南极国际GPS跟踪站的海潮位移改正

This paper describes the ocean loading tides corrections of GPS stations in Antarctica, such as the Great Wall station and Zhongshan station. Based on the theory of ocean loading tides, the displacement corrections of ocean loading tides on GPS stations in Antarctica are calculated by using the CRS4.0 ocean loading tides model. These corrections are also applied to GPS data processing. The GPS data are analyzed by the GAMIT software with and without these corrections. We compared and analyzed the GPS baseline components to get the differences. The results show that the ocean tidal displacement corrections have obvious effects upon GPS baseline components. Therefore, we should not ignore the ocean loading tides corrections of GPS stations in Antarctica to obtain precise and reliable results.     

北京市地铁暗挖施工沉降控制探讨

仅以北京市地铁4#线张自忠车站主体暗挖施工的沉降监控项目为研究背景,对穿越城市主干道的车站结构暗挖施工进行连续性的沉降变形监测;从地下构筑物暗挖施工的工序变化与地表沉降的关系进行试验研究.在预测基础上对获取的数据进行多层次的统计与分析,以研究其变形规律与稳定性,实现了信息化施工.     

利用GPS组合观测值探测与修复周跳算法实现

本文在目前常用的周跳探测和修复方法的基础上,根据相位减伪距组合,Melbourne-Wübbena组合,电离层残差组合三种GPS组合观测值优缺点互补,将这三种组合观测值有机结合产生可靠的探测与修复周跳算法并用程序实现,通过实例分析证明此算法能够探测和修复任意大小的周跳。     

广阔范围内GPS网坐标系统转换模型的建立及精度分析

全球定位系统(GPS)技术己经在许多领域得到广泛的应用,由于GPS定位得到的观测成果通常是世界大地坐标系统WGS-84中的坐标或坐标差,但在实际应用中上需要的往往是地面点在国家坐标系或地方独立坐标系中的坐标.确立坐标系统转换模型并分析此模型的精度,根据至少3个公共点的两套大地坐标利用最小二乘法原理求出转换参数.本文以W...     

星载激光雷达气溶胶数据辅助的近岸浑浊水体大气校正研究

提出了一种星载激光雷达CALIOP气溶胶数据辅助的MODIS/Aqua水色数据大气校正方法,并在长江口及其邻近浑浊水体区域进行了实验。通过与实测光谱数据的对比分析说明,本文方法能在一定程度上避免如近红外波段离水辐亮度为零的假设的不合理性,摆脱对实测数据的依赖,有效地反演离水辐亮度,修复SeaDAS软件中短波红外-近红外联合大气校正算法中短波红外波段引起的产品的条带问题。     

Normalized algorithm for mapping and dating forest disturbances and regrowth for the United States

Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that can be used as a surrogate for major clear-cut/fire disturbance information has recently been recognized as an important input to forest carbon cycle models for improving prediction accuracy. In this study, forest disturbances in the USA for the period of ∼1990–2000 were mapped using 400+ pairs of re-sampled Landsat TM/ETM scenes in 500m resolution, which were provided by the Landsat Ecosystem Disturbance Adaptive Processing System project. The detected disturbances were then separated into two five-year age groups, facilitated by Forest Inventory and Analysis (FIA) data, which was used to calculate the area of forest regeneration for each county in the USA.     

基于规则格网数据断面极值法的一种改进方法

在研究基于规则格网数据地形特征提取过程中,主要有断面极值法和流水模拟法.在断面极值法中,针对传统断面极值法生成的特征线存在零碎、并行交叉等缺点,我们改进了传统的局部断面极值法,在特征线连接过程中增加了“将特征点邻域内其它候选特征点设置为已被引用、根据特征线长度与范围阈值筛选特征线“等条件,以克服生成的特征线存在的零碎和并行交叉问题.     

基于SRTM-DEM的阿尔泰山构造地貌特征分析

基于美国SRTM-DEM数据，利用彩色晕染、密度分割与GIS空间统计分析等技术，并结合地质资料，通过地形高程、地表坡度 及地形剖面等分析手段，对阿尔泰山的构造地貌特征进行初步分析。研究表明，阿尔泰山脉平均海拔约1 790 m，平均坡度约21° ，其高海拔与高坡度的现代地貌特征，主要与强烈的断裂构造活动有关； 山脉严格受到以北西向为主的断裂构造活动的影响与控 制，其发育的构造地貌单元基本上呈北西走向特征； 山脉阶梯状地貌特征明显，共发育5级剥夷面，不同级剥夷面所处的海拔不一 样，同级剥夷面具有东北侧高于西南侧，山脉东、中段高于西段的特点。     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.     

运用人工鱼群算法的3D扫描碎片重建探究

针对传统三维碎片拼接匹配过程中依赖单一特征及存在误差累积的问题,提出了一种运用鱼群算法的全局最优匹配方法。该方法先对碎片点云数据进行多特征提取,结合纹理、专家经验信息对混合在一起的多种类型碎片进行粗糙集分类,之后采用鱼群算法的最优解求得最佳匹配方案。实例验证所提全局匹配方法具有能力强、与初始位置无关及较强的稳健性等特点,为三维碎片的全局匹配提供了一种有效的解决方案。