Table of Content

20 June 2013, Volume 42 Issue 3

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Research on Influence of Polar Gaps on Gravity Field Recovery Using GOCE Data

2013, 42(3):  0-0. 

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There are empty regions near the poles which are two spherical caps with angle radius of 96.7°, as the inclination of GOCE satellite is 96.7°. This paper will discuss the influence by combining the methods of invariants. Firstly it derives the formulas which show the influence of the polar gaps on the gravity field recovery, and then analyzes the magnitude and prosperity of the influence by simulation. The results show that different degrees will influence each other due to the destruction of orthogonality, especially on low orders. The method of remove-restore can effectively solve the problem of accuracy lose due to the polar gaps, but different reference models will give different results. However, even so, GOCE can still provide geoid with accuracy of several centimeters not in polar region.

Research the Algorithm of Wavelet Neural Network to Predict Satellite Clock Bias

2013, 42(3):  0-0. 

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Satellite clock bias (SCB) prediction plays an important role in satellite navigation system, such as optimizing clock parameters in navigation message, meeting the needs of real-time dynamic precise point positioning and providing the required information for satellite autonomous navigation. It is proposed that a wavelet neural network (WNN) model based on a method of once difference to predict clock bias considering the characteristic of SCB in this paper. The main ideas are that firstly two SCB values of adjacent epoch are made once difference to obtain the corresponding once difference sequences, then modeling to predict the once difference values of following time series. At last, the predicted sequences are recovered to the corresponding predicted SCB. This method makes the WNN model of SCB prediction not only employs simple framework but also has high prediction precision. Through prediction examples, the paper compares the above model with two common models, i.e. Quadratic Polynomial (QP) model and GM(1,1) model; the results show that the method of once difference can evidently improve the prediction precision of SCB for the given WNN and that the proposed model possesses better performance compared with the common models in SCB prediction. At the same time, the prediction results of all models mentioned in the paper are analyzed, and some useful conclusions are educed.

Parallel Filter of Progressive TIN Densification for Airborne LiDAR Point Clouds Using Multi-core CPU

2013, 42(3):  0-0. 

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Filtering is one of the key steps in the processing of airborne LiDAR data. General serial algorithms are inefficient in the processing of large scale point cloud and couldn’t meet the demand of rapid mapping. A parallel filter of progressive TIN densification based on the technology of multi-core computing is developed which parallelizes the most time-consuming job, i.e. triangulation and point filtering. The parallelization of triangulation is based on the divide-conquer method, and the point filtering employs a strategy of random allocation by decomposing the triangle sets into many sub-sets featuring discrete distribution to realize load balance. In an 8 cores environment, the algorithm gains a speed-up of 3.1 approximately in progressive densification. Comparative experiments have evaluated the algorithm’s capability of fully exploiting the advantages from multi-core technology and better adaptability to different spatial point patterns.

Improved GAC Model for Automatic Building Extraction from Lidar Point Clouds and Aerial Image

2013, 42(3):  0-0. 

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This paper proposes Improved GAC Model based on the initial curve and the external force，which is a new method for automatic building extraction from Lidar point clouds combined with the aerial image. In this study, the morphological alternating sequential filtering is used to access the initial curve automatically,and then the external force is improved by the Lidar depth gradient image,so the Improved Geodesic Active Contour (IGAC) Model is proposed. Experiment indicates that this method can inhibit the weak boundary leakage and produce high accuracy and completeness of building boundary.

River Extraction from the High Resolution Remote Sensing Image Based on Spatially Correlated Pixels Template and Adboost Algorithm

2013, 42(3):  0-0. 

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For the analysis of high resolution remote sensing images, in addition to pixel-based spectral data, spatial and structural information should also be consider for a more intuitive and accurate interpretation. This paper presents a kind of neighbor patterns, referred to the spatially correlated pixels template, to incorporate the spatial relationship among pixels. And in conjunction with Adboost ensemble learning algorithm, accurate river extraction from an IKONOS high resolution remote sensing image is obtained. Firstly, a particular form of spatially correlated pixels templates is generated by using the filter feature selection approach. Secondly, the multi-dimensional feature vectors are constructed according to the given template. Then, Adboost algorithm is used to make full use of available features. Finally, the accurate river extraction is achieved by ensemble learning. Experimental results show the proposed methodology compares favorably with the SVM and maximum likelihood methods, particularly in the aspect of overall accuracy and object-oriented property.

Sparse Nonnegative Matrix Factorization for Hyperspectral Band Selection

2013, 42(3):  0-0. 

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Hyperspectral data provides imagery with hundreds of spectral bands, but many of them contain redundant information. Band selection is often applied to reduce the dimensionality of the data. This paper proposes a new technique for band selection through sparse nonnegative matrix factorization (SNMF-BS) which decomposes the image data into the multiplication of basic matrix and the coefficient matrix. Using sparse NMF, Hyperspectral images can be described as sparse representation. Since sparse NMF acts as co-clustering, it can be used for band clustering without considering the distance metric between different spectral bands. By imposing the sparsity constraint on the coefficient matrix, clustering assignments of bands can be easily indicated through the largest entry in each column of the matrix. Through band clustering, sub-bands are selected to serve the need of dimensionality reduction, while preserving the physical meanings of the selected bands. The PHI-3 real hyperspectral dataset is experimented for band selection. Clustering validity indexes, KLC, band correlation and separability are used to do the evaluation. The experimental results show that sparse NMF provides considerable insight into the unsupervised clustering-based band selection problem and also offer the proper band combinations with spectral meanings. And the results also demonstrate that the proposed method outperforms other popular methods.

The 3D Visualization Method of Hexagonal Discrete Global Grid Data

2013, 42(3):  0-0. 

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Aiming at the 3D visualization method of hexagonal discrete global grid, a new spatial operation structure (Hexagonal Quad Balanced Structure, HQBS) for hexagonal discrete grid, was designed. It used 4 codes to encodes units, defined spatial vectors for grids and realized basic operations. Based on the operations, spatial index can be easily solved. And dynamic generation algorithms, spatial visualization methods and clipping of visible area of global grid were studied. Through visualization experiments, conclusions were obtained as follows. The average generation efficiency of global dynamic grid could reach 110 units per ms to 370 units per ms, and the loading time efficiency of grid data and spatial data per layer was about 300 ms. The average refreshing level of global discrete grid loaded with spatial data was about 20 frames per second, which ensured real-time displaying requirements.

An Extended SURF Descriptor and Its Application of Remote Sensing Images Registration

2013, 42(3):  0-0. 

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To solve the classical methods’ problems of long executing time or low accuracy, this paper proposes an extended SURF descriptor. On the method using SURF, the proposed method uses local normalization information and second-order gradient values of neighborhood regions to build a new one. Not only does this method perform as fast as SURF algorithm, but it also fully employs the image grayscale information and details. Considering the executing time and rate, experimental results presented in this paper show that the proposed method is more robust than classical methods.

Automated Airborne LIDAR System Calibration Using Virtual Tie Point

2013, 42(3):  0-0. 

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This paper presents an automated method of systematic bias self-calibration for airborne LIDAR. Traditional calibration approaches rely on manual extraction geometric features and lack adaptability for practical data. We attempt to establish a novel method based on conjugate point features extracted from overlapping LIDAR strips to play off the advantage of point features in abundance and accessibility. Firstly, the Virtual Tie Point Model is proposed to solve the point corresponding in discrete point cloud. Then, to employ intensify information of LIDAR data, an automatic workflow for corresponding point extraction is given. Finally, practical LIDAR data is used to test our method. Compared to coplanar constraint calibration method, the result illustrates the feasibility and effectiveness of the proposed method.

Method on Block Combined Geocoding of Airborne InSAR with Sparse GCPs

2013, 42(3):  0-0. 

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This paper proposed an absolute orientation model for slant-range elevation map of airborne InSAR which is not geocoded. At first, the model converts slant-range elevation map to ground-range elevation map according to elevation of the map, so relative displacement between image points can be eliminated. Then ground-range elevation map as a rigid body is transformed to map in geographic coordinate system by similarity transformation. So geocoding can be realized with the mapping between point of elevation map and ground point. On the basis of absolute orientation model, a block is made up with multiple ground-range elevation maps as cell models using common points of neighbor model. Then model orientation and solution for geographic coordinates of common points can be completed by block adjustment, and combined geocoding of multiple elevation maps can be realized. Experiment was carried out with airborne InSAR data containing three strips and located at Hengduan Mountain area of Western China. The resolution is 2.5m. The orientation points and check points were derived from block of spaceborne optical images. Distribution scheme of orientation points was determined with comparison of several different schemes. The results showed that the accuracy trended to be stable with nine orientation points and meet the need of topographic mapping at scale of 1:50 000.

A Robust Multi-frequency Phase Unwrapping Method Based on Gradient Reconstruction

2013, 42(3):  0-0. 

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In order to address the difficulties in elevation extraction for rugged terrain due to phase under sampling by conventional InSAR system, a phase unwrapping method supported by phase-gradient reconstruction from multi-frequency interferograms is presented. Based on statistical distribution property of wrapped phase, a maximum likelihood estimation technique using multi-frequency phase-gradient is investigated first. Considering the problem of high sensitivity to phase noise under limited number of frequencies in resolving gradient ambiguity, an improved phase-gradient estimation algorithm based on local surface modeling within neighborhood set is presented, and the way to enhance the robustness is further studied from aspects of frequency selection, estimation interval restriction and so on. Finally, experiments using simulated and real DEM data are performed respectively, and the results confirm the validity of the proposed method.

Extracting complex Building Facades from Mobile Laser Scanning Data

2013, 42(3):  0-0. 

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This paper proposes an efficient method of extracting complex building facades from mobile LiDAR data in large scale urban environment. The proposed method firstly eliminates the noise in the data. An adaptive neighborhood algorithm based on dimensionality is then adopted to calculate the local geometric features of each point, such as local normal vector and dimensionality feature. Then, a region growing segmentation method with adaptive growing rules is applied to segment the point cloud. Finally, Knowledge based feature recognition method is developed for detecting facade planar patches, which are combined to represent the whole facades of complex buildings. Experiments show that the proposed method has a promising solution for building facade extracting from mobile LiDAR point clouds.

Topographic Mapping in Mountainous Areas Using StereoSAR Assisted by External DEM

2013, 42(3):  0-0. 

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Matching between stereo SAR image pairs is crucial for Radargrammetry to extract height information since the matching accuracy will directly influence the accuracy of resultant DEM. The homologous points are difficult to identify in StereoSAR image pair due to complex geometric and radiometric distortions. In this paper, a new method is proposed to improve the matching performance. According to this method, an external DEM of coarse resolution is utilized as the auxiliary data from which the initial parallax can be derived to facilitate the step of image matching. At the same time, a pyramid delamination matching scheme is adopted to reduce the search range and thus improve the matching efficiency and control the propagation of gross errors. The experimental results show that the gross errors on the resultant DEM are reduced significantly with assistance of external DEM and the derived elevation accuracy is improved effectively.

Distributed Collaborative Geographic Modeling Task Decomposition Method Based on HTN Planning

2013, 42(3):  0-0. 

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In order to effectively solve the problem of static integrating mode of models in distributed collaborative geographic modeling environment, this paper proposes several decomposition principles of geographic modeling tasks such as function structure, computational complexity, organization multiplicity, and spatiotemporal scales by analyzing the decomposable process of distributed collaborative geographic modeling tasks. Hierarchical Task Network (HTN) planning is adopted to reach formalized expression of the geographic modeling tasks, in the meanwhile, Ordered Task Decomposition (OTD) is also applied to design recursive decomposition algorithm of modeling tasks. Ultimately, the modeling tasks are tessellated, decomposed and expanded to subtask network. With the adoption of SWAT model as an experimental case, HTN-based geographic modeling task planner was developed and realized. The experiment shows that the decomposition method of distributed collaborative geographic modeling tasks possesses preferable flexibility, intelligence and adaptability.

The LOD Representation and TreeMap Visualization of Attribute Information in Thematic Mapping

2013, 42(3):  0-0. 

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The structure of socio-economic information usually acts as the main representation object in thematic mapping. Traditionally the statistical chart of thematic map can only visualize the hierarchical component information at a single level, such as the percentage. In this study, a method for the LOD visualization of attribute information in thematic maps is proposed. The new hierarchical information visualization tool, namely the TreeMap in computer graphics field, is used to carry out the multi-level display of attribute information. The presented approach is able to adjust the level of structural details of the attribute information when changing the scale of thematic map. This study combines the Cartogram mapping model with TreeMap to establish the spatial location of the multi-level attribute information considering the topological properties among region polygons. This method provides the users with the strategy to visualize and cognize the attribute information at multi-levels.

A kind of spce oblique conic map projection model and its calculation

2013, 42(3):  0-0. 

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The problem of space map projection of side-glance radar imagery of satellite is researched in this paper. As the dynamic mathematical foundation, a kind of Space Oblique Conic Projection (SOC) is specifically designed for the side-glance radar imagery of satellite. The geometric model of SOC is considered firstly, and the groundtrack projection of the central line of side-glance region is established secondly based on this model, and then the formula of space oblique conic projection is deduced and the projection distortion is discussed. As an example, the side-glance radar imagery data of ocean satellite is considered, and a special space oblique conic projection model is obtained finally.

Study on the Methods of Indirect Contour Line Generalization Based on the 3DDougals-Peucker Algorithm

2013, 42(3):  0-0. 

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Abstract: Based on previous research, apply method of 3D Douglas-Peucker Algorithm to automatic generalization of contour lines. Discuss principle and technical line of indirect generalizing contour lines by taking contour as discrete point without specific format. Preliminary experiments have proved that the contour lines generalized by this method have the geometrical accuracy as well as the topological consistence, and the condition of continuity of the source contour lines for generalization by this method is not so strictly demanded. Therefore, it has a good prospect of application.

Research on the Linear Array Aerial Sensor Calibration Without Ground Control Points Based on Strip Structure

2013, 42(3):  0-0. 

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Based on the analysis of geometrical characteristic and error model of the linear array sensor, this paper puts forward a kind of linear array sensor calibration method without ground control points(GCPs), which could not be required testfield any more. From the analysis of the correlation of the various parameters of the geometric calibration, the geometrical conditions of the strip structure are provided to eliminate or reduce the correlations among various parameters which affect the accuracy of the calibration result. The special structure of the two-flight levels is discussed to eliminate the strong correlation between principal distance, principal point and height, in order to achieve the camera self- calibration process without ground control points. Research on the whole working process and using different camera data for calibration experiments, the accuracy of the new camera parameters are validated and analyzed. The results confirmed that the method in this paper is completely reliable and feasible, and can effectively improve the imaging data of geometric positioning accuracy.

Analysis of global ionospheric grid model integrated GPS/GLONASS

2013, 42(3):  0-0. 

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When using GPS dual frequency measurements to establish ionospheric models, the amount of satellites and distribution of pierce points would affect the accuracy. With the various navigation systems have been completed, it becomes an inevitable trend to establish ionospheric model with data from multi-systems. This paper studied on the establishment and data processing of ionospheric model based on the integration of GPS/GNSS systems, and developed a software of global ionospheric grid model based on GNSS, named IonoGim. Take the result of 001-031 days in 2010 as the example to analyze the influence for global ionospheric model by adding GLONASS data, we found that combining the data of GPS and GLONASS did not have a significant improvement for the result, on the contrary, the RMS at grids points were increased, which was caused by the weaker quality of GLONASS observations. However, the combining result corresponded better with CODE result. Besides, adding GLONASS observations to establish model cannot overcome the limitation of a bad accuracy over the marine area, therefore, how to improve the accuracy over the ocean still needs to be further studied.

Six Basic Principles for Cartography and its Interpretation

2013, 42(3):  447-452. 

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The book Six Basic Principles for Cartography by Pei Xiu in Xijin Dynasty in ancient China is an important historical document focusing upon the development of ancient Chinese measuring technology. Based on the former studies and achievements and combined with the basic principles and reasons in The Tribute to Yu complied by Pei Xiu, the article makes a comprehensive interpretation of Six Basic Principles for Cartography, taking into account the then measuring technology and development in former studies. On the basis of the above, with Zhunwang, the core of the six basic principles, used as a general measuring terminology to refer to precision measurements in ancient China, the article makes the further interpretation that the book Six Basic Principles for Cartography makes a summary of fundamental map making requirements on behalf ofsh Pei Xiu. The book also offers the best interpretation of Pei Xiu’s measuring technology, the Ji-li-hua-fang or the square grid system, combined with regional maps and textual research. The research makes complimentary contents into former ones.