Abrupt uplift of Tibetan Plateau a t the end of early Pleistocene and Australasian impact event

The latest sharp uplift of the Tibetan Plateau and adjacent mountains occurred at the end of the early Pleistocene. The uplift of the Plateau resulted from Late Mesozoic－Cenozoic comp ressional structure due to the subduction of the Indian Plate beneath the Asian continent. This event definitively effected the formation of basin-mountain relief, Cenozoic basin deformation, large scale aridity and desertification of western China. The Australasian meteorites impact event happened ca. 0.8 Ma ago, located in the triangle area of the Indian Ocean ridge (20°S/67°E) . The impact may have resulted in an acceleration of speeding of the Indian Ocean ridge pushing the Indian Plate to subduct rapidly northward. Thus, the impact event can give reasonable explanation for the dynamic background of the latest rapid uplift of the Tibetan Plateau and the continental deformation of western China and even of the Middle Asia.     

平原地区高潜水位采煤塌陷综合治理研究——以兖州煤田为例

煤炭资源的开采引发了采煤塌陷、农田损毁、生态破坏、农民失地等后果,给矿区带来了一系列经济、社会、环境问题。该文以兖州煤田为例,对平原地区高潜水位条件下煤炭开采引起的地表塌陷现状进行调查,充分掌握了塌陷区土地利用现状、塌陷区稳沉状况及破坏现状。分析了兖州煤田采煤塌陷区的土地损毁特点,研究了塌陷区综合治理的手段和方法,针对性地提出了高潜水位地区采煤塌陷综合治理的途径,为采煤塌陷区的规划治理提供了参考。     

基于局部回波幅值统计的海杂波背景下小目标检测

针对传统舰载雷达和岸基雷达很难检测出海杂波背景下小目标的现状,提出一种基于局部回波幅值统计的方法来检测海杂波背景下小目标.该算法基于数学统计思想:计算不同距离单元海杂波的幅值的最大值和标准偏差,分析发现距离单元含有小目标回波的最大幅值明显小于其它距离单元只含有海杂波回波的最大幅值,距离单元含有小目标回波的幅值的标准偏差明显大于距离单元只含有海杂波回波的幅值的标准偏差,因此可以在对小目标没有任何先验知识条件下,较准确地检测出海杂波背景下的小目标.实验证明,该算法是有效的.     

Precise, automatic and fast method for vanishing point detection

A new automated approach for vanishing point detection in images of urban scenes is described. This method is based on the theorem of Thales. The main contribution of this paper is the automatic and simultaneous detection of all vanishing points of the image, achieved by converting this problem into the detection of circles in a complex cloud of points, in which each point corresponds to a segment and is associated with an uncertainty. This extraction of circles uses a RANSAC method, modified to improve its speed by using accumulation techniques (Hough transform or otherwise). This robust estimation is then refined by least squares error propagation using the individual variances of each segment. The algorithm is robust, its accuracy is optimised and it is entirely automatic. Its successful operation has been tested on a large number of images of varied urban scenes.     

On the use of iterative re-weighting least-squares and outlier detection for empirically modelling rates of vertical displacement

The proper identification and removal of outliers in the combination of rates of vertical displacements derived from GPS, tide gauges/satellite altimetry, and GRACE observations is presented. Outlier detection is a necessary pre-screening procedure in order to ensure reliable estimates of stochastic properties of the observations in the combined least-squares adjustment (via rescaling of covariance matrices) and to ensure that the final vertical motion model is not corrupted and/or distorted by erroneous data. Results from this study indicate that typical data snooping methods are inadequate in dealing with these heterogeneous data sets and their stochastic properties. Using simulated vertical displacement rates, it is demonstrated that a large variety of outliers (random scattered and adjacent, as well as jointly influential) can be dealt with if an iterative re-weighting least-squares adjustment is combined with a robust median estimator. Moreover, robust estimators are efficient in areas weakly constrained by the data, where even high quality observations may appear to be erroneous if their estimates are largely influenced by outliers. Four combined models for the vertical motion in the region of the Great Lakes are presented. The computed vertical displacements vary between  − 2 mm/year (subsidence) along the southern shores and 3 mm/year (uplift) along the northern shores. The derived models provide reliable empirical constraints and error bounds for postglacial rebound models in the region.     

面向应用的CBERS-02星高分辨率相机成像数值模拟技术框架

技术框架研究的目标是准确仿真卫星高分辨率相机成像过程中辐射和几何质量的下降情况,从应用方的角度建立评价高分辨率卫星相机在国土资源领域的应用潜力和技术框架,并以CBERS-02B星HR相机在轨成像模拟为例进行了原理验证,同时对今后以国土资源应用评价为目标的高分辨率相机在轨成像模拟改进方案提出了建议。     

高分辨率遥感影像在云南澜沧老厂矿床地质研究中的应用

在云南澜沧老厂矿床地质研究中,高分辨率QuickBird 影像提供了丰富的地质异常信息:影像线-环结构反映出矿床的控矿环形构造及隐伏构造信息;影像色调异常斑块显示了地面围岩蚀变区域;遥感异常与物化探异常的高度吻合,为地质构造分析和成矿预测提供了有用信息和佐证.     

改进的P-SVM支持向量机与遥感数据分类

本文介绍了将P-SVM算法引入多光谱/高分辨率遥感数据的分类, 并且展示了卫星ASTER和航空ADS40数字影像分类的技术过程和结果验证。结果表明：P-SVM方法的分类精度不低于SVM, 并减少了时耗。     

一种自适应匹配子空间亚像元目标探测方法

为了克服基于线性混合模型的高光谱遥感影像亚像元目标探测方法的缺陷, 提出了一种基于全限制性线性分解的自适应匹配子空间探测方法。首先利用交叉相关光谱匹配技术求得各个像元所含端元类别信息, 然后根据端元类别信息和全限制性分解的结果构造自适应匹配子空间探测算子, 利用端元类别信息在探测中动态选择端元, 降低端元数目估计偏差对探测结果的影响, 提高探测器对目标与背景的可分性。实验证明, 该方法与其他基于线性混合模型的亚像元目标探测方法相比, 可以更好地克服端元数目估计偏差对探测结果的影响, 无论是端元个数低估还是     

自适应空间邻域分析和瑞利-高斯分布的多时相遥感影像变化检测

提出了一种基于自适应空间邻域分析和瑞利-高斯模型(Rayleigh-Gauss models, RGM)分布的多时相遥感影像自动变化检测方法。该方法把自适应空间邻域信息和改进的差值影像与比值影像乘积变换融合 法(improved multiplying transform fusion, IMTF)结合构造差异影像, 可以有效地抑制噪声和消除多时相影像之间配准误差的影响, 具有更强的鲁棒性。在对差异影像的分割处理中, 运用瑞利和高斯模型分别模拟变化类像元和非变化类像元的分布情况, 然后估计出两类像元的概率