GIS数据辅助下的线状目标自动提取

首先介绍了遥感影像中线状目标骨架自动提取的意义和研究现状，然后结合老的GIS数据，提出了一种算法来实现遥感影像中线状目标骨架的自动提取，算法主要包括影像预处理、GIS数据与影像的配准、骨架跟踪、编组连接与数据简化等步骤。最后又利用遥感影像和相应的GIS数据进行了实验，实验证明了算法的可行性和有效性。     

应用高光谱遥感数据估算土壤表层水分的研究

土壤水分是土壤的重要组成部分，它在陆地表层和大气之间的物质和能量交换方面扮演着重要角色，寻求快速而准确的方法估算土壤水分具有重要意义。通常，从可见光一近红外对土壤表层水分的估计多是建立在土壤水分与反射率的关系之上的。而在土壤水分含量不高时，土壤水分的增加使土壤光谱反射率在整个波长范围内降低，尤其在760nm，970nm，1190nm，1450nm，1940nm和2950nm等水分吸收波段，而在土壤水分含量较高时，土壤水分的增加会使土壤光谱反射率在某些光谱波段升高。而土壤水分的估计往往是基于土壤水分与土壤水分吸收波段的吸收强度之间的线性关系上，虽然这些经验的方法对于估算某些土壤的表层水分含量是有效的，但这些关系应用于其它条件(如不同种类土壤、土壤湿度变化范围很大的情况)时却面临很多困难，这与土壤的光谱反射率是由土壤的组成成分(土壤水分、有机质、氧化铁和粘土矿物等)的含量和它们在土壤中的分布密切相关。微分技术处理“连续”的光谱是遥感中常用的数学方法，微分技术能部分消除低频光谱成分的影响。现在微分光谱已广泛地应用于研究植被的生物物理参数、矿物和有机质等。然而利用微分光谱对土壤水分反演的研究却鲜见报道。本文通过对实验室中多种不同类型的土壤进行光谱与土壤表层水分含量进行观测，探讨了通过土壤反射率与微分光谱对土壤表层水分的反演方法。4种类型的土壤光谱数据(反射率(R)，反射率倒数的对数(log(1／R))，反射率的一阶微分光谱(dR／dλ)，反射率倒数的对数的一阶微分光谱(d(log(1／R))／dλ))与土壤表层水分之间的关系在本文中得到分析，R与log(1／R)对于不同土壤类型与土壤表层水分都很敏感，说明通过R与log(1／R)反演土壤表层水分受土壤类型的影响很大，而dR／dλ，d(log(1／R))／dλ)对土壤类型却不敏感，对土壤表层水分较为敏感，说明dR／dλ和d(log(1／R))／dλ)对于反演不同类型土壤具有很大的潜力，微分光谱与土壤水分在某些波段具有显著的相关性。通过随机对9种土壤(各具有4个土壤水分)的数据建立反演土壤水分的模型，并其他9种土壤(各具有4个土壤水分)的数据进行验证模型，结果表明，dR／dλ和d(log(1／R))／dλ)能够显著提高R与log(1／R)对于不同土壤类型土壤表层水分的反演精度，由于吸收过程是非线性的，在四种类型的土壤光谱数据中，总体来说，d(log(1／R))／dλ)具有最好的能力预测不同类型土壤的表层水分含量。     

基于典型相关分析的变化检测中变化阈值的确定

以东营市为例 ,把基于典型相关分析的方法运用于多时相遥感影像的变化检测中。对于变化阈值的确定 ,采用了一种基于贝叶斯理论的最小错误率的方法。这种方法实质上是一种非监督分类的方法 ,即不需要地面实况数据或其它先验知识 ,直接对典型相关处理后的差值图像进行分析计算得到阈值 ,使变化检测的错误率达到最小。实验结果证明了这种方法的有效性。     

利用热红外温差识别沙尘

沙尘识别是沙尘灾害监测和沙尘气溶胶特性研究的首要工作。利用辐射传输方程进行了沙尘气溶胶的辐射计算 ,对不同沙尘气溶胶光学厚度下的热红外通道温差ΔT(T11μm-T12 μm)的变化进行了分析。理论分析表明 ,利用热红外通道的温度差ΔT进行陆地沙尘识别是可行的。并利用NOAA AVHRR热红外通道的温度差ΔT进行了陆地沙尘识别的实验 ,经与地面气象站实测的沙尘天气现象相比较 ,结果一致。     

Computation of response spectra from mining tremors using neural networks

Underground coal and copper ore exploitation in two Polish mining regions causes mining tremors and a series of other negative phenomena in the environment. Although these tremors are strictly connected with human activity, they differ considerably from other paraseismic vibrations. The moment of their occurrence is not to be foreseen likewise for earthquakes. The main problem discussed in the paper was formulated as the neural network evaluation of a relation between mining tremor energies, epicentral distances and acceleration response spectra. Back-propagation neural networks with Resilient back-propagation learning method were used. Each input vector included information about the mining tremor energy and the epicentral distance. Values of acceleration response spectrum were expected as the outputs of neural networks. Neurally evaluated spectra were compared with spectra computed on the basis of experimental data. After the network is trained and tested, it can be used for mapping of new data of mining tremor energies and epicentral distances into the spectra. Then, what is the substantial advantage of neural approach, the prediction of acceleration response spectra can be performed without recording of surface vibrations. In the light of the results, it is visible that the presented way of computation of acceleration response spectra can be peculiarly applied to prognosis of mining tremors influences on structures.     

Study on comparison between absolute and relative input energy spectra and effects of ductility factor

Introduction Estimation of an attenuation relationship for strong ground motion parameters has been an interesting research subject in the field of engineering seismology and has played a very important role in seismic safety evaluation, seismic zoning, seismic hazard evaluation of major constructions, etc. At present, the generally used parameters include peak acceleration, peak velocity and elastic response spectrum. Such parameters mentioned above are essentially independent of the duration…     

Fractally Invariant Distributions and an Application in Geochemical Exploration

Fractal modelling has been applied extensively as a means of characterizing the spatial distribution of geological phenomena that display self-similarity at differing scales of measurement. A fractal distribution exists where the number of objects exhibiting values larger than a specified magnitude displays a power-law dependence on that magnitude, and where this relationship is scale-invariant. This paper shows that a number of distributions, including power-function, Pareto, log-normal and Zipf, display fractal properties under certain conditions and that this may be used as the mathematical basis for developing fractal models for data exhibiting such distributions. Population limits, derived from fractal modelling using a summation method, are compared with those derived from more conventional probability plot modelling of stream sediment geochemical data from north-eastern New South Wales. Despite some degree of subjectivity in determining the number of populations to use in the models, both the fractal and probability plot modelling have assisted in isolating anomalous observations in the geochemical data related to the occurrence of mineralisation or lithological differences between sub-catchments. Thresholds for the main background populations determined by the fractal model are similar to those established using probability plot modelling, however the summation method displays less capacity to separate out anomalous populations, especially where such populations display extensive overlap. This suggests, in the geochemical data example provided, that subtle differences in the population parameters may not significantly alter the fractal dimension.     

Detection and 2d modelling of cavities using pole–dipole array

The resistivity method is often used in cave prospecting. In this paper the pole–dipole array ability to detect cavities at different depths and with different water contents is investigated. The research was performed using analogical and numerical modelling. According to the results, empty caves at a depth less than four times its diameter can be easily detected. The ability of the pole–dipole array to detect water-filled caves reaches a minimum at filling percentages of 30–50%. Overburden effects research shows that low resistivity overburden reduces the resolution capability of the array. This study shows that equivalent results can be obtained by modelling the empty caves as infinite resistivity bodies or, alternatively, as very high resistivity ones. The analysis of field data acquired in the Maciço Calcário Estremenho (Portugal) shows the practical importance of the pole–dipole array in cavities prospecting.     

复杂条件下的地下管线探测技术

以深圳市某大道顶管施工地下管线的探测成果为例,研究了在复杂场地条件下,探测地下管线的地球物理方法和技术,着重研究了电磁感应探测法.认为在复杂条件下,对钢质煤气管,应采用电磁感应探测法;对钢质或铁质给水管,应采用直接法;对电力管和电信管,应尽量采用夹钳法;对排水(管)渠等非金属材质管线,应采用地质雷达探测的方法.