Table of Content

20 October 2015, Volume 44 Issue 10

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The Spherical Wavelet Model and Multiscale Analysis of Characteristics of GPS Velocity Fields in Mainland China

CHENG Pengfei, WEN Hanjiang, SUN Luoqing, CHENG Yingyan, ZHANG Peng, BEI Jinzhong, WANG Hua

2015, 44(10):  1063-1070.  doi:10.11947/j.AGCS.2015.20140141

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The GPS measurements of the Crustal Movement Observation Network in China (CMONC) from 1999 to 2009 were processed, and the velocities of 1068 stations in east and north directions were derived. These velocities were used to establish velocity models in east and north directions within mainland China by using Difference of Gauss (DOG) spherical wavelet. The trend of GPS velocity fields are derived by regional Euler vector method, the residual velocity fields are then used for the spherical wavelet modeling. The scales of wavelets are selected according to distributions of GPS stations. The accuracy of the model is estimated according to the mean square deviation between observations and model, which is ±0.95 mm/a for east direction, and ±0.97 mm/a for north direction in the region with dense stations, while it is ±1.32 mm/a and ±1.30 mm/a respectively for east and north directions in the region with sparse stations. The spherical wavelet modeling of the velocity can also show characteristics at different scales.

An Alteration of Gauss Projection Based on Oblique Deformed Ellipsoid

BIAN Shaofeng, LIU Qiang, LI Zhongmei, LI Houpu

2015, 44(10):  1071-1077.  doi:10.11947/j.AGCS.2015.20140290

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For east-west spanning line, to reduce abscissa value of Gauss projection, the oblique reference ellipsoid was constructed by means of least square method. Via theory of coordinate system transformation, spatial rectangular coordinates of target region in each coordinate system were carried out, and then geodetic coordinates of target region on oblique reference ellipsoid were relatively given. Through ellipsoid transformation, oblique deformed ellipsoid was established to lessen distortion of projection caused by height. Taking one railway for example, it were shown that "An alteration of Gauss projection based on oblique deformed ellipsoid" could greatly deplete abscissa components, avoid zoning of Gauss projection and reduce height effectively, as well as the relevant distortion it caused. Strict mathematical model and clear operation process of the Gauss projection are convenient for programming of relative software, which can be applied in engineering.

Image Centroid Algorithms for Sun Sensors with Super Wide Field of View

ZHAN Yinhu, ZHENG Yong, ZHANG Chao, MA Gaofeng, LUO Yabo

2015, 44(10):  1078-1084.  doi:10.11947/j.AGCS.2015.20150118

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Sun image centroid algorithm is one of the key technologies of celestial navigation using sun sensors, which directly determine the precision of the sensors. Due to the limitation of centroid algorithm for non-circular sun image of the sun sensor of large field of view, firstly, the ellipse fitting algorithm is proposed for solving elliptical or sub-elliptical sun images. Then the spherical circle fitting algorithm is put forward. Based on the projection model and distortion model of the camera, the spherical circle fitting algorithm is used to obtain the edge points of the sun in the object space, and then the centroid of the sun can be determined by fitting the edge points as a spherical circle. In order to estimate the precision of spherical circle fitting algorithm, the centroid of the sun should be projected back to the image space. Theoretically, the spherical circle fitting algorithm is no longer need to take into account the shape of the sun image, the algorithm is more precise. The results of practical sun images demonstrate that the ellipse fitting algorithm is more suitable for the sun image with 70°~80.3° half angle of view, and the mean precision is about 0.075 pixels; the spherical circle fitting algorithm is more suitable for the sun image with a half angle of view larger than 80.3°, and the mean precision is about 0.082 pixels.

Global Empirical Model for Estimating Water Vapor Scale Height

ZHANG Bao, YAO Yibin, XU Chaoqian

2015, 44(10):  1085-1091.  doi:10.11947/j.AGCS.2015.20140664

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Water vapor scale height is an important parameter that reflects the vertical distribution of water vapor and also a key parameter that is usually used to make height correction in GNSS zenith wet delay and tropospheric tomography. Based on the spectral analysis of the time series of water vapor scale height from 2006 to 2012, it is found that the water vapor scale height shows an annual and a semi-annual variation in time. So, the trigonometric functions with an annual and a semi-annual cycle are used to express the time variation of water vapor scale height.And then the European Centre for Medium-range Weather Forecasting (ECMWF) data are used to fit the coefficients of the trigonometric functions at 1°×1° grid points on a global scale. By these methods,a global water vapor scale height model GSH is firstly established, which considers both the time and geographic variations of water vapor scale height. By taking radiosonde data as reference, the GSH model has bias of -0.19 km and rootmean square error (RMSE) of 1.81 km; by taking ECMWF data as reference, the GSH model has bias of 0.04 km and RMSE of 1.52 km. The GSH model shows a relatively even accuracy on a global scale, and could serve the study of GNSS meteorology and provide reference values of water vapor scale height for related meteorological researches.

Bathymetry Prediction Based on the Admittance Theory of Gravity Anomalies

OUYANG Mingda, SUN Zhongmiao, ZHAI Zhenhe, LIU Xiaogang

2015, 44(10):  1092-1099.  doi:10.11947/j.AGCS.2015.20140427

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Based on the admittance theory of gravity anomalies, the method of bathymetry prediction was studied in detail in this paper. In frequency domains, the correlation between gravity anomalies and bathymetry was analyzed, which suggests that the wavelength band correlated strongly was in a range of 20—300 km, this band was appropriated to inverse bathymetry by gravity anomalies. Took the Emperor Chain as an example, the uncompensated admittance model and flexural isostatic admittance model were used for researching, respectively, the included parameter of crust thickness and effective elastic thickness were calculated by the isostatic response function. As the down continuation factor was unstable, a high-cut filter was proposed in the inversion procedure to ensure convergence of series. The results showed that, the admittance theory of gravity anomalies can be used effectively in the bathymetry prediction, the predicted result was real and reliable, the relative precision was approximately 6%, which was equal to ETOPO1 model, and the detailed feature of sea floor which was not showed in ETOPO1 model can also be depicted; the precisions were not so well in areas of ocean mountains intensively distributed because of the complexion of the sea floor.

A Block Adjustment Method of High-resolution Satellite Imagery with Straight Line Constraints

CAO Jinshan, GONG Jianya, YUAN Xiuxiao

2015, 44(10):  1100-1107.  doi:10.11947/j.AGCS.2015.20150023

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Taking "observed straight lines and predicted straight lines in image space being bound to coincide" as a geometric constraint and the rational function model (RFM) as the imaging geometric model of high-resolution satellite imagery (HRSI), a block adjustment method of HRSI with straight line constraintsis proposed. For the proposed method, the control straight line (CSL) in image space should be correspondent with the one in object space while the image point and the ground point on the lines are not necessarily correspondent. Two IKONOS images covering San Diego area, two QuickBird images covering Spokane area and two SPOT-5 images covering Provence area, respectively, were used. The experimental results showed that the proposed method can take full advantage of the control information in the form of linear features. Systematic errors in the rational polynomial coefficients (RPCs) can be compensated effectively. After block adjustment, both the planimetric and height accuracies of the IKONOS, QuickBird and SPOT-5 images reach better than 1 pixel.

A Seamline Optimization Approach Based on Watershed Segmentation for Aerial Image Mosaicking

YUAN Shenggu, WANG Mi, PAN Jun, HU Fen, LI Dongyang

2015, 44(10):  1108-1116.  doi:10.11947/j.AGCS.2015.20150088

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Seamline optimization is a key step in the process of aerial image seamless mosaicking.This paper presents a novel algorithm of seamline optimization for aerial image mosaicking by adaptive marker-based watershed segmentation.The preferred region is determined by the difference of the region achieved by adaptive marker-based watershed segmentation. Then, the minimum binary heap Dijkstra's algorithm is adopted to determine the final seamlines in the preferred region. The experimental results show that the seamline determined by our method can avoid crossing obvious stand-alone objects. Compared with other algorithms,our method has higher feasibility and higher speed.

Measure of Information Content of Remotely Sensed Images Accounting for Spatial Correlation

ZHANG Ying, ZHANG Jingxiong

2015, 44(10):  1117-1124.  doi:10.11947/j.AGCS.2015.20140417

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A measure is proposed based on the information theory and geostatistics to evaluate information content in remotely sensed images. The method is based on the additive noise model and maximum mutual information.These factors affecting the information content have been taken into account, such as noise, spatial correlation and so on. It is suitable for measuring the information content in optical images that have robust spatial correlation with different land cover types. An experiment was performed on a Landsat TM image with three different kinds of land cover types (city, farmland and mountain). The result shows that city has the most information content. It also proves that there is a log positive correlation between information content and the variance of the images.

Fast and Intelligent Seamline Detection for Orthoimage Mosaicking Based on Minimum Spanning Tree

CHEN Jiyi, XU Biao, ZHANG Li, AI Haibin, DU Quanye

2015, 44(10):  1125-1131.  doi:10.11947/j.AGCS.2015.20140467

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A method of fast and intelligent seamline detection is presented that based on minimum spanning tree for high resolution orthoimage mosaicking. The image gradient and difference of homonymy pixels in the overlap area are calculated to build the differential image, which is deemed as a weighted undirected graph. According to the Bottleneck model, the optimal seamline is detected on the differential image by finding the minimum spanning tree of the weighted undirected graph. This method discards the conventional iterative process, thus achieves high speed. Experiment results illustrate the value of the proposed method which achieves great efficiency and guarantees the quality of the seamlines at the same time.

An Matching Method for Vehicle-borne Panoramic Image Sequence Based on Adaptive Structure from Motion Feature

ZHANG Zhengpeng, JIANG Wanshou, ZHANG Jing

2015, 44(10):  1132-1141.  doi:10.11947/j.AGCS.2015.20140622

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Panoramic image matching method with the constraint condition of local structure from motion similarity feature is an important method, the process requires multivariable kernel density estimations for the structure from motion feature used nonparametric mean shift. Proper selection of the kernel bandwidth is a critical step for convergence speed and accuracy of matching method. Variable bandwidth with adaptive structure from motion feature for panoramic image matching method has been proposed in this work. First the bandwidth matrix is defined using the locally adaptive spatial structure of the sampling point in spatial domain and optical flow domain. The relaxation diffusion process of structure from motion similarity feature is described by distance weighting method of local optical flow feature vector. Then the expression form of adaptive multivariate kernel density function is given out, and discusses the solution of the mean shift vector, termination conditions, and the seed point selection method. The final fusions of multi-scale SIFT the features and structure features to establish a unified panoramic image matching framework. The sphere panoramic images from vehicle-borne mobile measurement system are chosen such that a comparison analysis between fixed bandwidth and adaptive bandwidth is carried out in detail. The results show that adaptive bandwidth is good for case with the inlier ratio changes and the object space scale changes. The proposed method can realize the adaptive similarity measure of structure from motion feature, improves the correct matching points and matching rate, experimental results have shown our method to be robust.

Object-oriented Change Detection for Remote Sensing Images Based on Multi-scale Fusion

FENG Wenqing, ZHANG Yongjun

2015, 44(10):  1142-1151.  doi:10.11947/j.AGCS.2015.20140260

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In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects which have different sizes; then, according to the features of the objects, the method of change vector analysis is used to obtain the change detection results of various scales. In order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

Multi-scale Clustering of Points Synthetically Considering Lines and Polygons Distribution

YU Li, GAN Shu, YUAN Xiping, YANG Minglong

2015, 44(10):  1152-1159.  doi:10.11947/j.AGCS.2015.20150136

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Considering the complexity and discontinuity of spatial data distribution, a clustering algorithm of points was proposed. To accurately identify and express the spatial correlation among points,lines and polygons, a Voronoi diagram that is generated by all spatial features is introduced. According to the distribution characteristics of point's position, an area threshold used to control clustering granularity was calculated. Meanwhile, judging scale convergence by constant area threshold, the algorithm classifies spatial features based on multi-scale, with an O(n log n) running time.Results indicate that spatial scale converges self-adaptively according with distribution of points.Without the custom parameters, the algorithm capable to discover arbitrary shape clusters which be bound by lines and polygons, and is robust for outliers.

Modeling Uncertainty of Directed Movement via Markov Chains

YIN Zhangcai, SUN Huatao, CHEN Xuefei, LIU Qingquan

2015, 44(10):  1160-1166.  doi:10.11947/j.AGCS.2015.20140357

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Probabilistic time geography (PTG) is suggested as an extension of (classical) time geography, in order to present the uncertainty of an agent located at the accessible position by probability. This may provide a quantitative basis for most likely finding an agent at a location. In recent years, PTG based on normal distribution or Brown bridge has been proposed, its variance, however, is irrelevant with the agent's speed or divergent with the increase of the speed; so they are difficult to take into account application pertinence and stability. In this paper, a new method is proposed to model PTG based on Markov chain. Firstly, a bidirectional conditions Markov chain is modeled, the limit of which, when the moving speed is large enough, can be regarded as the Brown bridge, thus has the characteristics of digital stability. Then, the directed movement is mapped to Markov chains. The essential part is to build step length, the state space and transfer matrix of Markov chain according to the space and time position of directional movement, movement speed information, to make sure the Markov chain related to the movement speed. Finally, calculating continuously the probability distribution of the directed movement at any time by the Markov chains, it can be get the possibility of an agent located at the accessible position. Experimental results show that, the variance based on Markov chains not only is related to speed, but also is tending towards stability with increasing the agent's maximum speed.

Curvature Integration Constrained Map Matching Method for GPS Floating Car Data

ZENG Zhe, LI Qingquan, ZOU Haixiang, WAN Jianhua

2015, 44(10):  1167-1176.  doi:10.11947/j.AGCS.2015.20140352

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The paper presents a map-matching method which mainly considers the curvature integral value of the curve as a map-matching characteristic for constraining the associated matching between two adjacent GPS track points. Through the implementation of map matching experiments for floating car data on the different conditions of both route categories and sampling intervals, the proposed curvature integration constrained map-matching method could be superior to the classic floating car map matching method when evaluating them by the matching accuracy and stability.

GNSS and RTS Technologies Based Structural Health Monitoring of Bridges

YU Jiayong

2015, 44(10):  1177-1177.  doi:10.11947/j.AGCS.2015.20150017

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Research on Aerial Triangulation Angle/Axis Representation and 3D Reconstruction for Vehicle-borne Street-level Image Sequence

XU Zhenliang

2015, 44(10):  1178-1178.  doi:10.11947/j.AGCS.2015.20150113

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GNSS Kinematic Position and Velocity Determination for Airborne Gravimetry

HE Kaifei

2015, 44(10):  1179-1179.  doi:10.11947/j.AGCS.2015.20150133

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Real Time Monitoring of Ground Motion with Observations of High-rate GPS and Strong-motion

TU Rui

2015, 44(10):  1180-1180.  doi:10.11947/j.AGCS.2015.20150093

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