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    20 September 2014, Volume 43 Issue 9
    Study of Optimal Regularization Parameter Determination Method in Downward Continuation of Gravimetric and Geomagnetic Data
    LIU Xiaogang LI Yingchun XIAO Yun ZHAI Zhenhe
    2014, 43(9):  881-887.  doi:10.13485/j.cnki.11-2089.2014.0160
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     Downward continuation is one of the key steps in the processing of gravimetric and geomagnetic data. However, downward continuation is a typical ill-posed problem, and its computation is unstable. Therefore, the regularization methods are needed in order to realize the effective continuation of gravimetric and geomagnetic data, and the determination of regularization parameter is the most important content in the study of downward continuation by regularization method. According to the Poisson integral plane approximate relationship between observation and continuation data, and combining with Fast Fourier Transform (FFT) algorithm, the computation formulae were transformed to frequency domain so as to accelerate the computational speed. The Landweber regularization iteration method was introduced so that the instability could be overcome and the results precision could be improved, based on that the determination method of optimal regularization parameter in downward continuation was studied by L-curve method. The availability of regularization parameter was validated by simulated geomagnetic data, and continuation results in good precision were also derived.

    Robust Weighted Total Least Squares Based on IGG Weighting Function
    GONG Xunqiang LI Zhilin
    2014, 43(9):  888-894.  doi:10.13485/j.cnki.11-2089.2014.0140
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    In weighted total least squares, gross errors of observation data are not taken into consideration. In order to resolve this problem, a robust method of weighted total least squares with reweighting iteration based on IGG weighting function is proposed. Thorough experimental evaluation with a large number of simulation data and real-life data sets has been carried out. The results of coefficient estimation and error estimation are systematically compared with weighted total least squares, and robust weighted total least squares based on Huber weighting function. It is shown that (a) more reliable parameter estimation can be obtained by two robust weighted total least squares; and (b) more importantly, the proposed method performs better than others.

    Method of Processing GNSS Reference Network Data with Refined Datum Definition for Rank-deficiency Elimination
    ZHANG Baocheng OU Jikun YUAN Yunbin
    2014, 43(9):  895-901.  doi:10.13485/j.cnki.11-2089.2014.0164
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    Global Navigation Satellite System (GNSS) networks are widely used for determining satellite orbit/clocks, monitoring crustal deformation and velocity field of the Earth as well as estimating the Earth’s rotation parameters. The data processing strategies comprise Double-Difference (DD) based baseline solution as well as un-differenced based Precise Point Positioning (PPP) solution. On the basis of fundamental GNSS observation equations, full-rank function models adopted by both strategies are respectively derived after identification of two distinct sets of datum parameters. Moreover, the potential pitfalls associated with both strategies are summarized. For instance, the estimable phase biases are biased by the clocks in context of DD strategy and thus become time-varying between adjacent epochs; with respect to PPP strategy, the integer nature of estimable ambiguities is deteriorated due to their absorption of phase biases. A modified strategy is proposed in this paper by means of determining a set of refined datum parameters so as to take advantage of benefits belonging to either DD or PPP strategies. Its main advantages involve: the solvability and the time-constancy of phase biases would largely reduce the number of unknowns and consequently improve formal precision of network solution. Furthermore, owing to well-kept integer nature of the estimable ambiguities, the reliability of network solution would be potentially strengthened after successful ambiguity resolution. Keywords: GNSS; reference network data processing; rank-deficiency elimination; time-varying parameters; time-constant parameters; precise point positioning

    A Method of Determining the Weight Matrix for BDS Single Point Positioning
    XIAO Guorui SUI Lifen LIU Changjian LV Zhiping GAN Yu QI Guobin
    2014, 43(9):  902-907.  doi:10.13485/j.cnki.11-2089.2014.0165
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    The constellation of BeiDou Navigation Satellite System is composed of Geostationary Earth Orbit (GEO) satellites and Non-Geostationary Earth Orbit (Non-GEO) satellites. In consideration of the huge difference between GEO satellites altitude and Non-GEO satellites altitude, the global nonlinear least squres algorithm(Bancroft algorithm) is applied for BDS single point positioning in this paper. The Bancroft algorithm based on the Lorentz inner product is mainly in four dimensional space. A new algorithm to get the BDS observation weight is introduced by transforming Lorentz inner product into error equation, and then weight of the error equation is deduced. In order to testify the method, a code-minus-phase combination (CC) of BDS measurements is used to determine the code noise of GEO and Non-GEO satellites, a multipath combination (MP) is introduced to extract the multipath of pseudorange and improve the accuracy of single point positioning. The result indicates that new algorithm can improve the accuracy of BDS single point positioning.

    An Automatic Sample Collection Method for Object-oriented Classification of Remotely Sensed Imageries Based on Transfer Learning
    WU Tianjun LUO Jiancheng XIA Liegang YANG Haiping SHEN Zhanfeng HU Xiaodong
    2014, 43(9):  908-916.  doi:10.13485/j.cnki.11-2089.2014.0163
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    For the large-scale remote sensing applications, the automatic classification of remotely sensed imageries is still a challenge. For example, the artificial sample collection scheme cannot meet the needs of automatic information extraction from the remotely sensed imageries. In order to establish a prior knowledge-based and fully automatic classification method, an automatic sample collection method for object-oriented classification, with the introduction of data mining to the process of information extraction, is proposed. Firstly, the unchanged landmarks are located. Then the prior class knowledge from old interpreted thematic images is transferred to the new target images. And the above knowledge is then used to rebuild the relationship between landmark classes and their spatial-spectral features. The results show that, with the assist of preliminary thematic data, the approach can automatically obtain reliable object samples for object-oriented classification. The accuracy of the classified land-cover types and the efficiency of object-oriented classification are both improved.

    Effect of Temporal Variation of Atmospheric Refraction on Geosynchronous Circular SAR Focusing Performance
    KOU Leilei XIANG Maosheng
    2014, 43(9):  917-923.  doi:10.13485/j.cnki.11-2089.2014.0124
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    Combining the geosynchronous SAR (GEOSAR) with the circular SAR (CSAR), the geosynchronous circular SAR (GEOCSAR) has many advantages such as broad coverage, high resolution three dimensional (3D) imaging and continuous surveillance. However, due to its very long synthetic aperture time (about 24 hours for full aperture measurement), the effect of the atmospheric temporal variation may be significant, for the atmosphere usually changes its structures on timescales of minutes to hours. Since this paper considers the L-band GEOCSAR system, the tropospheric and ionospheric effects should both be included. The phase error due to the temporal variation of the tropospheric and ionospheric refraction is modeled. Then, the effect of the temporal variation of the troposphere and ionosphere on GEOCSAR imaging is derived and analyzed. Besides, the minimum of the random tropospheric and ionospheric temporal variation causing the L-band GEOCSAR imaging performance deterioration is deduced. The effects of atmospheric temporal variation are validated via simulations.

    The Automatic Extraction and Recognition of Lunar Impact Craters Fusing CCD Images and DEM Data of Chang’e-1
    LUO Zhongfei KANG Zhizhong LIU Xinyi
    2014, 43(9):  924-930.  doi:10.13485/j.cnki.11-2089.2014.0137
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    As the extraction of lunar craters presently suffer from insufficient quantitative information and mis-extraction, this paper proposes an algorithm of automatic extraction and recognition of lunar impact craters fusing CCD images and DEM data of Chang’e-1. (1) The images of craters comply with specific rules derived from the illumination of sun, therefore the extraction of craters in CCD images is implemented by the matching of corresponding crater feature segments; (2) the mis-extraction of craters in CCD images is then eliminated in terms of  the continuity of the aspects of crater wall, which are computed using DEM data. (3) the edge points of a crater are extracted in the light of the abnormal change between the direction of the  normal vector of an edge point and that of a non-edge point, the parameters of craters are then computed through the fitting of edge points and the types of craters are recognized according to the proportion of points on the bottom and the hatch of craters. The proposed approach is tested on CCD images and DEM data of Chang’e-1. The results show that our proposed algorithm has good performance in the high-latitude areas where the distribution of lunar impact craters is uniform.

    Post-earthquake Landsides Distribution along Longmenshan Major Fault during Rainy Season with Short-baseline InSAR
    CHENG Haiqin CHEN Qiang LIU Guoxiang YANG Yinghui
    2014, 43(9):  931-938.  doi:10.13485/j.cnki.11-2089.2014.0161
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    In order to investigate the spatial pattern of landslides along the major fault in Longmenshan area, the PALSAR interferometric pair with short baseline was utilized in the study. The atmospheric phase correction model with three dimensional geo-spatial factors was proposed to eliminate the long wavelength components. The LOS deformation threshold was set to reduce the short wavelength phase error. The terrain slope factor was introduced to analyze the spatial pattern of post-earthquake landslides triggered by the rainstorm. The results show that the active landslides presented clearly a linearly distribution along both sides of Yingxiu-Beichuan fault. The majority of landslides were about (3~15) km away from the major fault. The statistics data suggested that almost 90 percent of the post-earthquake landslides located in the elevation range of (1000~3000) m and the terrain slope factor (15~35) degrees. The spatial distribution characteristics with 70% landslides scattered on the hanging wall indicated that the after effect of hanging wall upthrusting motion dominated the pattern of post-earthquake landslides.

    A Building Detection Algorithm Based on Visual Attention and Feature Fusion in High Resolution SAR Images
    SU Juan ZHANG Qiang CHEN Wei WANG Jiping
    2014, 43(9):  939-944.  doi:10.13485/j.cnki.11-2089.2014.0162
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    A building detection algorithm based on visual attention and feature fusion is proposed for high spatial resolution SAR images. Firstly, visual attention model is constructed on the basis of great difference between buildings and backgrounds, and used to segment the ROIs of buildings. Secondly, bright lines and shadow regions are extracted in the segmented ROIs. Finally, D-S evidence theory is used to fusion the focus of attention, bright line and shadow region, and then the buildings are detected. Experimental results demonstrate that, the proposed algorithm has high detection accuracy for rectangular buildings in SAR images.

    Change Detection Experimental Study Based on Spectral and Texture Features
    LI Liang SHU Ning WANG Kai GONG Yan
    2014, 43(9):  945-953.  doi:10.13485/j.cnki.11-2089.2014.0138
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    In order to make full use of spectral and texture features, an object-oriented change detection method for remote sensing images based on multi-features fusion is proposed in this paper. First image segmentation is used to get image objects. Then the spectral and lbp texture histograms of each object are extracted. G statistic is adopted to calculate the distance of histograms between two periods. The heterogeneity of each object is built by weighted spectral and texture distance. At last, the expectation maximization algorithm and bayesian rule with minimum error rate are applied to get the change/no change results. Experimental results on QuickBird and SPOT-5 images show that the method proposed in this article can integrate the spectral and texture features effectively and improves the accuracy of change detection.

    Drift Angle Residual Corrrection Technology in Satellite Photogrammetry
    WANG Jianrong WANG Renxiang HU Xin
    2014, 43(9):  954-959.  doi:10.13485/j.cnki.11-2089.2014.0128
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    Based on the stereo image photography mechanism, the paper analyzes the vertical parallax caused by drift angle correction technical measures,and establishes the Mathematical model for residual of drift angle of stereo camera. It derives the error equation that can calculate the drift angle residual’s influence on vertical parallax, and put forward solutions from the aspects of camera parameters on-orbit calibration and error compensation of low frequency in bundle adjustment. The theoretical analysis and practical test with real satellite images shows that the correction residual of drift angle has a relatively great influence on vertical parallax, and it must be corrected through camera parameters on-orbit calibration and error compensation of low frequency, so that the accuracy of positioning without ground control point on a global scale can be maintained.

    The Graph Theory Approach to Grid Pattern Recognition in Urban Building Groups
    GONG Xianyong WU Fang
    2014, 43(9):  960-968.  doi:10.13485/j.cnki.11-2089.2014.0125
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    Map Patterns in building groups embody the relationship of the material form of cities and their social-economic function, and reflect the city’s spatial structure, which have great importance in Cartographic Generalization and Multi-Scale Representation. On the basis of related research home and abroad, a Graph Theory approach is proposed to recognize the grid pattern in building groups. Firstly the cognitive characteristics and definitions of grid pattern are analyzed. Then neighborhood relationship is captured by proximity graph with the help of Delaunay triangulation, and visual distance model is established considering the Gestalt principles. Multi-connected linear pattern is recognized with constrains such as linear arrangement and compactness. Finally the line pattern intersection graph and similar orientation graph are formed. The candidate grid patterns are extracted through graph operation such as finding maximal complete sub-graph, join, intersection and post-processing. Experiments show that this approach is effective, feasible and practicable for obvious grid pattern recognition with the agreement of human spatial cognitive characteristics.

    Research on a Buffer Algorithm Based on Region-Merging of Buffered Geometry Components and Its Parallel Optimization
    FAN Junfu MA Ting ZHOU Chenghu JI Min ZHOU Yuke XU Tao
    2014, 43(9):  969-975.  doi:10.13485/j.cnki.11-2089.2014.0122
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    Abstract: The double-sided parallel line method and the geometry rasterization-based dilation method have been extensively used for buffer generation in spatial analysis. The former involves a series of complex numerical operations and may not be suitable for parallelized computation; the latter inevitably introduces precision problems and computation complexity. In this paper, we proposed a parallel buffer construction algorithm based on region-merging of buffered geometry components in association with the message passing interface (MPI) parallel programming model. Several optimization strategies were studied for the parallel buffer algorithm. The performances of both serial and parallel buffer algorithms were comparably analyzed. Three performance bottlenecks which significantly impact the algorithm efficiency were identified: area merging operation, task load balance strategy and MPI inter-process results merging methods. Corresponding optimization approaches involving tree-like area and inter-process results merging and the parallel task partition based on vertex number oriented parallel task partition strategy were suggested to overcome these bottlenecks. Several experiments were carried out to examine the performance efficiency of the optimized parallel algorithm. The estimation results suggested that our method could provide high performance and processing ability for buffer construction in a parallel environment. Our method could provide insights into the parallelization of spatial analysis algorithm.

    A Semantic Categorization of Hydrological Domain Based on Formal Concept Analysis
    LI Junli HE Zongyi YAN Xiongfeng ZHU Qiaoli
    2014, 43(9):  976-981.  doi:10.13485/j.cnki.11-2089.2014.0130
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    The reasonableness of the geographic information categorization system has a direct impact on the interaction and sharing of geographic information. A method is proposed to explore the hierarchical semantic categorization of the fundamental geographic information from GB/T 13923-2006 in China. First,we selected a set of meta-properties to extract the semantic of geographical entity, and then construct the formal concept context and Hasse Diagram based on Formal Concept Analysis, finally, we implemented Lattice-tree transforming method of generating the hierarchical semantic classification of hydrological domain, which possessed the direct semantic inclusion. The method eliminates the overlapping concept and crossing semantic among the original classification system, which is a useful complement to the existing classification methods. As well as merits and limitations are discussed.

    A geographical information oriented trajectory model and spatio-temporal pattern querying
    XIANG Longgang WU Tao GONG Jianya
    2014, 43(9):  982-988.  doi:10.13485/j.cnki.11-2089.2014.0121
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    Trajectory processing and analyzing is now one of the hottest research issues in related fields, such as geography, database, and so on. Inspired from the Stop/Move abstract model of trajectory, this paper aims at modeling trajectory by integrating context geographical information and studying the processing techniques on trajectory spatio-temporal pattern queries. First, the semantic relationships between Stop/Move objects and point/line/polygon features are analyzed, based on which a novel trajectory model that explicitly expresses geographical information associated semantics is proposed; Next, an application-independent trajectory relational schema for this trajectory model is designed; Next, the concept of trajectory spatio-temporal pattern query is introduced, and its SQL processing framework, based on trajectory relational schema, is also proposed. Finally, this paper discusses how to processing trajectory spatio-temporal pattern queries with pure SQL languages. To make the answering procedure more clearly, this paper not only presents several typical example queries and their corresponding SQL statements, covering all three types of trajectory spatio-temporal pattern queries, i.e., location-time, location-order and location-relation, but also analyze in detail the hidden SQL processing steps. The trajectory model and its sptaio-temporal pattern querying, proposed in this paper, is a relatively new solution to process and analyze trajectory dataset. It is not only capable to model trajectory and its context geographical information, but also a cost-efficient way to process trajectory spatio-temporal pattern queries, which is carried out just based on mature SQL technology without the necessary to develop complicated data mining methods.

    Study on Dynamic Service Computing of HSOSCS
    CHENG Dayu
    2014, 43(9):  989-989.  doi:10.13485/j.cnki.11-2089.2014.0167
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    The Study of GIS Computational Model Based on Geometric Algebra
    LUO Wen
    2014, 43(9):  990-990.  doi:10.13485/j.cnki.11-2089.2014.0168
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    The Study of GIS Computational Model Based on Geometric Algebra