秩亏自由网平差在地铁隧道保护区中的应用

地铁隧道保护区沉降监测网中包含多个基准点,依据不同基准点平差所得结果也不相同。本文引入秩亏自由网平差方法,将所有基准点视为待定参数进行平差,并通过工程实例,验证此方法在地铁隧道保护区沉降观测中有一定的适用性。     

SHORT COMMUNICATION COMMENTS ON THE RESIDUAL BILINEARIZATION METHOD

Through theoretical analysis and computer simulation,this short communication comments on theresidual bilinearization(RBL)method and compares it with non-bilinear rank annihilation(NBRA)forthe treatment of second-order calibration with non-bilinear data.It is found that these two methods aremathematically equivalent but have different noise propagation properties.The second-order advantage,namely quantitation in the presence of unknown interferences,can be carried over to non-bilinear dataonly if there exists a net analyte rank(NAR)for the analyte of interest.     

福建港口体系结构研究

阐述了福建港湾自然条件和港口开发现状,采用赫希曼-赫芬达尔指数分析近20年来港口体系空间结构的动态演变规律,结果表明,福建港口体系空间结构演变总趋势呈分散化。这说明了港口间的竞争大于合作,职能结构趋同,因而形成合理分工与协作的福建港口群是当务之急。鉴于此,运用模糊聚类、货种区位商等分析技术,对其体系内的港口等级层次、职能结构的基本特征进行探讨,并在此基础上提出了各港口职能分工的发展方向。     

用附有条件的参数平差法求解秩亏网新探

通过引进典则参数,以较简捷的方式证明了秩亏网平差应满足的条件方程,从而用附有条件的平差方法求解秩亏网平差参数的最小二乘极小范数解。     

分形城市引力模型的一般形式和应用方法--关于城市体系空间作用的引力理论探讨

基于分形思想和城市规模-产出关系推导出城市引力模型的一般形式Iij=GijMaiiMajjR-bij,论证了参数a和b的分维性质,并将引力系数定义为Gij=G|Rij,|/(1+Sij),式中Rii为i、j两城市的相关系数,Sij为二者的相似系数,G为量纲转换系数.以长春城镇体系和郑、汴、洛点-轴系统为实例说明了模型的应用方法,并指出了城市引力数值的相对性特征.作者发现,城镇体系各要素的引力之和Fi=∑Iij,在一定时空条件下满足位序-规模法则F(k)=F1K-q(k=1,2,…,n);这也表明,借助引力计算可以揭示城市体系某些隐含的地理规律.     

基于唐宋文人足迹集聚性分析的中心文化城市变迁

中国历史文化研究一直是中国文学研究的热点,大量的研究都是基于文学作品本身或文人个体特征进行,缺乏大数据的支持;历史的发展是大量个体共同驱动的结果,文化地理中众多文人的行为潜在影响着古代文化分布和变迁。本文提出基于文人群体运动行为的位置关联和聚合的大数据分析方法,根据唐宋时期文人的移动足迹数据来论证中国历史上的文化中心城市的变迁。文化地理领域中的3次文化中心转移的观点,是基于3次历史事件驱动的定性推理分析,缺乏有效的古代文化方面的数据支撑。本文力图从数据科学、信息科学和GIS分析角度来审视这一结论。从人文领域已经出版的学术研究著作中采集唐宋时期具有代表性作家的11万条足迹数据,利用GIS的位置关联技术形成足迹图,构建了文人迁徙网络图;并采用空间化的PageRank算法计算出唐宋时期各城市的文化吸引力,直观地呈现出了不同时期文人聚集的中心城市,重塑唐宋文化中心变迁。同时,从定量、地理位置变化和时序角度剖析了中国不同时期城市的文化吸引力的分布和变化。为论证中国文化中心的南北变迁,对唐宋时期的城市文化吸引力聚合,以20年间隔来科学计算出南北文化中心的对比和演变,科学表现文化中心的南北随时间的变化,论证了中国文化中心3次南移的后2次,发现中国文化中心南移的时间早在北宋时期就已完成。     

用主成分法求解秩亏自由网的研究

结合多数平差和主成分估计理论,导出误差方程中含多重共线性关系时求解未知数的公式,并证明主成分估计的解是最小二乘最小范效解。由此,将主成分估计推广到秩亏自由网平差中,导出求解未知多数及其协因数的公式,并据主成分估计演绎出用附有条件的参数平差法求解秩亏自由网的条件方程（基准在达式）。     

Robust Kalman filter for rank deficient observation models

A robust Kalman filter is derived for rank deficient observation models. The datum for the Kalman filter is introduced at the zero epoch by the choice of a generalized inverse. The robust filter is obtained by Bayesian statistics and by applying a robust M-estimate. Outliers are not only looked for in the observations but also in the updated parameters. The ability of the robust Kalman filter to detect outliers is demonstrated by an example. Received: 8 November 1996 / Accepted: 11 February 1998     

自动建立多边形拓扑关系算法步骤的优化与改进

作者从算法和过程的效率、自动化水平和数据的完整性入手，简要分析了传统算法中存在的问题。在此基础上，以提高自动化水平为目的，将地理实体多边形拓扑关系的建立过程归结为：弧结点的匹配和弧连接关系的建立；同一结点上弧－弧拓扑关系的建立；闭合边界弧段相邻关系的建立；闭合边界包含关于的确定等主要步骤。给出了各主要步骤的算法，并对提高算法效率也提出了新的改进方案。分析与试验表明：新算法对于减少人工操作次数提高自     

Detail focused fusion of hyperspectral and multispectral imagesEI北大核心CSCD

Hyperspectral image (HSI) and multispectral image (MSI) are two types of images widely used in the field of remote sensing. These images are useful in certain applications, such as environmental monitoring, target detection, and mineral exploration. HSI contains a large amount of spectral information. Photons are typically collected in a larger spatial area on the sensor to ensure a sufficiently high signal-to-noise ratio (SNR). Accordingly, the HSI spatial resolution is much lower compared with MSI. This low spatial resolution greatly affects the practicality of HSI. Accordingly, fusing a low-spatial resolution HSI (LR-HSI) with a high-spatial resolution MSI (HR-MSI) in the same scene to obtain a high-resolution HSI (HR-HSI) is a method for solving such problems, which resolves the contradiction that the spatial resolution and the spectral resolution cannot simultaneously maintain a high level. From the analysis of fusion effect, the spatial and spectral reconstruction errors of the existing algorithms are mainly reflected in the edge and detail areas. The method proposed in this work was a fusion algorithm for dictionary construction and image reconstruction based on detail attention. In terms of maintaining spectral characteristics, the spectral distribution in the detail area is complex and diverse because of the proximity effect of the image. This work proposes to perform dictionary learning on the image and detail layers. The detail perception error terms and a constraint of edge adaptive directional total variation are proposed for spatial characteristic enhancement, which is combined with a local low rank constraint in the same fusion framework to estimate the sparse coefficient. Experiments were conducted on two datasets, namely, Pavia University and Indian Pine, to verify the effectiveness of the proposed method. The quantitative evaluation metrics contain peak SNR, relative dimensionless global error in synthesis, spectral angle map, and universal image quality index. Based on the experimental comparison, the fusion result of the algorithm proposed in this work is significantly improved compared with those of the other algorithms in terms of spatial and spectral characteristics. This work uses dictionary learning to propose a fusion algorithm for dictionary construction and image reconstruction with attention to details through the analysis of the existing hyperspectral and multispectral image fusion algorithms. A hierarchical dictionary learning algorithm is proposed to address the problem of large reconstruction error in the detail part of the existing algorithms. The detail perception error term and the direction adaptive full variational regularization term are used to improve the spectral dictionary solution and coefficient estimation, respectively. The result of the fusion is the error in the spectral characteristics and spatial texture of the detail, which achieves an accurate representation of the edge detail. © 2022 National Remote Sensing Bulletin. All rights reserved.