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Table of Content

    20 October 2019, Volume 48 Issue 10
    Geodesy and Navigation
    The MODIS PWV correction based on CMONOC in Chinese mainland
    LIU Bei, WANG Yong, LOU Zesheng, ZHAN Wei
    2019, 48(10):  1207-1215.  doi:10.11947/j.AGCS.2019.20180386
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    It was carried out for calibration of MODIS PWV in different climates in Chinese mainland based on GNSS observations and meteorological data provided by CMONOC. Firstly, it was carried out for the correlation analysis of GNSS PWV and MODIS PWV, based on the different climate types. And then, it was constructed for the correction-model of MODIS PWV by different climate types based on GNSS PWV. It was carried out for improved effect according to the measured GNSS PWV and the interpolation effect comparison before and after the calibration of MODIS PWV. The MODIS PWV correction model of different climate types can be used to effectively improve the precision of MODIS PWV. It can be used in the application of MODIS PWV in short-term weather forecast and InSAR atmospheric correction.
    Quasi real-time monitoring of CE-5 inter-device separation based on same-beam interferometry
    GAO Yunpeng, REN Tianpeng, DU Lan, CHEN Sirui, ZHANG Zhongkai
    2019, 48(10):  1216-1224.  doi:10.11947/j.AGCS.2019.20180351
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    The lunar spacecraft Chang'E-5 includes the orbiter, the returner, the lander and the riser. During the round-moon flight phase, the real-time monitoring of separation between two combinations, the orbiter/returner assembly and the lander/riser assembly, is the key detection section of flight control. It is proposed that a nearly real-time separation monitoring by using very long baseline interferometry (VLBI) technology. Particularly, during the separation process, the state-of-art measuring technique of same-beam interferometry (SBI) can be obtained from the downlink signals transmitted from the different antennas of the two assemblies, and the resulting relative phase delay can improve the relative distance resolution. The Chang'E-3 static test shows that the relative distance between the two antennas of its lander is solved with the accuracy of <0.3 m with the SBI measurements on a single baseline and the average error is about 0.15 m. The simulated Chang'E-5 separation shows that the separation response time based on SBI measurements is determined with double thresholds with a delay of no more than 30 s.
    New algorithm for detecting AO outliers in AR model and its application in the prediction of GPS satellite clock errors
    HAN Songhui, ZHANG Guochao, ZHANG Ning, ZHU Jianqing
    2019, 48(10):  1225-1235.  doi:10.11947/j.AGCS.2019.20180271
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    Based on the EM algorithm, an algorithm for detecting additive outlier in an autoregressive (AR) time series is proposed. The algorithm can fit the AR model and detect the additive outlier at the same time, and it can efficiently prevent the occurrence of masking and swamping.At last, the proposed algorithm is applied to process the data of GPS satellite clock error prediction. The examples verify the effectiveness of the algorithm in detecting the additive outlier and predicting the satellite clock error.
    Effect analysis of the weighting scheme with modified FCM clustering algorithm on precision of SLR orbit determination
    SHAO Fan, WANG Xiaoya, HE Bing, ZHANG Jing
    2019, 48(10):  1236-1243.  doi:10.11947/j.AGCS.2019.20180373
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    As to the problem of reasonable weighting of station observations in the precise orbit determination of satellite laser ranging (SLR), a modified fuzzy c-means(FCM) clustering algorithm is introduced into the determination of the weights of SLR station observations. Based on the SLR global performance report card provided by the International Laser Ranging Service (ILRS), it is performed that a near real-time sliding reweighting of the station, aiming to change the experienced or somewhat arbitrary weights in the SLR data processing. The orbit of satellite LAGEOS 1 from Jan. 2014 to Dec. 2016 is computed from the SLR data. The results show that the clustering carried out considering only the three variables in the SLR global performance report card:LAGEOS normal point volume, LAGEOS normal point RMS, and percentage of LAGEOS normal point accepted can improve the precision of orbit determination and the efficiency of station observations to the maximum extent. For the 365 3-day arcs involved in the calculation, the precision of the 91.46% arc segment is improved, and the average increase is about 3.7 mm. Additionally, the root mean square (RMS) of the observational residual of individual station is also reduced, which is crucial for SLR technology that is moving towards millimeter-scale measurement precision.
    Triggering relations and stress effects analysis of two Mw>6 earthquakes in southwest Taiwan based on InSAR and GPS data
    WANG Leyang, GAO Hua, FENG Guangcai
    2019, 48(10):  1244-1253.  doi:10.11947/j.AGCS.2019.20180587
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    InSAR and GPS have great advantages in seismic research. InSAR can quickly obtain continuous co-seismic deformation observation in a wide range, while GPS has high accuracy and can quickly obtain stable measurement. With the increase of SAR satellites and the shortening of the return period, it is more powerful to study the seismic triggering relationship and stress effects by using InSAR and GPS jointly. On March 4, 2010, and February 6, 2016, two earthquakes with Mw>6.0 occurred successively in southwestern Taiwan, which are called Jiashian earthquake and Meinong earthquake, respectively. Those are two of the three destructive earthquakes that have occurred in the southwestern plain of Taiwan in the last 200 years (the other was the 1946 M 6.1 Hsinhua earthquake). The time and space intervals between Jiashian and Meinong earthquakes are very small. The study of the relationship between them can not only explore the underground structure of the two events but also further understand the triggering relationship between strong earthquakes. In addition, the effect of the surrounding faults after the two events and which faults have high seismic risk are also worth discussing. As no scholar has deeply studied the relationship between the two events and the effect of the surrounding faults, we used the GPS and InSAR coseismic deformation obtained from ALOS to invert the slip distribution model of the Jiashian earthquake. Based on the static Coulomb stress model, the relationship between Jiashian and Meinong earthquake is analyzed. Seven faults in southwestern Taiwan have been constructed and the stress change models of them have been obtained. We analyzed the high earthquake risk area in southwestern Taiwan based on these stress change models. Fault model obtained by InSAR and GPS inversion shows that the fault structures of Jiashian and Meinong events are very similar, both of which are thrust faults with certain strike-slip. The major slip area of the Jiashian event is between 12~16 km which is slightly deep than that of the Meinong event. The maximum slip of the Jiashian event is 0.61 m at about 14 km depth. The moment of the Jiashian event we obtained by linear inversion is 2.27×1018 Nm corresponding to Mw 6.20 which is consistent with the results of USGS (Mw 6.21) and GCMT (Mw 6.3). After Jiashian earthquake, the stress on the causative fault of Meinong event increased greatly, the maximum increment reached 4.0 MPa, and the area of stress increase accounted for about 74% of the total area of the inferred fault. This shows that the Jiashian earthquake has a very obvious acceleration effect on the Meinong earthquake. However, after the Meinong event, the stress of the causative fault of the Jiashian event increased less, and the average increment is only 0.03 MPa. Under the combined effect of the Jiashian and Meinong events, the Zouchen and Hsinhua faults on the west of the Jiashian earthquake have obviously stress accumulated. We believe that Zuochen and Hsinhua faults in southwestern Taiwan are of high risk after Jiashian and Meinong earthquakes, which deserve continuous attention and further study.
    Photogrammetry and Remote Sensing
    Panoramic SLAM for multi-camera rig
    JI Shunping, QIN Zijie
    2019, 48(10):  1254-1265.  doi:10.11947/j.AGCS.2019.20180443
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    Simultaneous localization and mapping (SLAM) is a research hotspot in fields of photogrammetry, computer vision and robotics, and has been widely applied in mobile mapping system, robots, driverless car, etc. This paper presents a fully automated feature based SLAM solution for a panoramic imaging system consisted of multi-camera rig. First, we developed a fisheye camera calibration model for guaranteeing high accurate coordinate transformation between the fisheye camera and the panoramic camera. Second, we imbedded the panoramic camera model into the SLAM process including initialization, local map building, key frame selection, graph optimization and bundle adjustment. In addition, we developed the algorithm in the processes of feature matching, bundle adjustment, frame tracking considering the disadvantages from the large image distortion and long baseline of the panoramic camera system. Experiments are executed on two data sets with more than 8000 panoramic images. Results show that the proposed panoramic SLAM solution achieves automatic camera localization and map construction, and the localization accuracy approaches the GPS reference. With respect to the mainstream SLAM systems based on conventional cameras, such as Mono-SLAM, Stereo-SLAM and RGB-D SLAM, our proposed panoramic SLAM system could serve as a beneficial supplement and supplies a cheap solution for GPS denied localization problem.
    Aircraft detection in remote sensing imagery with multi-scale feature fusion convolutional neural networks
    YAO Qunli, HU Xian, Lei Hong
    2019, 48(10):  1266-1274.  doi:10.11947/j.AGCS.2019.20180398
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    Aircraft detection in remote sensing images (RSIs) is a meaningful task. There are many problems in current detection methods, such as low accuracy in complex background and dense aircraft area, especially for small-scale aircraft. To solve these problems, an end-to-end aircraft detection method named MultDet is proposed in this paper. Based on single shot multibox detector (SSD), a lightweight baseline Network is used to extract multi-scale features for its powerful ability in feature extraction. To obtain the feature maps with enriched representation power, then the multi-scale deconvolution feature fusion block is designed. We add the high-level features with rich semantic information to the low-level features via deconvolution fusion block. In order to locate aircraft of various scales more accurately, a series of aspect ratios of default boxes are set to better match aircraft shapes and combine predictions deduced from feature maps of different layers. The quantitative comparison analysis are carried out on the challenging UCAS-AOD data set. The experimental results demonstrate that the proposed method is accurate and robust for multi-scale aircraft detection, and achieves 94.8% AP(average precision) at the speed of 0.050 0 s/img with the input size 512×512 using a single Nvidia Titan Xp GPU.
    Object detection in optical remote sensing images based on combination of multi-layer feature and context information
    CHEN Ding, WAN Gang, LI Ke
    2019, 48(10):  1275-1284.  doi:10.11947/j.AGCS.2019.20180431
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    Object detection is the basic and key step of remote sensing image analysis. In optical remote sensing images, object detection faced many challenges such as multi-scale and small objects, appearance ambiguity and complicated background. To address these problems, a new method of object detection based on convolutional neural networks (CNN) and hybrid restricted boltzmann machine (HRBM) is proposed. Firstly, the detail-semantic feature fusion network (D-SFN) is designed to extract fusion features from low-level and high-level CNNs, which can make the target representation more distinguishable, especially for small objects. Secondly, context information is incorporated to further boost feature discrimination, which also improves the detection accuracy. Experiments on NWPU datasets show that the proposed method can significantly improve the accuracy of object detection and has certain robustness.
    Object detection in remote sensing imagery based on convolutional neural networks with suitable scale features
    DONG Zhipeng, WANG Mi, LI Deren, WANG Yanli, ZHANG Zhiqi
    2019, 48(10):  1285-1295.  doi:10.11947/j.AGCS.2019.20180393
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    Object detection and recognition in high spatial resolution remote sensing images (HSRI) is an important part of image information automatic extraction, analysis and understanding in high resolution earth observation system. The robustness and universality of traditional object detection and recognition algorithms using artificial design object feature are poor. To solve these problems, object detection and recognition in HSRI based on convolutional neural networks (CNN) with suitable scale features is proposed. Firstly, the suitable scale of the region of interest (ROI) of object is obtained by statistic the scale range of object in HSRI in the process of training and testing of CNN. Then, a CNN framework for object detection and recognition in HSRI is designed according to the suitable object ROI scale. The mean average precision (mAP) of the proposed CNN framework and Faster-RCNN is tested using the WHU-RSone data set. The experimental results show that the mAP of ZF model and VGG-16 model of the proposed CNN framework are 8.17% and 8.31% higher than that of Faster R-CNN ZF model and Faster R-CNN VGG-16 model, respectively. The proposed CNN framework can obtain good object detection and recognition results.
    Cartography and Geoinformation
    Joint AIHS and particle swarm optimization for Pan-sharpening
    CHEN Yingxia, CHEN Yan, LIU Cong
    2019, 48(10):  1296-1304.  doi:10.11947/j.AGCS.2019.20180509
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    Pan-sharpening is a process of obtaining a high spatial and spectral multispectral image (HMS) by combining a low resolution multispectral image (LMS) with a high resolution panchromatic image (PAN). In this paper, a Pan-sharpening method called PAIHS is proposed. It is based on adaptive intensity-hue-saturation (AIHS) transformation, variational Pan-sharpening framework and two assumptions:①pan-sharpened image and original multispectral image (MS) have the same spectral information; ②pan-sharpened image and PAN image contain the same geometric information. The suitable objective function was established, and optimized by particle swarm optimization (PSO) to obtain the optimal control parameters and minimum value, which corresponds to the best Pan-sharpening quality. The experimental results show that the proposed method has high efficiency and reliability, and the obtained performance index is also better than some of the current mainstream fusion methods.
    A vision-aided geo-registration method for outdoor ARGIS in urban environments based on 2D maps
    DENG Chen, YOU Xiong, ZHANG Weiwei, ZHI Meixia
    2019, 48(10):  1305-1319.  doi:10.11947/j.AGCS.2019.20190007
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    The accuracy of the outdoor 6DOF absolute pose obtained by the current portable pose sensor is usually insufficient in urban environments, which makes the geo-registration accuracy of outdoor AR poorly. Aiming at this issue, a method and technical framework for outdoor vision-aided localization is proposed with 2D maps to improve the outdoor ARGIS geo-registration accuracy. Based on the initial pose obtained by the pose sensor, the basic principles of image localization and pose optimization based on 2D maps are expounded in detail. The experimental results show that the proposed method can effectively optimize the initial pose obtained by the pose sensor, and thus improve the geo-registration accuracy of outdoor AR.
    A content-based WMS layer retrieval method combining multiple kernel learning and user feedback
    LI Muxian, GUI Zhipeng, CHENG Xiaoqiang, WU Huayi, QIN Kun
    2019, 48(10):  1320-1330.  doi:10.11947/j.AGCS.2019.20180410
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    To facilitate the discovery and use of geographic information, it is necessary to design an effective retrieval strategy to locate the map layers that customers want from massive WMS resources. Existing text-based WMS retrieval strategies are unable to solve the problems of metadata loss and inconsistency between pictures and metadata text, without considering map content. The visual similarity between maps is used to design a WMS layer retrieval method that combines multi-feature multiple kernel learning and user feedback to help users search for desired WMS layers. Color, shape and texture features are fused by multiple kernel learning to classify and rank layers according to similarity. A feedback mechanism is also established in the retrieval strategy, which is an effective guarantee that improves accuracy by collecting user-marked layers. Various kinds of WMS layers are selected to calculate the precision ration, analyze the time cost, and validate the retrieval feedback mechanism. The experimental results of selected WMS layers verified that the proposed algorithm is fast and highly precise. It can be integrated with existing text-based retrieval and discovery portals of geographic information.
    Representation and curvature analysis of great ellipse on common chart projection plane
    LI Songlin, CHEN Cheng, BIAN Shaofeng, LI Houpu, LIU Qiang
    2019, 48(10):  1331-1338.  doi:10.11947/j.AGCS.2019.20180348
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    By using the space vector method, the equation of great ellipse on ellipsoidal surface only related to the geographical coordinates of the starting and ending points was derived, the parameter equations of great ellipse routes on various projection planes were obtained from the great ellipse equation and the positive solution formulas of the four kinds of common projection. And then the curvature and radius of curvature of great ellipse routes on the four kinds of projection planes were derived. The great ellipse route from London to New York was taken as an example, by drawing the great ellipse route on different projection planes and analyzing the curve of curvature and curvature radius, the conclusion is drawn that the representation of great ellipse route on gnomonic projection plane is straight line, while which of great ellipse route on the other projection planes are curves with curvature changing slightly. The formulas of curvature radius derived in this paper can be used to calculate the "substitution distance" of great ellipse routes, which is convenient to measure and draw the great ellipse routes on the nautical chart with any scale, and improve the efficiency of nautical drawing.
    Summary of PhD Thesis
    Research and implementation of empirical TEC models
    FENG Jiandi
    2019, 48(10):  1339-1339.  doi:10.11947/j.AGCS.2019.20180599
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    Research on the GPS coordinate time series analysis
    MING Feng
    2019, 48(10):  1340-1340.  doi:10.11947/j.AGCS.2019.20190006
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