Table of Content

20 May 2018, Volume 47 Issue 5

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Block Movement and Strain Characteristics Effected by Earthquake in Sichuan-Yunnan Region

DANG Yamin, YANG Qiang, LIANG Shiming, WANG Wei

2018, 47(5):  559-566.  doi:10.11947/j.AGCS.2018.20160311

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In this paper, we studied the active blocks movement and deformation in the Sichuan-Yunnan region before and after the Wenchuan earthquake by using the measured velocity field of GNSS during the period from 1999 to 2007 and from 2009 to 2015. We established movement and strain model of active blocks before and after earthquake by introducing the translation-rotation-strain model, and effective to separate the blocks movement and blocks strain characteristics. According to this, the characteristics of the motion and strain of the block before and after the earthquake are analyzed. The results show that the Qiangtang block and Bayankala block to the East movement increases significantly, and after the Wenchuan earthquake is the biggest change in the boundary zone between Qiangtang block and South-China block, the compressive strain larger boundary section, and after the Wenchuan earthquake the relative extrusion movement increased significantly between Sichuan-Yunnan block and Qiangtang block, and South-China block and Bayankala block, but the relative motion between the South-China block and Sichuan-Yunnan block did not change significantly.

Evaluation of the External Accord Accuracy of Airborne Gravity Data with Upward Continuation

JIANG Tao, XIAO Xuenian, DANG Yamin, ZHANG Chuanyin, LIU Zhanke

2018, 47(5):  567-574.  doi:10.11947/j.AGCS.2018.20170053

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Three methods for evaluating the external accord accuracy of airborne gravity survey line data, namely the gradient based, the Poisson integral based and the fast Fourier transform (FFT) based upward continuation (UPC) of terrestrial gravity, are introduced. A cross validation method is proposed for the estimation of terrestrial gravity errors and their propagation at flight altitude. The external accord accuracy of airborne gravity survey line data over Mu Us in Inner Mongolia is evaluated based on the three UPC methods and the proposed cross validation method. Numerical results show that the gridding interpolation error and representative error of terrestrial gravity range from 0.66 to 0.92 mGal, which demonstrates the necessity of removing these errors for error estimation of airborne gravity data. The Poisson integral and the FFT based UPC method are capable of evaluating the external accord accuracy of airborne gravity data, both have comparative performance. Applying the methods for the data acquired by GT-2A airborne gravimetry system over Mu Us in Inner Mongolia, it turns out the external accord accuracy of the airborne gravity disturbances is better than 1.42 mGal(1 Gal=1×10^-2 m/s²) after the removal of terrestrial gravity error contribution,while some remaining integral edge effects still exist.

The 3D Gravity Vectors Method in China Land and Ocean Quasi-geoid Determination

XING Zhibin, LI Shanshan

2018, 47(5):  575-583.  doi:10.11947/j.AGCS.2018.20170076

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The horizontal component of earth gravity field-vertical deflection is very sensitive to the information of terrain. Firstly, using 3D gravity vectors-grid vertical deflections which are calculated by gravity and terrain data by solving physical geodetic boundary value problems (GBVP), grid gravity anomaly and grid terrain data to calculate the differences of height anomaly, then, with the control of GPS/leveling points to form rigorous geometric conditions, after that, the grid height anomaly is calculated by L-S adjustment method. Finally, a quasi-geoid model with a high precision and resolution is achieved. Based on the method presented, a national quasi-geoid model is built which includes land and ocean by using more than 6600 GPS/leveling points data, 1'×1' grid vertical deflections, grid gravity anomaly and grid terrain data. Compared with the GPS/leveling points, the absolute precision of our national quasi-geoid is about 4 cm, while the relative precision is better than 7 cm.

Real-time Estimation Method for GLONASS Phase Inter-frequency Bias Based on Particle Swarm Optimization

SUI Xin, XU Aigong, HAO Yushi, WANG Changqiang

2018, 47(5):  584-591.  doi:10.11947/j.AGCS.2018.20170244

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GLONASS phase inter-frequency bias (IFB) is linearly correlated to ambiguity, so it is difficult to separate phase IFB and ambiguity quickly. To solve this problem, a real-time estimate method for GLONASS phase IFB is proposed. By analyzing the relationship between the phase IFB parameter and the RATIO value, the phase IFB estimation problem comes down to solve the optimization problem. The particle swarm optimization (PSO) algorithm is one of the optimization methods, which is used to estimate the phase IFB parameters. This method can search the IFB rate parameter in an effective and reliable way without increasing the number of estimated parameters and prior information, and GLONASS ambiguities can be real-time fixed. The experimental results show that the average number of searching per epoch is 32 for single-epoch solution, which is far below what particle filter-based estimation of phase IFB needs, the number of searching per epoch is always 200 by using particle filter-based estimation. The average number of searching per epoch is only 9 by using PSO for filtering solution. The ambiguity-fixing success rate is above 96.2% whether for single-epoch solution or filtering solution, and maximal position differences of fixed solution are all below 4 cm.

Regional Ground Surface Mass Variations Inversed by Radial Point-mass Model Method with Spatial Constraints

GUO Feixiao, SUN Zhongmiao, ZHAO Jun, MIAO Yuewang, XIAO Yun

2018, 47(5):  592-599.  doi:10.11947/j.AGCS.2018.20170547

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Radial point-mass model method is the disturbance gravity downward continuation in essence, which is an ill-posed problem. In general, the regularization method is an efficient way to get the reliable solution. To solve this problem, the radial point-mass model method is improved by using Helmert variance component estimation with adding spatial constraints from a practical point of view. Taking South America continent as study area, radial point-mass model method with spatial constraints is verified by experimental results. The experiments results show that the condition number of normal equations is decreasing obviously after adding spatial constraints. The inversion results of radial point-mass model method with spatial constraints are consistent with results of other methods. Furthermore, the radial point-mass model method with spatial constraints provides an alternative way to monitor regional surface mass variations by satellite gravimetry.

Torus Harmonic Analysis and Prediction of Global Ionospheric TEC

FENG Wei, ZHANG Chuanding, WU Xing, WANG Kai

2018, 47(5):  600-610.  doi:10.11947/j.AGCS.2018.20150323

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It is established that an Ionospheric TEC spherical harmonic model based on torus harmonic analysis, by applying the torus harmonic analysis method which is ripe in gravity research into modeling Ionospheric TEC. The characteristics of the proposed model parameters are tested and analyzed in detail. The results show that the proposed model fitting accuracy is excellent. When coefficients truncated to 15th order, the recovery error is less than 4% all the year. The spherical harmonic model has good applicability except the Arctic and the Antarctic area. The characteristics of the proposed spherical harmonic model coefficients is estimated. It is applied that the degree-by-degree residual modeling method, and approaches the regularity of the spherical harmonic coefficients with the use of trend function, power spectrum analysis theory and the ARMA model. The rules of the proposed model coefficient changes are discovered, and then the prediction model is established. Therefore, the prediction based on the model coefficients is achieved. Besides, the accuracy variation problem of prediction coefficients and the data accumulation time of coefficients short-term prediction are analyzed. Finally through the prediction of TEC, the precision of this model is verified.

Change-detection Method for SAR Image Using Adaptive Distance and Fuzzy Topology Optimization-based Fuzzy Clustering

WANG Jianming, SHI Wenzhong, SHAO Pan

2018, 47(5):  611-619.  doi:10.11947/j.AGCS.2018.20160607

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In this paper, a framework of change detection based on adaptive distance and fuzzy topology (FATCD) is proposed for synthetic aperture radar (SAR) imagery. FATCD integrates the characteristics of differenced image and can overcome the limitations of fuzzy C-means (FCM) type algorithms. The framework includes two key steps. First, a new adaptive method is employed to calculate the distances from samples to cluster centers using an adaptive distance function. As a result, the formula of pixel membership evaluation is modified, and the accuracy of the obtained fuzzy membership degree is improved. Then, fuzzy topology is integrated into the maximum membership rule to improve the traditional defuzzification method. In virtue of the above two points, FATCD can enhance the change detection performance of FCM-type algorithms. Experimental results on two different SAR images confirm the effectiveness of the proposed technique.

Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

ZHENG Zhuo, FANG Fang, LIU Yuanyuan, GONG Xi, GUO Mingqiang, LUO Zhongwen

2018, 47(5):  620-630.  doi:10.11947/j.AGCS.2018.20170191

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High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN) method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.

Crowd-sourced Pictures Geo-localization Method Based on 3D Reconstruction

YUAN Yi, CHENG Liang, ZONG Wenwen, LI Shuyi, LI Manchun

2018, 47(5):  631-643.  doi:10.11947/j.AGCS.2018.20170365

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People are increasingly becoming accustomed to taking photos of everyday life in modern cities and uploading them on major photo-sharing social media sites. These sites contain numerous pictures, but many have incomplete or blurred location information. The geo-localization of crowd-sourced pictures enriches the information contained therein, and is applicable to activities such as urban construction, urban landscape analysis, and crime tracking. However, geo-localization faces huge technical challenges. This paper proposes a method for large-scale geo-localization of crowd-sourced pictures. Our approach uses structured, organized Street View images as a reference dataset and employs a three-step strategy of coarse geo-localization by image retrieval, selecting reliable matches by image registration, and fine geo-localization by 3D reconstruction to attach geographic tags to pictures from unidentified sources. 3D reconstruction based on close-range photogrammetry is used to restore the 3D geographical information of the crowd-sourced pictures, resulting in the proposed method improving the median error from 256.7 m to 69.0 m, and the percentage of the geo-localized query pictures under a 50 m error requirement from 17.2% to 43.2% compared with the previous method. Another discovery of the proposed method is that, regarding the causes of reconstruction error, closer distances from the query cameras to the main objects in query pictures tend to produce smaller errors. The proposed method is not limited to small areas, and could be expanded to cities and larger areas owing to its flexible parameters.

An Adaptive Sampling Strategy for Land Cover Change Information and Its Accuracy Characterization

MEI Yingying, ZHANG Jingxiong

2018, 47(5):  644-651.  doi:10.11947/j.AGCS.2018.20170262

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An adaptive sampling strategy is proposed for location-specific characterization of accuracy in land cover change information. The local accuracy characterization strategy was established based on local patterns of land cover change maps (e.g land cover change classes, patch size, heterogeneity and dominance), which include exploring covariates significantly relate to accuracy. Standard error of prediction accuracy was used for identifying the area which needs to improve the reliability of prediction accuracy and locating samples adaptively and progressively. The performance of different sampling methods for accuracy prediction was evaluated at the same testing samples in Wuhan. It was indicated that 100 more training samples selected by adaptive sampling strategy lead to about 50.66% increase in prediction accuracy, as measured by sums-of-squares. In comparison, for random sampling, the same increase in training sample size led to about 17.22% increase in prediction accuracy, as measured by sums-of-squares. This confirms that adaptive sampling strategy improves the sampling efficiency while reduces the uncertainty in local accuracies prediction. Model selection reveals that land cover change classes and dominance are the highest significant covariates.

A Multi-scale Polygonal Object Matching Method Based on MBR Combinatorial Optimization Algorithm

LIU Lingjia, ZHU Daoye, ZHU Xinyan, DING Xiaohui, GUO Wei

2018, 47(5):  652-662.  doi:10.11947/j.AGCS.2018.20160625

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Aiming to solving the problem of positional discrepancy of corresponding objects in multi-scale polygonal object matching and that the potential matching pairs can't be directly identified by the method of areal overlapping, it is proposed that a multi-scale polygonal object matching method based on minimum bounding rectangle combinatorial optimization algorithm. The basic idea of our method is that:①identifying the potential matching pairs of 1:1, 1:N and M:N with combinatorial algorithm and simple shape characteristic;②establishing multi-characteristic artificial neural network model to evaluate these potential matching pairs. The proposed method is demonstrated in the experiment of matching between 1:2000 and 1:10000 polygonal objects of residential buildings and industrial facilities in Zhoushan, Zhejiang Province. The experimental results showed that the proposed matching method show superior performance against a method of area overlapping and artificial neural network. Its precision and recall are 96.5% and 89.0% under the positional discrepancy scenario, and it successfully match 1:0, 1:1,1:N and M:N matching pair.

A Local Polynomial Geographically and Temporally Weight Regression

ZHAO Yangyang, ZHANG Xiaolu, ZHANG Fuhao, QIU Agen, YANG Yi, SHI Lihong, LIU Xiaodong

2018, 47(5):  663-671.  doi:10.11947/j.AGCS.2018.20170674

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Geographically and temporally weight regression (GTWR) estimates regression coefficients and fitted value by weighted least squares (WLS), which under the assumption of the same minimum random variance. As without considering the spatio-temporal heteroscedasticity, it may reduce the accuracy of estimation. Local polynomial estimation is a nonparametric estimation method to eliminate heteroscedasticity in statistics. On the basis of the local polynomial estimation, the local polynomial geographically and weight regression temporally (LPGTWR) approach is proposed in this paper. It reconstructs the spatio-temporal coefficients using three-dimensional Taylor Series in order to satisfy the Gauss-Markov assumption of independent identical distribution. Then estimate the regression coefficients and fitting value using weighted least squares. The experiments use both simulated data and real data to compare LPGTWR, GTWR and local linear-fitting-based geographically weight regression (LGWR). Experiments using simulated data showed that LPGTWR can significantly improve the accuracy of estimation not only in goodness-of-fit of the fitted value, but also in reducing bias of the coefficient estimation and the estimation. It is useful by adopting LPGTWR to eliminate heteroscedasticity effect and improve estimation accuracy.

Phase Center Offset and Phase Center Variation Estimation In-flight for ZY-3 01 and ZY-3 02 Spaceborne GPS Antennas and the Influence on Precision Orbit Determination

YUAN Junjun, ZHAO Chunmei, WU Qiongbao

2018, 47(5):  672-682.  doi:10.11947/j.AGCS.2018.20170703

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ZY-3 01 and ZY-3 02 satellites, as important remote sensing stereoscopic mapping satellites in China, undertake the tasks of production of geographic products, land resource investigation and so on. Precision orbit determination(POD) is a prerequisite for the success of ZY-3 01 and ZY-3 02 missions. Dual-frequency GPS receiver and SLR reflector manufactured by China play significant roles in POD and independent orbits checkout. Although PCO priori values were obtained before satellites launched,by PCO estimation in-flight, this paper analyses the feasibility of PCO in different directions and finds ZY-3 01 and ZY-3 02 SLR RMS checkouts are improved 0.331 mm,0.399 mm respectively. Further, this paper estimates PCV models of ZY-3 01 and ZY-3 02 spaceborne GPS antennas using direct approach and residual approach and their PCV models can reach[-15 mm 15 mm]. Through the use of PCV models(10°×10°), ZY-3 01 orbits SLR checkouts are improved 2.143 mm (direct approach), 1.628 mm (residual approach), orbit accuracy in 3D of overlapping arcs are improved 11.377 mm (direct approach),13.903 mm (residual approach), ZY-3 02 orbits SLR checkouts are improved 0.727 mm (direct approach),0.692 mm (residual approach), orbit accuracy in 3D of overlapping arcs are improved 1.736 mm (direct approach),1.548 mm(residual approach).The effect of PCV model resolution (10°×10°,5°×5°,2°×2°) on POD is further discussed in this paper. After comprehensive consideration of computational efficiency, storage space, increase amplitude and other factors, 5°×5° PCV model by residual approach is the best choice.

A Hybrid Flow Direction Algorithm for Water Routing on DEMs

XIA Yuling, LI Xiaojuan, WANG Tao

2018, 47(5):  683-691.  doi:10.11947/j.AGCS.2018.20170614

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Hydrological information extracted from digital elevation models (DEMs) is the basis of distributed hydrological models. Algorithms determining water flow direction over terrain surface are basis for extracting hydrological information from the DEM. Flow direction and accumulation distributions have a direct effect on catchment area. Single flow direction algorithm is widely used because of its easiness to implement and to track upstream catchment areas. However, the single flow direction (SFD) algorithms tend to produce unnatural parallel flow paths in gentle slope areas. Therefore, multiple flow direction (MFD) algorithms have been proposed to calculate water flow directions. However, MFD algorithms create overlap upstream boundaries of watersheds. Considering applicability of SFD and MFD algorithms, a hybrid approach is proposed to calculate a more reasonable distribution of water under different terrain conditions. First, a template-based terrain classification algorithm is applied to the given DEM which is categorized into five classes:valleys, ridges, passes, gentle slope area and steep slope area with a slope threshold value. A single flow direction algorithm is applied to steep slope, valley and ridge area. A multiple flow direction algorithm is used to determine water flow directions in the gentle slope and passes area. In this paper, two small watersheds in the Linfen Basin of the Loess Plateau and the Sichuan Basin in the Yangtze River Basin were selected as study areas. SRTM DEMs of 30 m and 90 m are used in experiments. The results of hybrid flow direction algorithm are compared with the results of typical SFD and MFD algorithms. The divergent effect is apparently suppressed compared to multi-flow direction algorithms. The occurrence of unnatural parallel drainage lines is decreased compared to the results of single flow direction algorithms. And improvements of hybrid flow direction on DEMs of 30 m is better than 90 m datasets.

Research on Technology and Method of Vector Road Data Aided Inertial Navigation

LI Xiang

2018, 47(5):  692-692.  doi:10.11947/j.AGCS.2018.20170454

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