多源遥感影像误匹配点剔除的粗糙模糊C-均值方法

简要概述了遥感影像匹配中,误匹配点剔除的常用方法.对SIFT特征描述子生成及其匹配、粗糙模糊C-均值方法聚类分析的原理方法进行了详细论述.针对SIFT方法匹配出的大量点对,将不同时相,不同传感器、不同分辨率影像广义划分为同分辨率和不同分辨率.基于同分辨率影像匹配点对问连线具有相同的距离及斜率、不同分辨率影像匹配点对间连线的延长线交于一点的几何约束条件,利用粗糙模糊C-均值模型聚类分析方法对点对快速剔除误匹配点后,对剔除的结果利用最小二乘方法进行精匹配,结果达到亚像素.最后,通过对不同时相、不同分辨率、不同传感器的多源遥感影像实验分析验证了该方法的适用性、可靠性及精确性.     

Investigating the propagation mechanism of unmodelled systematic errors on coordinate time series estimated using least squares

The propagation of unmodelled systematic errors into coordinate time series computed using least squares is investigated, to improve the understanding of unexplained signals and apparent noise in geodetic (especially GPS) coordinate time series. Such coordinate time series are invariably based on a functional model linearised using only zero and first-order terms of a (Taylor) series expansion about the approximate coordinates of the unknown point. The effect of such truncation errors is investigated through the derivation of a generalised systematic error model for the simple case of range observations from a single known reference point to a point which is assumed to be at rest by the least squares model but is in fact in motion. The systematic error function for a one pseudo-satellite two-dimensional case, designed to be as simple but as analogous to GPS positioning as possible, is quantified. It is shown that the combination of a moving reference point and unmodelled periodic displacement at the unknown point of interest, due to ocean tide loading, for example, results in an output coordinate time series containing many periodic terms when only zero and first-order expansion terms are used in the linearisation of the functional model. The amplitude, phase and period of these terms is dependent on the input amplitude, the locations of the unknown point and reference point, and the period of the reference point's motion. The dominant output signals that arise due to truncation errors match those found in coordinate time series obtained from both simulated data and real three-dimensional GPS data.     

GPS网数据处理几个问题

本文指出在GPS网平差中有关精度评定、权的确定以及坐标转换所产生的控制点间隙等存在问题，供研究讨论。     

长白山天池火山区长白-敦化剖面结晶基底的探测和研究

时间项分析法中，应用广义最小二乘法进行反演，对长白山天池火山区岩浆系统的长白—敦化(L1)剖面的Pg波到时进行了计算处理，得到了Pg波时间项及基底速度值；取上部地壳的介质平均速度为4．5km/s，经反演求得了各点的深度值，给出了长白山天池火山区结晶基底的厚度分布。结晶基底厚度一般在2．0km左右，而在长白山天池下方结晶基底最厚处接近4．0km；在万宝和敦化附近各有一不太明显的凹陷，其原因可能与在这两个位置处有几条断裂穿过有关。     

研究气温变化趋势的新方法——三组耐抗线

针对气象资料难以满足高斯分布的情况,引进了具有耐抗性的三组耐抗线方法,分析了满足不同信度情况下最小二乘回归和三组耐抗线的差异,并用西藏近30 a气温资料进行了检验。结果表明三组耐抗线方法比最小二乘法研究气候变化趋势有明显优势;采用最小二乘法得到的西藏气候变暖估计偏高。     

地震预警现地PGV连续预测的最小二乘支持向量机模型

为提升现地仪器地震烈度预测的准确性与连续性,研究面向地震预警的PGV连续预测模型.以中国仪器地震烈度标准的计算参数:0.1～10 Hz带通滤波三分向矢量合成速度峰值PGV为预测目标,利用日本K-net与KiK-net台网P波触发后1?10 s强震数据,基于人工智能中的机器学习方法-最小二乘支持向量机,选取7种特征参数作...     

Mapping of moraine dammed glacial lakes and assessment of their areal changes in the central and eastern Himalayas using satellite data

The relatively rapid recession of glaciers in the Himalayas and formation of moraine dammed glacial lakes(MDGLs) in the recent past have increased the risk of glacier lake outburst floods(GLOF) in the countries of Nepal and Bhutan and in the mountainous territory of Sikkim in India. As a product of climate change and global warming, such a risk has not only raised the level of threats to the habitation and infrastructure of the region, but has also contributed to the worsening of the balance of the unique ecosystem that exists in this domain that sustains several of the highest mountain peaks of the world. This study attempts to present an up to date mapping of the MDGLs in the central and eastern Himalayan regions using remote sensing data, with an objective to analyse their surface area variations with time from 1990 through 2015, disaggregated over six episodes. The study also includes the evaluation for susceptibility of MDGLs to GLOF with the least criteria decision analysis(LCDA). Forty two major MDGLs, each having a lake surface area greater than 0.2 km2, that were identified in the Himalayan ranges of Nepal, Bhutan, and Sikkim, have been categorized according to their surface area expansion rates in space and time. The lakes have been identified as located within the elevation range of 3800 m and6800 m above mean sea level(a msl). With a total surface area of 37.9 km2, these MDGLs as a whole were observed to have expanded by an astonishing 43.6% in area over the 25 year period of this study. A factor is introduced to numerically sort the lakes in terms of their relative yearly expansion rates, based on their interpretation of their surface area extents from satellite imageries. Verification of predicted GLOF events in the past using this factor with the limited field data as reported in literature indicates that the present analysis may be considered a sufficiently reliable and rapid technique for assessing the potential bursting susceptibility of the MDGLs. The analysis also indicates that, as of now, there are eight MDGLs in the region which appear to be in highly vulnerable states and have high chances in causing potential GLOF events anytime in the recent future.     

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Non-stationary covariance function modelling in 2D least-squares collocation

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non- stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.     

全站仪水域面积测量及其精度分析

水域面积测量的特殊性,决定了采用传统的面积测量方法很难实时地得到水域的覆盖面积。全站仪提供的面积测量功能很好地弥补了这个缺憾并能够提供较高的成果精度。阐述了全站仪面积测量的原理与方法,对全站仪水域面积测量中误差的计算公式进行了讨论,并分析了水域面积的测量精度,得出了几点有益的结论。