one uses the Anderson-Darling goodness-of-fit (GoF) statistic, another uses the ratio of maximized likelihood (closely related to the Akaike information criterion and the Bayesian information criterion), and the third employs a normality transformation followed by application of the Shapiro-Wilk statistic. We show this last method to be the most recommendable, due to its advantages with sizes typically encountered in hydrology. We apply the simulation results to some flood POT datasets.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR E. Volpi  相似文献   
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In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories.  相似文献   
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This short article evaluates the stochastic method of ground motion simulation for Bucharest area using both the single-corner frequency model and recently introduced double-corner frequency models. A dedicated Q model is derived using ground motions obtained during the largest Vrancea earthquakes from the past 30 years. The simulated ground motions are tested against the observed data from the Vrancea earthquakes of August 1986 and May 1990. Moreover, the observed data are also compared against simulations obtained using the Q model derived by Oth et al. (2008). Finally, the results of the simulations show that the derived Q model is better suited for larger magnitude events, while the Q model of Oth et al. (2008) provides better results for smaller earthquakes.  相似文献   
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以汶川地震中的都江堰地区震后遥感图像为例,研究分析了图像分割技术及模糊分类技术,在此基础上,用分类精度更高的单尺度、多特征的面向对象图像处理方法进行建筑物震害评估。重点探索了混淆矩阵在震害评估中的应用,通过Kappa统计值进行震害分类结果的比对与精度评价,并验证该分类方法的稳定性。研究结果表明:改进后的面向对象图像处理方法简单、快速且精度较高,具有良好的适用性和稳定性。  相似文献   
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One approach to model the high-frequency attenuation of spectral amplitudes of S-waves is to express the observed exponential decay in terms of Kappa (κ) factor [1]. Kappa is a significant parameter used for identifying the high-frequency attenuation behavior of ground motions as well as one of the key parameters for stochastic strong ground motion simulation method. As of now, there is not a systematic investigation of the Kappa parameter based on the recently-compiled Turkish ground motions. In this study, we examine a strong ground motion dataset from Northwestern Turkey with varying source properties, site classes and epicentral distances. We manually compute κ from the S-wave portion of each record and study both horizontal and vertical kappa values. We use traditional regression techniques to describe the (potential) relationships between kappa and selected independent variables such as the site class, distance from the source or magnitude of the event. A linear effect of magnitude on kappa is not found statistically significant for the database studied herein. We express the initial findings of a regional κ model for Northwestern Turkey as a function of site class and epicentral distances. Single station analyses at selected sites confirm the regional model. Finally, we present stochastic strong motion simulations of past events in the region using the proposed kappa model. Regardless of the magnitude, source-to-site distance and local site conditions at the stations, the high-frequency spectral decay is simulated effectively at all stations considered.  相似文献   
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对ETM+影像进行多种算法融合实验,除应用ERDAS软件现有的融合方法(PCA、MLT)外,还利用IDL语言编程实现了SFIM、HPF、MB等融合算法,通过多次修改SFIM、HPF、MB融合算法中滤波器窗口的大小、滤波算子的实验,达到既不产生噪声又增强了图像纹理信息的融合效果。对融合后的影像进行了相同地物样本、不同分类方法的监督分类。以2002年内蒙古土地利用遥感调查数据为评价标准(内蒙古自治区遥感与地理信息系统重点实验室提供),用总体精度(overall accuracy)、kappa系数两种评价指数综合反映各种融合算法与各种分类方法结合的分类精度,并对各种分类方法及融合算法予以评价。  相似文献   
10.
Crustal attenuation for Jamaica, West Indies   总被引:1,自引:0,他引:1  
The S and coda wave spectra of small earthquakes on the island of Jamaica were used to determine the near surface and coda Q attenuation, kappa" align="BASELINE" BORDER="0"> and Q c,respectively. Q c determined by the single-station method was found in the range of 1 to 10 Hertz to be given by the relationship, Q c= 60 ± 5f 0.87±0.05. This suggests that the Jamaican crust is highly attenuating which is further supported by the observation of rapid intensity fall-off with distance for earthquakes that have affected the island in the past. kappa" align="BASELINE" BORDER="0">, determined from S-wave spectra with short travel times was found to be 0.058 ± 0.012 on the central crustal block, which makes up nearly two-thirds of the island, and 0.080 ± 0.014 in surrounding belt sub-regions. The pattern of kappa" align="BASELINE" BORDER="0"> values seems to fit with the surface geology in that the central block has areas of exposed outcrops of older and harder rock than the belts, which are characterized by thicker sedimentary sequences as well as intense fracturing and faulting.Atkinson and Boore (1998) and Atkinson(2001) presented an alternative method to stochastic modelling for ground motion in Eastern North America, whereby California attenuation relationships were modified to account for crustal differences invelocity-depth profile, Q and kappa" align="BASELINE" BORDER="0"> between both regions. Following their example, the California spectral attenuation relation of Boore, Joyner and Fumal (1997) was modified to account for differences between the California and Jamaica crust, resulting in an attenuation relation that is deemed to be more appropriate for Jamaica. Spectral accelerations for Jamaica when compared to California, are especially reduced beyond 20 km from the source and at high frequencies, f 1 hertz.The study concludes that the Jamaican crust, although having an oceanic composition is highly attenuating, which may be a result of intensive tectonic processes, whereas kappa" align="BASELINE" BORDER="0"> is consistent with near-rock conditions on the central block and soft rock conditions elsewhere on the island.  相似文献   
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