Table of Content

20 April 2020, Volume 49 Issue 4

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Review

Rethinking ubiquitous mapping in the intelligent age

LIU Jingnan, GUO Wenfei, GUO Chi, GAO Kefu, CUI Jingsong

2020, 49(4):  403-414.  doi:10.11947/j.AGCS.2020.20190539

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The definition and connotation of ubiquitous surveying and mapping are given at first. The differences from the traditional surveying and mapping are analyzed and presented. Since the Internet enables convenient interaction of information between people, the most significant progress of ubiquitous mapping in the Internet age is to meet diverse demands about relations between human beings and the society, as well as human beings and the environment, which means that human beings have become the mapping target. At the same time, ubiquitous mapping also focuses on the dynamic perception of environmental changes, the perception and cognition and corresponding services of the relationship between human beings and the environment. This paper indicates that the Internet cannot meet the demands of coordinated perception to physical world or the coordinated management neither the control of remote wide area due to the virtuality of its position and the too low network time standard. Therefore, the Internet and the Internet of Things shall advance towards the ubiquitous network with the capability of perceiving accurate space-time position. This paper discuss that the ubiquitous network is a perceptive network with space-time characteristics of “Any Time and Any Where” with the evolution of the Internet and the Internet of Things, and is evolving towards “Any Thing and Any Service” with the expansion of the intelligent demands. Currently, only the global satellite navigation system including Beidou, namely GNSS technology, is able to provide the ubiquitous network with space-time position perception and management and control capability in wide area and the global scale. Supported by ubiquitous network, ubiquitous mapping is developing with the characteristics of real-time and accurate space-time perception and control, to realize the perception, cognition, and regulation of land, sea and air network integration, indoor and outdoor integration, and the integration of human beings into physical world and virtual network world as well. As a result, the ubiquitous network will also be the key information infrastructure in the intelligent age. To understand the demands of ubiquitous mapping in the intelligent age, this paper combs through the definition of intelligence, wisdom and artificial intelligence from the perspective of natural intelligence and space-time position. The fundamental, key and coordinated role of ubiquitous mapping is discussed based on the four hot research directions of the new-generation artificial intelligence, including the cross-border integration, human-machine coordination, open collective intelligence and autonomous control, and its application to military, engineering, real-time and high-precision mapping as well as the earthquake early warning. At last, this paper sheds light on the vision of future application trend of ubiquitous mapping to new fields in the intelligent age, such as ubiquitous mapping of the virtual space, construction of digital twin virtual human, and “space and time sovereignty” to national security.

Geodesy and Navigation

Preliminary analyses of the original weighting algorithm of the echelle atomique libre

WU Yiwei

2020, 49(4):  415-422.  doi:10.11947/j.AGCS.2020.20190170

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The echelle atomique libre (EAL) is the basis of international atomic time (TAI). It is a weighted average of several hundred atomic clocks of different laboratories spread worldwide. The weights of the original weighting algorithm of the weighted average algorithm (ALGOS) forming EAL is studied and discussed. The mathematical expectation values of the frequency deviation variances are derived. The mathematical distribution values of the frequency deviation variances are also derived with approximation. These expressions explain some experimental performances. Simulations validate the theoretical analyses.

A dual linear polarization fringe fitting method for VLBI observation

HUANG Yidan, LIU Lei, SHU Fengchun, ZHENG Weimin

2020, 49(4):  423-431.  doi:10.11947/j.AGCS.2020.20190083

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In this paper, we propose a dual linear polarization fringe fitting method which can be used in the next generation VLBI system (VLBI global observing system, VGOS). The legacy geodetic VLBI observation mode is dedicated to the right circular polarization (RCP), which differs from the dual linear polarization adopted in the VGOS system. The algorithm presented in this work consists of the calibration part and combined fringe fitting part. In the calibration part, we derive the intermediate frequency (IF) delay and phase calibration information from each polarization product by carrying out fringe fitting on a strong reference source. Then this information is applied to the target sources. In the combined fringe fitting part, we combine 4 polarization products into the Pseudo-Stokes Intensity and in the meanwhile search for the appropriate differential parallactic angle, so as to maximize the amplitude of the intensity and therefore derive the delay as observable. Compared with single polarization, the combined product yields higher signal-to-noise ratio (SNR) and smaller fringe phase scatter.

An empirical atmospheric weighted mean temperature model considering the lapse rate function for China

HUANG Liangke, PENG Hua, LIU Lilong, LI Chen, KANG Chuanli, XIE Shaofeng

2020, 49(4):  432-442.  doi:10.11947/j.AGCS.2020.20190168

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The atmospheric weighted mean temperature, T_m, plays an important role in the process of retrieving precipitable water vapor from Global Navigation Satellite System (GNSS) signals. Aiming at the characteristics of complex terrain in China,we develop a T_m lapse rate function that considering sophisticated seasonal variations, and then a new grid T_m model for China, named as CT_m, is established using gridded T_m data over an 8-year period from 2007 to 2014 provided by the global geodetic observing system (GGOS) atmosphere.Both gridded T_m data and radiosonde profiles from 2015 are treated as reference values to assess the performance of CT_m. The results are compared with the Bevis formula and the GPT2w model. The results show that the CT_m with the annual bias and RMS error of -0.52 K and 3.28 K when compared with gridded T_m data, respectively. In terms of RMS,the CT_m has improved by approximately 27% and 13% against GPT2w-5 and GPT2w-1, respectively. While the CT_m has the annual bias and RMS error of 0.26 K and 3.75 K against radiosonde data, and which has improved by approximately 21% and 16% against GPT2w-5 and GPT2w-1, respectively,especially in Western China, where the significant performance was observed for CT_m. Besides, the CT_m has RMS_PWV and RMS_PWV/PWV values of 0.29 mm and 1.36% when used to estimate GNSS-PWV. The CT_m model does not require any in situ meteorological parameters, thus, which has potential application for high-precision real-time GNSS-PWV retrieving in China.

Optimization of regularization parameter based on minimum MSE

LIN Dongfang, ZHU Jianjun, FU Haiqiang, ZHANG Bing

2020, 49(4):  443-451.  doi:10.11947/j.AGCS.2020.20190148

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Tikhonov regularization method is widely used in geodesy for ill-posed problems. The regularization parameter is an important factor for regularization method to solve the ill-posed problem. However, it is very difficult to determine an optimal regularization parameter. L-curve method is proposed to determine the feasible regularization parameter, which is well known to be a stable and reliable method. However, the extensive application researches show that the regularization parameter determined by L-curve method often leads to oversmoothed results. As a result, the regularization method cannot effectively improve the estimation accuracy of model parameters. Concerning this issue, this paper analyzes the effectiveness of regularization parameter on MSE (mean square error) of regularized estimation. Then, an MSE calculation method is proposed by using SVD (singular value decomposition) technology. In the method, the MSE is divided into several parts that correspond to the singular values. Therefore, the iterative calculation of MSE is avoided and the reasonable regularization parameter can be determined part to part. Using the reliable parts of MSE, the most useful regularization parameter can be determined to optimize the L-curve determined regularization parameter. Finally, the regularization parameter optimization method is proposed. Numerical example and PolInSAR vegetation inversion experiment are carried out to demonstrate the effectiveness of the regularization parameter optimization method. The results show that the regularization parameter optimization method can greatly improves the model parameter estimation of regularization method.

Inversion of global marine gravity anomalies with vertical deflection method deduced from Laplace equation

ZHANG Shengjun, LI Jiancheng, KONG Xiangxue

2020, 49(4):  452-460.  doi:10.11947/j.AGCS.2020.20190108

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The quality of marine gravity field derived from satellite altimetry mainly relies on denser data coverage, enhanced spatial resolution as well as improved range precision. In this study, a comparison of application effect for several waveform retracking methods is firstly executed on the basis of multi-satellite altimetry dataset sincluding Geosat GM/ERM,ERS-1 GM/ERM, TOPEX/Poseidon,Envisat,Cryosat-2,Jason-1 ERM/GM and SARAL/AltiKa. According to the statistics of along-track standard deviation, the two-step retracker proposed by Sandwell is superior to other retrackers such as MLE-4, threshold, advanced threshold, and β-5 parameter fitting method. Tuned parameters for certain low-pass filtersare given within the resampling procedure for each altimeter mission in order to calculate accurate along-track slopes. Then a 1'×1' global marine gravity field model is inversed based on the remove-restore procedure by introducing the EGM2008 as reference model. The root mean squares (rms) of difference are respectively 3.4 mGal and 1.8 mGal by comparing with DTU13 and SIO V23.1 model. Meanwhile, the comparison with ship-measured data results a RMS range of 4~8 mGal, while better coincidence shows up in typical ocean areas. In summary, both the comparisons indicate that the new model has a comparable accuracy level with DTU13 and V23.1 at designed 1'×1' grid interval.

A method for mitigating GNSS multipath effect based on multi-point hemispherical grid model

WANG Yawei, ZOU Xuan, TANG Weiming, CUI Jianhui, LI Yangyang

2020, 49(4):  461-468.  doi:10.11947/j.AGCS.2020.20190184

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Multipath effect is related to the observational environment of stations, and cannot be eliminated or mitigated by differential algorithm. It is a major factor affecting accuracy and reliability in GPS signal processing. This paper proposes a method to mitigate the multipath effect—MHGM (Multi-point Hemispherical Grid Model). The method divides the hemisphere centered on each station into a grid, and estimates the multipath error at the station based on parametrization of the grid points, which can be applied to different kinds of hardware and software system of GPS data processing and observation environment. The experimental results in this paper show that, MHGM multipath error modeling based on data from observations made improvements in the mean RMS of double-differenced observation residuals averaging about 71.3%, an average increase of 26.9% compared with the traditional sidereal filtering method, the positioning results of 1.7 mm in level and 3.0 mm in altitude are obtained for static observation using real-time kinematic relative positioning mode. MHGM proposed in this paper also can used to assess orientation of error sources around the station, giving guidance which may assist in the physical elimination of sources of multipath error.

Photogrammetry and Remote Sensing

Variational refinement of mesh with line constraint for photogrammetry

DENG Fei, CHEN Xin, YAN Qingsong, QU Yingjie

2020, 49(4):  469-479.  doi:10.11947/j.AGCS.2020.20190255

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In order to solve the problem of that urban 3D reconstruction is too smooth in the edge area with line features, it is proposed a variational refinement of mesh with line constraint. The algorithm takes the initial reconstruction mesh as input and introduces three energy terms. Transforming the refinement problem into energy reduction problem. Firstly, photo-consistency constraints are constructed by combining all image information, and then regularization constraints are added to all the vertices of the mesh. Finally, 3D line constraint is added to energy term. The gradient difference value is obtained by discretizing sum of three weighted energy term to each vertex. Using gradient descent method to make each vertex move along the gradient vector. When the energy no longer decreases or reaches enough iterations, the refined mesh model is obtained. Calculating the coordinate corrections of each vertex by variational refinement iteration method. Thus, vertices naturally migrate to the object edges if any. The results show that the proposed algorithm can preserve the edge features better. Compared with the existing Poisson surface reconstruction algorithm, the quality of mesh is higher and the visual effect is better.

Road marking extraction and semantic correlation based on vehicle-borne laser point cloud

YAO Lianbi, QIN Changcai, ZHANG Shaohua, CHEN Qichao, RUAN Dongxu, NIE Shungen

2020, 49(4):  480-488.  doi:10.11947/j.AGCS.2020.20190241

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At present, automatic driving technology has become one of the development direction of the future intelligent transportation system. The high-precision map, which is an important supplement of the on-board sensors under the condition of shielding or the restriction of observing distance, provides a priori information for high-precision positioning and path planning of the automatic driving with the level of L3 and above. The position and semantic information of the road markings, such as the absolute coordinates of the solid line and the broken line, are the basic components of the high-precision map. In this paper, scan lines are extracted from the vehicle-borne laser point cloud data, and the road surfaces are extracted from scan lines according to the mutation of the geometry of road edge. On this basis, the road surface point cloud image is transformed into raster image with a certain resolution by using the method of inverse distance weighted interpolation, and the grid image is converted into binary image by using the method of adaptive threshold segmentation based on the integral graph. Then the method of the Euclidean clustering is used to extract the road markings point cloud from the binary image. Semantic information can be extracted from the road markings point cloud using the method of the characteristic attribute selection. Finally, semantic association is established between the traffic markings and the traffic regulation.

Line segment fusion method for high-resolution optical satellite image

DAI Jiguang, ZHU Tingting, ZHANG Yilei, WANG Yang, FANG Xinxin

2020, 49(4):  489-498.  doi:10.11947/j.AGCS.2020.20190109

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To solve the problem of line segment breakage in high resolution optical satellite images, a simple line segment fusion method is proposed based on the idea of complementary advantages of line segment extraction results from different methods. Firstly, this paper starts with edge extraction and edge tracking, compares and analyses the experimental results of different methods to verify the necessity of line segment fusion. Secondly, two line segment extraction methods, which are different in edge extraction and edge tracking, are selected as the fusion elements, and Dai method is improved. Thirdly, Phase grouping, endpoint constraints and topological constraints are used to construct line segment matching models of different methods. Finally, a line segment fusion decision-making model is established according to the principle of line segment length priority. Through the analysis of experimental results of several high resolution optical satellite images with different types, sizes and coverage areas,compared with other methods, the proposed method has the advantages of high completeness.

High-resolution remote sensing image semantic segmentation based on semi-supervised full convolution network method

GENG Yanlei, TAO Chao, SHEN Jing, ZOU Zhengrong

2020, 49(4):  499-508.  doi:10.11947/j.AGCS.2020.20190044

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In the field of remote sensing, the method of realizing image semantic segmentation by using a large amount of label image data to supervise training full convolution network will result in expensive label drawing cost, while the use of a small amount of label data would lead to network performance degradation. To solve this problem, this paper proposes a semi-supervised full convolution network based semantic segmentation method for high resolution remote sensing images. Specifically, we explore an ensemble prediction technique to train the end-to-end semantic segmentation network by simultaneously optimizing a standard supervised classification loss on labeled samples along with an additional unsupervised consistence loss term imposed on labeled and unlabeled data. In the experiments, the image data set of Vaihingen in Germany provided by ISPRS and satellite GF-1 data were used, and the experimental results show that the proposed method can effectively improve the network performance degradation caused by using only a small amount of label data.

Comparison of machine learning algorithms based on Sentinel-1A data to detect icebergs

XIAO Xiangwen, SHEN Xiaoyi, KE Changqing, ZHOU Xinghua

2020, 49(4):  509-521.  doi:10.11947/j.AGCS.2020.20190174

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Iceberg detection is of great significance for marine environmental monitoring and safe sailing of vessels. It is an important part of the construction of the Arctic channel and the exploitation of the Arctic. Iceberg detection using synthetic aperture radar (SAR) images has unique advantages. Many machine learning algorithms can be used in the recognition of icebergs in SAR images. In order to maximize the performance of machine learning algorithms, it is necessary to evaluate different machine learning algorithms and their matching feature and feature standardization methods, so as to select the optimal iceberg detection process method. Therefore, based on Sentinel-1A SAR image, this paper uses a variety of machine learning methods, a variety of feature combinations and a variety of feature standardization methods for iceberg detection, and compares the performance differences of each process method. Machine learning algorithms include Bayes classifier (Bayes), back propagation neural network (BPNN), linear discriminant analysis (LDA), random forest (RF) and support vector machine (SVM); feature standardization methods include Min-max standardization, Z-score standardization and log function standardization; data sets are comprised of 969 iceberg and non-iceberg samples with 12 SAR image features, located mainly on the east coast of Greenland. The classification result is measured by the area under the receiver operating characteristic (ROC) curve (AUC). The results show that the AUC value of RF with the best configuration is the highest, reaching 0.945, which is 0.09 higher than worst Bayes. In terms of detection rate, under the case of 80% iceberg recall rate, the non-iceberg recall rate of RF is 92.6%, which is the best, 1.4% higher than the second BPNN, 2.6% higher than the worst Bayes; under the case of 90% iceberg recall rate, the non-iceberg recall rate of BPNN is 87.4%, 0.8% higher than the second RF and 2.7% higher than the worst Bayes. The above results show that it is very important to select the best machine learning algorithm, the best features and feature standardization method for iceberg detection.

Image semantic segmentation and stitching method of traffic monitoring video

LIU Sichao, WU Pengda, ZHAO Zhanjie, LI Chengming

2020, 49(4):  522-532.  doi:10.11947/j.AGCS.2020.20190224

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As the extension of image stitching, video stitching plays an important role in scene monitoring, target recognition and so on. Traditional video stitching methods are mostly suitable for the videos with large overlapping regions and only geometric features of images are considered in feature matching. When dealing with traffic monitoring videos, existing methods often leads to stitching failure or large distortion because of the overlap region between different cameras is small and the angle between the main optical axes is large. Hence, an image semantic segmentation and stitching method of traffic monitoring video is proposed in this paper. First, the edge angular second-order difference histogram algorithm is proposed to recognize the orthophoto image automatically in the multi-video intersection area, and the orthophoto image is used as the stitching background image. Second, the orthophoto image and video image are segmented semantically based on fully convolutional network (FCN), and traffic thematic features are extracted separately. Finally, the traffic thematic features are used as constraints for feature point matching, and each traffic monitoring image is matched to the orthophoto image to realize regional video stitching. The experimental of real video data from a city in Shandong Province show that the proposed method obtain better stitching images for monitoring videos with smaller overlap areas, and effectively improve the accuracy of feature point matching.

Summary of PhD Thesis

Research on change of fractional vegetation cover of alpine grassland and its environmental impact factors on the Qinghai-Tibetan Plateau

CHEN Jianjun

2020, 49(4):  533-533.  doi:10.11947/j.AGCS.2020.20190402

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Studies on glacier mass balance in the High Asia retrieved by ICESat-GLAS data and GRACE time-varying gravity field

WU Hongbo

2020, 49(4):  534-534.  doi:10.11947/j.AGCS.2020.20190187

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Research on the establishment of global tropospheric delay model with high precision and its applications in ground-based GNSS techniques

HU Yufeng

2020, 49(4):  535-535.  doi:10.11947/j.AGCS.2020.20190099

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Global and regional Moho depth recovery from state-of-the-art satellite gravity model

CHEN Wenjin

2020, 49(4):  536-536.  doi:10.11947/j.AGCS.2020.20190414

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