Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods

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.     

Detection of station coordinate discontinuities within the Italian GPS Fiducial Network

The Detection Identification Adaptation (DIA) procedure was applied to the coordinate time-series of some permanent GPS stations belonging to the Italian GPS Fiducial Network (IGFN), of the Italian Space Agency (ASI), to detect discontinuities and to reject outliers. The daily solutions of the stations of Cagliari, Genoa, Medicina, Noto, Turin, Perugia and Venice were computed for the period 1997.0–2003.0 using Bernese GPS software v.4.2. The data were interpolated using a model with a linear term and an annual periodic term. The parameters were estimated by least squares. The DIA procedure was organized to automatically detect discontinuities and outliers. Approximately, 70% of the discontinuities present in the coordinate time-series were identified and their magnitudes were estimated. The identified discontinuities are basically caused by equipment replacement and reference frame changes, but in a few cases the reason is still unknown. With regard to the outliers, roughly 6% of the data were rejected. These data were considered outliers on the base of the level of significance and of the power of the test adopted in this work. Except for the stations of Perugia and Venice, the estimated coordinates agree with ITRF2000 values at the 10 mm level, and the estimated velocities are within a few mm/year of the ITRF2000 values.     

利用多元地震属性预测测井特性

通过寻找井旁地震数据与测井曲线的关系,将这一关系应用到远离井的区域(只有地质数据,但无测井)来预测测井的有关特性,其方法有单属性分析和多属性分析[1]。本文通过实例描述了多属性分析的特点及预测结果。从单属性回归到多属性预测、再到神经网络预测过渡时,预测能力持续提高。同时对地震属性的选择和有效性进行了讨论,将结果应用到整个二维地震剖面上,能更好地确定井以外区域的测井特性。     

辽宁地震信息网络通讯线路的设计与实施

从辽宁省地震局信息网络建设的实际需求出发,采用层次化设计方法,将通讯线路分为三层:即区域中心、汇聚层和台站。各层之间采用2MSDH传输电路实现层间连接,通过路由器的配置来保证数据流的畅通,实现了全网互联互通。本文介绍了辽宁地震信息网络通讯线路的设计与实施过程。     

浅谈县局计算机网络维护

对单收站接收机的硬件进行升级后，可在另一台电脑上收看及录制单收站多媒体视频广播；也可在多台电脑上安装Micaps2．0；便于对地面测报网络的维护；电脑系统的维护。     

动量BP算法在路基沉降预测中的应用

提出一种采用动量BP算法来预测路基沉降的方法,结合具体的工程实例,构建了预测路基沉降的具体BP神经网络模型。预测结果表明,该模型有较高的预测精度,可作为预测路基沉降的一种新方法。     

基于抽水试验的土体渗透性耦合响应模型研究

土体中大量降排水的过程实际上是土体中有效应力增长的过程。通过对抽水试验中土体渗透系数的回归分析,建立了渗透系数与有效应力增量之间的耦合响应模型关系,说明降排水过程中土体渗透系数是呈非线性变化的。     

A Network Model for Dispersion of Communicable Diseases

The spread of communicable diseases through a population is an intrinsic spatial and temporal process. This paper presents an individual‐based analytical framework for modeling the spatial and temporal heterogeneity in the disease transmission. The framework specifies a network model structure and six associated parameters. These parameters describe the properties of nodes, the properties of links, and the topology of the network. Through this model structure and associated parameters, this framework allows the representation of discrete individuals, individualized interactions, and interaction patterns in a network of human contact. The explicit representation of the spatial distribution and mobility of individuals in particular facilitates the modeling of spatial heterogeneity in the disease transmission.     

Small-world characteristics on transportation networks: a perspective from network autocorrelation

Studies on small-world networks have received intensive interdisciplinary attention during the past several years. It is well-known among researchers that a small-world network is often characterized by high connectivity and clustering, but so far there exist few effective approaches to evaluate small-world properties, especially for spatial networks. This paper proposes a method to examine the small-world properties of spatial networks from the perspective of network autocorrelation. Two network autocorrelation statistics, Moran’s I and Getis–Ord’s G, are used to monitor the structural properties of networks in a process of “rewiring” networks from a regular to a random network. We discovered that Moran’s I and Getis–Ord’s G tend to converge and have relatively low values when properties of small-world networks emerge. Three transportation networks at the national, metropolitan, and intra-city levels are analyzed using this approach. It is found that spatial networks at these three scales possess small-world properties when the correlation lag distances reach certain thresholds, implying that the manifestation of small-world phenomena result from the interplay between the network structure and the dynamics taking place on the network.      

苏通大桥钢箱梁制造几何控制三维高精度基准网测设

本文详细介绍了对苏通大桥主桥钢箱梁制造几何控制三维高精度基准网的测设，通过实际工程的实施对高精度三维基准网的方案设计和精度控制进行了有效的探索。