Acta Geodaetica et Cartographica Sinica

Towards Geo-spatial Information Science in Big Data Era

LI Deren

2016, 45(4): 379-384. doi:10.11947/j.AGCS.2016.20160057

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Since the 1990s, with the advent of worldwide information revolution and the development of internet, geospatial information science have also come of age, which pushed forward the building of digital Earth and cyber city. As we entered the 21st century, with the development and integration of global information technology and industrialization, internet of things and cloud computing came into being, human society enters into the big data era. This article covers the key features (ubiquitous, multi-dimension and dynamics, internet+networking, full automation and real-time, from sensing to recognition, crowdsourcing and VGI, and service-oriented) of geospatial information science in the big data era and addresses the key technical issues (non-linear four dimensional Earth reference frame system, space based enhanced GNSS, space-air and land unified network communication techniques, on board processing techniques for multi-sources image data, smart interface service techniques for space-borne information, space based resource scheduling and network security, design and developing of a payloads based multi-functional satellite platform). That needs to be resolved to provide a new definition of geospatial information science in big data era. Based on the discussion in this paper, the author finally proposes a new definition of geospatial information science (geomatics), i.e. Geomatics is a multiple discipline science and technology which, using a systematic approach, integrates all the means for spatio-temporal data acquisition, information extraction, networked management, knowledge discovering, spatial sensing and recognition, as well as intelligent location based services of any physical objects and human activities around the earth and its environment. Starting from this new definition, geospatial information science will get much more chances and find much more tasks in big data era for generation of smart earth and smart city . Our profession will make great contribution to human sustainable development!

The Pre-earthquake Ionosphere Anomaly of the 2015 Nepal Earthquake

YAO Yibin, ZHAI Changzhi, KONG Jian, LIU Lei

2016, 45(4): 385-395. doi:10.11947/j.AGCS.2016.20150384

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An ionospheric anomaly detection method based on singular spectrum analysis is introduced firstly.With the TEC time sequence of GIM grid points around the Nepal earthquake epicenter, the positive ionospheric anomalies are determined on 23 April around the eastern region of the epicenter. Using the two-dimensional ionospheric anomalies map, further analysis is taken to comfirm the ionospheric positive anomaly area distributing from 25°N to 37.5°N, 90°E to 110°E, and the anomaly time ranging UT9:00 to UT15:00 on 23 April, 2015. The data of crustal movement observation network of China issued to analyze the STEC fluctuation changes of IPP(ionosphere piece piont) trajectories in the abnormal area, and it is found that on 23 April the STEC values of IPP trajectories passing through the abnormal area are obviously larger than the ones a few days after and before the earthquake time, and returned to the normal level after leaving the abnormal area. Lastly, the CIT (computerized ionosphere tomography) method is used to present the 3D ionospheric anomalies distribution, and it is found that, at UT9:00-UT15:00 on 23 April the peak of ionospheric positive anomaly on the eastern region of the epicenter is approximately at (30°N, 115°E), with the altitude ranging from 100 to 500 km. Also the anomalous peak varies with height is consistent with ionosphere density vertical distribution.

GRACE Data-based High Accuracy Global Static Earth's Gravity Field Model

CHEN Qiujie, SHEN Yunzhong, ZHANG Xingfu, CHEN Wu, XU Houze

2016, 45(4): 396-403. doi:10.11947/j.AGCS.2016.20150422

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To recover the highly accurate static earth's gravity field by using GRACE satellite data is one of the hot topics in geodesy. Since linearization errors of dynamic approach quickly increase when extending satellite arc length, we established a modified dynamic approach for processing GRACE orbit and range-rate measurements in this paper, which treated orbit observations of the twin GRACE satellites as approximate values for linearization. Using the GRACE data spanning the period Jan. 2003 to Dec. 2010, containing satellite attitudes, orbits, range-rate, and non-conservative forces, we developed two global static gravity field models. One is the unconstrained solution called Tongji-Dyn01s complete to degree and order 180; the other one is the Tongji-Dyn01k model computed by using Kaula constraint. The comparisons between our models and those latest GRACE-only models (including the AIUB-GRACE03, the GGM05S, the ITSG-Grace2014k and the Tongji-GRACE01) published by different international groups, and the external validations with marine gravity anomalies from DTU13 product and height anomalies from GPS/levelling data, were performed in this study. The results demonstrate that the Tongji-Dyn01s has the same accuracy level with those of the latest GRACE-only models, while the Tongji-Dyn01k model is closer to the EIGEN6C2 than the other GRACE-only models as a whole.

A New Ambiguity Resolution Method Using Combined RNSS-RDSS of BeiDou

ZHAO Jiaojiao, QU Jianghua, YUAN Hong

2016, 45(4): 404-410. doi:10.11947/j.AGCS.2016.20150164

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Ionospheric delay is a major problem in the process of ambiguity resolution over medium and long baselines that the time consuming is barely satisfactory and the success rate is not high. This paper proposes a new ambiguity resolution method which combines the RNSS and RDSS observations of BeiDou to reduce the ionospheric delay. Firstly, two optical virtual observations with small total noise level and ionospheric delay coefficient are selected by analyzing the RNSS and RDSS combination signals. Then, the NL integers of GEO are solved using geometry-independent and ionosphere-free model which are formed by new virtual observations. Finally, the NL integers of non-GEO are solved with known GEO NL integers. This method is verified using simulated data. Test results show that, the new method has higher success rate and less consuming time compared with traditional method.

A Newton Algorithm for Multivariate Total Least Squares Problems

WANG Leyang, ZHAO Yingwen, CHEN Xiaoyong, ZANG Deyan

2016, 45(4): 411-417. doi:10.11947/j.AGCS.2016.20150246

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In order to improve calculation efficiency of parameter estimation, an algorithm for multivariate weighted total least squares adjustment based on Newton method is derived. The relationship between the solution of this algorithm and that of multivariate weighted total least squares adjustment based on Lagrange multipliers method is analyzed. According to propagation of cofactor, 16 computational formulae of cofactor matrices of multivariate total least squares adjustment are also listed. The new algorithm could solve adjustment problems containing correlation between observation matrix and coefficient matrix. And it can also deal with their stochastic elements and deterministic elements with only one cofactor matrix. The results illustrate that the Newton algorithm for multivariate total least squares problems could be practiced and have higher convergence rate.

A Method of Globally Optimal Registration for Multi-view Point Clouds Constrained by Closed-loop Conditions

YAN Li, TAN Junxiang, YANG Yonghao, LI Shaoda

2016, 45(4): 418-424. doi:10.11947/j.AGCS.2016.20150018

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This paper proposes a rigorous registration method of multi-view point clouds constrained by closed-loop conditions for the problems of existing algorithms. In our approach, the point-to-tangent-plane iterative closest point algorithm is used firstly to calculate coordinate transformation parameters of all adjacent point clouds respectively. Then the single-site point cloud is regarded as registration unit and the transformation parameters are considered as random observations to construct conditional equations, and then the transformation parameters can be corrected by conditional adjustments to achieve global optimum. Two practical experiments of point clouds acquired by a terrestrial laser scanner are shown for demonstrating the feasibility and validity of our methods. Experimental results show that the registration accuracy and reliability of the point clouds with sampling interval of millimeter or centimeter level can be improved by increasing the scanning overlap.

Positioning Model and Accuracy Evaluation of Conical Scanning Airborne Laser Bathymetry System

LI Kai, ZHANG Yongsheng, TONG Xiaochong, SHEN Erhua

2016, 45(4): 425-433. doi:10.11947/j.AGCS.2016.20150161

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Conical scanning airborne laser bathymetry system with fixed angle is selected as a research object to deduce the vector equation of laser in the prism, the atmosphere and the water from the internal structure of the laser rangefinder. Then the vector equation is combined with GPS/INS to deduce positioning model of foot laser point in mapping coordinates. The factors that influence the positioning accuracy of the airborne laser bathymetry system are fully considered and comprehensive accuracy evaluation model of conical scanning airborne laser bathymetry system is given with the use of error propagation law. System parameters, indicators which are widely used in the world are used to calculate the positioning accuracy of airborne laser bathymetry system. The main sources of error involved in positioning model are analyzed and discussed.

A Pansharpening Method Based on HCT and Joint Sparse Model

XU Ning, XIAO Xinyao, YOU Hongjian, CAO Yingui

2016, 45(4): 434-441. doi:10.11947/j.AGCS.2016.20150372

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A novel fusion method based on the hyperspherical color transformation (HCT) and joint sparsity model is proposed for decreasing the spectral distortion of fused image further. In the method, an intensity component and angles of each band of the multispectral image is obtained by HCT firstly, and then the intensity component is fused with the panchromatic image through wavelet transform and joint sparsity model. In the joint sparsity model, the redundant and complement information of the different images can be efficiently extracted and employed to yield the high quality results. Finally, the fused multi spectral image is obtained by inverse transforms of wavelet and HCT on the new lower frequency image and the angle components, respectively. Experimental results on Pleiades-1 and WorldView-2 satellites indicate that the proposed method achieves remarkable results.

Bundle Adjustment for Satellite Linear Array Images Based on Total Least Squares

YU Anzhu, JIANG Ting, GUO Wenyue, QIN Jinchun, JIANG Gangwu

2016, 45(4): 442-449. doi:10.11947/j.AGCS.2016.20150354

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Since the coefficient matrix of image point observation equations may contain random error, it is proposed that a bundle adjustment method for satellite linear array CCD imagery based on total least squares. Assuming that both point observation random error and the coefficient matrix random error are independent and identically distributed, a total least squares based bundle adjustment algorithm, which contains both virtual observation equations of exterior elements and error equations of ground control points, has been deduced using Lagrange conditional extremum. The variance of any type of virtual observation equation can be estimated using variance component estimation. Thus the proposed method can handle with adjustment problems with more than one type of virtual observation equation and chose the undetermined coefficient in proposed method using priori information or the ridge mark method, which overcomes the deficiency of existing virtual observation total least squares method and ensures that the adjustment problems can be solved correctly and effectively. Experiments have been taken on both simulative data and real satellite linear array images in two areas. Results indicate that the proposed method can get more accurate solutions than traditional least squares algorithm and recently proposed virtual observation total least squares method. The proposed method can also get more accurate bundle adjustment results when compared to conventional method.

The Three Dimensional Douglas-Peucker Algorithm for Generalization between River Network Line Element and DEM

DOU Shiqing, ZHAO Xuesheng, LIU Chengjun, LIN Yawen, ZHAO Yanqin

2016, 45(4): 450-457. doi:10.11947/j.AGCS.2016.20140584

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At present, the three dimensional Douglas-Peucker (3D_DP) algorithm is mainly used on generalization of a single type of DEM. This paper introduces the "bending adjustment index" to improve the 3D_DP algorithm, and puts forward a new method for generalizing river network and DEM in three-dimensional space. In this method, river network line vector data are extracted into 3D discrete point data sets which are added elevation attributes, and then they are merged with the 3D discrete point data sets of DEM. The generalization operations are made by the improved 3D_DP algorithm after the hierarchical selection of river networks. Through the contrast and analysis of the experimental results, the well experiment results have been achieved. Under the role of bending adjustment index, the overall distribution form of the rivers and the main terrain features can be reserved reasonably on the generalization. The river network and DEM data were generalized under the same simplified factor in this method. It improves the quality of the cartography generalization.

A Space-time Interpolation Method of Missing Data Based on Spatio-temporal Heterogeneity

FAN Zide, GONG Jianya, LIU Bo, LI Jialin, DENG Min

2016, 45(4): 458-465. doi:10.11947/j.AGCS.2016.20150123

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Space-time interpolation is widely used to estimate missing data in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, it is still challenging to model heterogeneity of space-time data in the interpolation model.To overcome this limitation, in this study, a novel space-time interpolation method based on spatio-temporal heterogeneity is proposed to estimate missing data of space-time datasets. Firstly, space partitioning and time slicing of space-time data was implemented. Then the estimates of missing data are computed using space-time surrounding records with heterogeneous spatio-temporal covariance model.Further the weights of space and time are determined using the correlation coefficient and the finally estimates of missing data is combined integrating time and space estimates. Finally, two datasets are selected to verify the accuracy of this method. Experimental results show that the proposed method outperforms the four state-of-the-art methods with higher accuracy and applicability.

Change Detection and Updating by Using Map Overlay for Buildings on Multi-scale Maps

YANG Min, AI Tinghua, YAN Xiongfeng, YANG Wei, ZHOU Xiaodong, ZHOU Qi

2016, 45(4): 466-474. doi:10.11947/j.AGCS.2016.20150302

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This study aims to develop a method of change detection and updating for urban building features at smaller-scale maps from updated larger-scale maps. Firstly, an in-deeper and comprehensive analysis of changes between maps at different times and scales was discussed. Then, a technical framework of change extraction and updating was proposed based on the functions of map overlap and data enrichment. Finally, real-life data were used to verify the effectiveness of the proposed method, and results also showed that our method is flexible and suitable for layer-level updates.

An Adaptive Method for Mining Hierarchical Spatial Co-location Patterns

CAI Jiannan, LIU Qiliang, XU Feng, DENG Min, HE Zhanjun, TANG Jianbo

2016, 45(4): 475-485. doi:10.11947/j.AGCS.2016.20150337

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Mining spatial co-location patterns plays a key role in spatial data mining. Spatial co-location patterns refer to subsets of features whose objects are frequently located in close geographic proximity. Due to spatial heterogeneity, spatial co-location patterns are usually not the same across geographic space. However, existing methods are mainly designed to discover global spatial co-location patterns, and not suitable for detecting regional spatial co-location patterns. On that account, an adaptive method for mining hierarchical spatial co-location patterns is proposed in this paper. Firstly, global spatial co-location patterns are detected and other non-prevalent co-location patterns are identified as candidate regional co-location patterns. Then, for each candidate pattern, adaptive spatial clustering method is used to delineate localities of that pattern in the study area, and participation ratio is utilized to measure the prevalence of the candidate co-location pattern. Finally, an overlap operation is developed to deduce localities of (k+1)-size co-location patterns from localities of k-size co-location patterns. Experiments on both simulated and real-life datasets show that the proposed method is effective for detecting hierarchical spatial co-location patterns.

Improving the Matching Rate of Line Feature by Using Dynamic Simplification

CHEN Jingnan, QIAN Haizhong, WANG Xiao, HE Haiwei, HU Huiming

2016, 45(4): 486-493. doi:10.11947/j.AGCS.2016.20150074

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Vector line feature matching is one of the hot research in the field of spatial data matching. This paper proposes a method of improving the accuracy of line feature matching based on dynamic simplification. Firstly, use the square root law to respectively determine the numeric ranges of the simplification thresholds for the two matching line features; then, let the threshold change by a certain step within this range, and simplify the line features separately. After every simplification is completed, the matching similarity is recalculated and replaced by a higher value so as to attain the maximum similarity. Finally, compare the maximum similarity with the matching threshold to judge if the two line features match. This algorithm is essentially a process which adopts the dynamic simplification to drive the dynamic matching. The dynamic simplification can retain line's main morphological feature, in this way the impact of local details on matching algorithm decreases, accordingly the matching accuracy is improved. The validity and universality of the presented method is proved through experiments and comparative analysis.

Line Simplification of Three-dimensional Drainage Considering Topological Consistency

LIU Minshi, LONG Yi, FEI Lifan

2016, 45(4): 494-501. doi:10.11947/j.AGCS.2016.20150288

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In view of the fact that drainage line simplification using conversional methods is usually hard to keep the three-dimensional characteristics and topological relationships, this paper proposes a new method of three-dimensional drainage line simplification which maintains topological consistency. It firstly expends the conversional D-P algorithm to three-dimensional in order to keep three-dimensional characteristics during the simplification. Then it constructs tree structures for drainage lines to express their topological relations. Finally, it simplifies river lines and reconstructs topological relations of main streams and their branches according to the hierarchical order of water system tree. The experimental results show that this method has a higher accuracy in simplification and can maintain not only three-dimensional shape characteristics of water system but also the topological consistency at river confluences.

Parallel Algorithms for Polygon Overlapping

FAN Junfu

2016, 45(4): 502-502. doi:10.11947/j.AGCS.2016.20150495

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