Table of Content

20 February 2022, Volume 51 Issue 2

Previous Issue    Next Issue

Geodesy and Navigation

The MERSI/FY-3A PWV correction method based on GNSS

ZHAO Qingzhi, DU Zheng, YAO Wanqiang, YAO Yibin

2022, 51(2):  159-168.  doi:10.11947/j.AGCS.2022.20210060

Asbtract ( )   HTML ( )   PDF (6227KB) ( )  

References | Related Articles | Metrics

Accurate water vapor information is of great importance for short-range weather warnings and long-term climate monitoring. A MERSI/FY-3A PWV correction method is proposed in this paper to address the low water vapor accuracy obtained by the Medium-Resolution Spectral Imager (MERSI) of the second generation of Chinese polar-orbit meteorological satellite FY-3A. Firstly, the daily product data were obtained by processing the 5 min product of MERSI/FY-3A and evaluated by using ground-based GNSS and Radiosonde data in China; then, according to the seasonal distribution of PWV, the GNSS-based PWV seasonal calibration model is constructed; finally, a comparison of the calibrated MERSI/FY-3A PWV using Radiosonde data was performed to verify the validity of the proposed method. The results show that the proposed PWV seasonal calibration correction model can effectively improve water vapor accuracy in MERSI/FY-3A 5 min and 10 days products, with an improvement rate of 58.63% and 68.72%, respectively. This method can provide a theoretical foundation for the rapid correction of water vapor in remote sensing.

A real-time estimating algorithm of GLONASS inter-frequency code bias and its application in RTK

XU Longwei, WU Zhongwang, DONG Xurong

2022, 51(2):  169-181.  doi:10.11947/j.AGCS.2022.20200416

Asbtract ( )   HTML ( )   PDF (16133KB) ( )  

References | Related Articles | Metrics

It is difficult to eliminate GLONASS inter frequency code bias (IFCB) by empirical model.In RTK positioning, especially for medium and long-distance heterogeneous baselines that need to take into account atmospheric delay, IFCB will reduce the convergence rate of ambiguity, and even cause incorrect ambiguity solutions.In this paper, a real-time estimation algorithm of inter-station IFCB is proposed. The new algorithm origins from the classical double differenced Hatch-Melbourne-Wübbena (HMW) combination and ionospheric free combination, can obtain precise IFCB after a short period of filtering. The experiment results show that IFCB between stations may up to several nanoseconds and are stable for a long time. As a ratio 3:5 of the prior error of GPS/GLONASS observations, the uncorrected IFCB may cause the performance of GPS/GLONASS RTK positioning worse than that of single GPS. The proposed algorithm can effectively mitigate the negative influence of IFCB, including the accuracy of ambiguity floating solutions, the convergence speed and fixed rates of RTK positioning results. For some baselines, the time to first fixed of RTK positioning accelerate from 9.2 s to 2.1 s, and the fixed solution ratios enhance from 84.5% to 97.9%.

Decentralized extend information filter for cooperative localization of UUVs

DU Zhenqiang, CHAI Hongzhou, XIANG Minzhi, ZHANG Fan, HUANG Ziru, ZHU Huawei

2022, 51(2):  182-191.  doi:10.11947/j.AGCS.2022.20210144

Asbtract ( )   HTML ( )   PDF (4429KB) ( )  

References | Related Articles | Metrics

Compared with the single UUV, the cooperative work of unmanned underwater vehicle (UUV) can expand the sensing range and accomplish complex tasks.Due to the complexity of the underwater environment and the limitation of UUV sensors, the huge real-time communication required by the traditional Kalman filtering method is difficult to realize in the underwater environment,which makes the result of current cooperative localization is not rigorous. To solve the problem, a new decentralized extend information filter method for UUVs cooperative localization is proposed. Based on the rigorous theory, the distributed cooperative localization of UUVs is realized.Each UUV establishes its own state chain according to the local sensor data, broadcasts its observation information, and cooperates to complete the Cholesky correction. The consistency between the proposed decentralized filter and centralized filter is proved, and the comparison experiment between the new method and the traditional method is carried out.Theoretical simulation analysis shows that,compared with the traditional methods that the observation updating of the single UUV or the two UUVs will result in the observation updating of the whole UUVs, the new method realizes the observation updating only related to the UUVs that directly involved in the observation.The proposed method reduces the communication payloads and has good expansibility for observation information.

Internal calibration method of GOCE gravity gradients

PAN Juanxia, ZOU Xiancai

2022, 51(2):  192-200.  doi:10.11947/j.AGCS.2022.20210067

Asbtract ( )   HTML ( )   PDF (10166KB) ( )  

References | Related Articles | Metrics

The accurate calibration of the GOCE gravity gradiometer is one of the premises for determining the earth's gravity field model with high precision. L1b dataset of GOCE gradiometer and star sensors are used in the internal calibration. The combination of different star sensors by least-squares adjustment can prevent the propagation of the less accurate component due to the reference frame transformation, thus the accuracy of angular rates used by internal calibration can be improved. In this paper, GOCE data in November 2009 are used to verify the ESA's calibration method. On this foundation, considering the rotation matrices between star sensors and gradiometer are time-varying,improved calibration model is presented by using parameters of the rotation matrices. The analysis shows that the parameters are about 100 arcseconds with a liner drift of 3~30 arcseconds in this month. Based on ESA's internal calibration model considering parameters of three accelerometer pairs, a calibration by using transformation matrix from star sensors to gradiometer and the parameters of three accelerometer pairs is presented in this paper. The accuracy of gravity gradients after calibration shows the effectiveness of this method below frequency of 0.005 Hz. Possible developments of GOCE gradiometer calibration based on this method are discussed in this paper which provides foundation for processing of GOCE and other gravity satellites.

Sea level estimation using the combination of GNSS observations

WANG Jie, WANG Nazi, XU Tianhe, GAO Fan, HE Yunqiao

2022, 51(2):  201-211.  doi:10.11947/j.AGCS.2022.20200367

Asbtract ( )   HTML ( )   PDF (6000KB) ( )  

References | Related Articles | Metrics

Comparing with tide gauge, GNSS-IR is used to monitor the sea level at low-cost, and the measurements are not susceptible to crustal subsidence. Moreover, sea level can be retrieved using the data provided by the existing coastal continuously operating reference stations (CORS).Signal-to-noise ratio (SNR) values provided by high-precision geodetic GNSS equipment, are the usual observations for GNSS-IR sea level estimation, however, this observations are not always exist, especially in early GNSS files. Fortunately, the classical observations-carrier phase and the code phase-also contains the information of sea surface height. Therefore, this paper aims to realize GNSS-IR sea level estimation based on two combinations of code pseudorange and carrier phase. In this paper, simulation data is used to prove that the accuracy of the GNSS-IR sea level measurements based on the former combination is affected by the residual of ionospheric delay, while the latter combination can avoid the influence of this error term. In order to verify the effectiveness of the used methods, different observations of the Global Positioning System (GPS) and BeiDou Satellite navigation system (BDS), which are obtained from the station installed at Weihai coastal trestle were processed and analyzed. The results show that there exists good agreement between the sea level results of proposed method and that recorded by an in-situ radar altimeter, and correlation coefficient is better than 85%. The experimental results show that the two combination methods of code pseudorange and carrier phase both can be used for GNSS-IR sea level estimation. In addition, because GNSS-IR sea level measurements are affected by various error terms, the inversion accuracy is low, so that the superiority of the latter combination in avoiding ionospheric delay residuals is not clearly shown. The proposed methods increases the diversity of sea level estimation methods, and provides more feasibility for sea level estimation using GNSS reflectometry technology.

Photogrammetry and Remote Sensing

Advanced quaternion unscented Kalman filter based on SLAM of mobile robot pose estimation

ZHAO Leyang, YAN Li

2022, 51(2):  212-223.  doi:10.11947/j.AGCS.2022.20210082

Asbtract ( )   HTML ( )   PDF (4625KB) ( )  

References | Related Articles | Metrics

In automatic motion controlled mobile robot system, the estimation and correction of its own pose is very crucial for the motion of robot. Kalman filter is a classical method to solve the problem of simultaneous localization and mapping (SLAM) in robot system. Compared with Kalman filter, unscented Kalman filter (UKF) uses nonlinear model directly, avoids operation of Jacobian matrix of complex nonlinear function. In this paper, based on the unscented Kalman filter, sigma points are selected by square root decomposition of prior covariance, and then weighted mean and covariance are calculated. In addition, Quaternion is used to represent attitude of robot, and quaternion vector is converted to rotation space for matrix operation. According to the characteristic of square root decomposition and quaternion vector, a quaternion square root unscented Kalman filter is proposed. By comparing the robot poses estimation results on quaternion square root unscented Kalman filter (QSR-UKF), square root unscented Kalman filter (SR-UKF) and extended Kalman filter (EKF), the simulation results show that the proposed QSR-UKF method is effective.

Classification of high spatial resolution remote sensing imagery based on object-oriented multi-scale weighted sparse representation

HONG Liang, FENG Yafei, PENG Shuangyun, CHU Sensen

2022, 51(2):  224-237.  doi:10.11947/j.AGCS.2022.20190290

Asbtract ( )   HTML ( )   PDF (36474KB) ( )  

References | Related Articles | Metrics

In this paper, according to the multi-scale advantage for high spatial resolution remote sensing imagery and the influence difference among multi-scale objects for classification, the objected-oriented multi-scale weighted sparse representation classification algorithm is proposed by taking the advantages of object-based image analysis method and sparse representation classification algorithm. Firstly, the multi-scale segmentation results are obtained and the multi-scale features are extracted by the multi-scale segmentation algorithm; secondly, the object weights in each scale are computed according to multi-scale segmentation quality measure, and the objected-oriented multi-scale weighted sparse representation model is constructed; finally, the two domestic GF-2 high spatial resolution remote sensing images and one high-spatial and spectral resolution dataset (Washington D.C. data) were adopted to verify the proposed algorithm. The experiment results show that the proposed algorithm can obtain the highest classification accuracy with OA and Kappa,efficiently improve classification accuracy at each scale objects, reduce salt and pepper noise in the classification results, and respectively maintain the regional integrity in the large scale objects and the details in the small scale objects comparing with the traditional SVM, pixel sparse representation,single scale and multi-scale sparse representation and object-based deep learning methods.

Detection of damaged buildings based on generative adversarial networks

GE Xiaosan, CHEN Xi, ZHAO Wenzhi, LI Ruixiang

2022, 51(2):  238-247.  doi:10.11947/j.AGCS.2022.20200318

Asbtract ( )   HTML ( )   PDF (7616KB) ( )  

References | Related Articles | Metrics

As one of the most affected hazard-affected bodies in natural disasters, accurate damage information extraction of buildings plays a significant role in post-disaster emergency rescue. Referring to the idea of multi-mode fusion technique, a recursive generative adversarial networks (RS-GAN) method is proposed to automatically detect damaged buildings. In RS-GAN, the workflow of damaged buildings detection is composed of two sub-tasks as follows:building identification before disasters as well as damaged building detection after disasters, which are completed in two GAN branches respectively. Specifically, RS-GAN adds a joint loss function to connect the two GAN branches, making full use of the potential mutual benefit between the two tasks to improve the detection accuracy. In addition, the results of building identification are added to the damaged building detection task to locate potential damaged areas. The method proposed in this paper is an end-to-end model, which can automatically detect damaged buildings without excessive manual intervention. To verify the effect of the RS-GAN model, in this paper, two experiments were set with the Santa Rosa dataset and Missouri respectively. Experimental results show that RS-GAN method has better detection performance compared to other competitive methods, and the overall accuracy and average accuracy on the Santa Rosa data set are 0.90 and 0.86, respectively.

Effects of spatial network on time series InSAR phase unwrapping: take the Delaunay and Dijkstra networks for example

MA Zhangfeng, JIANG Mi, LI Guihua, HUANG Teng

2022, 51(2):  248-257.  doi:10.11947/j.AGCS.2022.20200469

Asbtract ( )   HTML ( )   PDF (15207KB) ( )  

References | Related Articles | Metrics

In time series InSAR phase unwrapping, coherent pixels are required to be fully connected by a spatial network and then ambiguity can be estimated. During the network generation, Delaunay triangulation has been an invariable choice for InSAR community, but its network configuration easily contains the edge of high phase gradient, which leads to the violation of phase continuity assumption. Given that whether the geometry of Delaunay is suitable for phase unwrapping or not is rarely discussed, in this paper we quantitatively discussed the performance of Delaunay triangulation in phase unwrapping and we also proposed a new network through introducing the graph theory to improve the unwrapping accuracy. Experimental results validate that the proposed method can better satisfy the phase continuity assumption, and is superior to the Delaunay network for a reduction of ~33% unclosed interferogram triangle loops. Compared to the previous researches focused on unwrapping methods and the improvement of objective function, this study reveals the importance of the improvement of spatial network to the time series phase unwrapping.

Cartography and Geoinformation

Point process decomposition method for multi-scale spatial co-location pattern mining

DENG Min, CHEN Kaiqi, SHI Yan, CHEN Yuanfang, GUO Yiwen

2022, 51(2):  258-268.  doi:10.11947/j.AGCS.2022.20200548

Asbtract ( )   HTML ( )   PDF (3689KB) ( )  

References | Related Articles | Metrics

Spatial co-location pattern mining aims to discover association rules formed by multiple types of geographic elements or events frequently adjacent to each other, which is the key for understanding the internal occurrence mechanism of complex geographic phenomena. Aiming at the shortcomings of existing spatial colocation pattern mining methods in the effective modeling of geographic data characteristics (such as the multi-scale characteristic), this paper proposes a multi-scale spatial co-location pattern mining method based on point process decomposition. Firstly, the spatial distribution of geographical elements with multiple types is modeled as a mixed spatial point process by constructing a random variable, and a non-parametric statistical index is introduced to discriminate the characteristic scale of the co-location patterns. On this basis, we define a conditional probability density distribution function to mine multi-scale spatial co-location patterns using points process decomposition. The experimental analysis results show that the proposed method can accurately depict the spatial distribution of spatial co-location patterns at different scales, and effectively reduce the subjectivity of artificially setting parameters.

An adaptive building simplification approach based on shape analysis and representation

YAN Xiongfeng, YUAN Tuo, YANG Min, KONG Bo, LIU Pengcheng

2022, 51(2):  269-278.  doi:10.11947/j.AGCS.2022.20210302

Asbtract ( )   HTML ( )   PDF (9327KB) ( )  

References | Related Articles | Metrics

Building simplification is one of the long-standing challenges in cartography. Establishing a hybrid simplification mechanism based on shape characteristics is an effective strategy to adapt to the diversity and complexity of building shapes. However, existing studies mainly focus on local structure analysis or simplified result evaluation, lacking analytical perspective and deep understanding of the overall shapes. This study proposed a shape-adaptive building simplification approach using deep learning. First, a graph convolutional autoencoder was designed to encode the shape features implicated in the boundary of each building. Then, the mapping relationship between the shape encodings and four candidate simplification algorithms was established using a supervised learning model, so as to realize an adaptive mechanism of selecting the appropriate simplification algorithm according to the shape characteristics of the input building. Experimental results show that our approach performs better than the standalone application of existing algorithms in measuring the changes of position, orientation, area, and shape, and have good theoretical and practical significance.

Ontology knowledge reasoning method for multi-source intelligent road selection

GUO Xuan, QIAN Haizhong, WANG Xiao, LIU Junnan, REN Yan, ZHAO Yuzhe, CHEN Guoqing

2022, 51(2):  279-289.  doi:10.11947/j.AGCS.2022.20210168

Asbtract ( )   HTML ( )   PDF (3058KB) ( )  

References | Related Articles | Metrics

In the era of big data, multi-source data is increasing. However, there is a semantic inconsistency among multi-source data, we propose an intelligent road selection method based on ontology knowledge reasoning. In this paper, we use basic scale map as basic case and use navigation data and OSM data as experimental data. Features such as grade, length, degree, closeness and betweenness are calculated based on road stroke, and their concepts are extracted to construct a road selection ontology. In order to correlate basic case with experimental data, conceptual similarity is calculated from semantic feature and numerical feature. Then, ontology and semantic web rule language are used to define road selection rules and reason the process knowledge of cartographic generalization, which realize the automatic selection of multi-source road data. The experiments indicate that our method can effectively eliminate the semantic inconsistency among multi-source data to realize the road intelligent selection in similar areas.

Suitability analysis of graded color schemes for area feature rendering in digital environment

YAO Xiangyu, HUANG Lina, YU Yang

2022, 51(2):  290-300.  doi:10.11947/j.AGCS.2022.20200499

Asbtract ( )   HTML ( )   PDF (4763KB) ( )  

References | Related Articles | Metrics

This work is concerned with appropriate graded color schemes for area feature rendering in digital environment when the value and hue change simultaneously. We designed seven color schemes based on Munsell color harmony order and CIEDE2000 color difference formula, and a visual cognitive experiment was conducted. It is concluded that:① Increasing color distance will lead to higher accuracy of color recognition. ② Compared with scales that has same color distance between classes, the first-increase-then-decrease scale results in better legibility. ③ The distribution of patch area has no significant effect on color recognition. ④ Increase in color distance may decrease color coordination. The first-increase-then-decrease scale performs better while maintaining color coordination, which is recommended for graded color schemes. It also can be extended to maps with different uniformity of patch area.

A point-feature label placement algorithm considering spatial distribution and label correlation

CAO Wen, PENG Feilin, TONG Xiaochong, DAI Haoran, ZHANG Yong

2022, 51(2):  301-311.  doi:10.11947/j.AGCS.2022.20210247

Asbtract ( )   HTML ( )   PDF (1767KB) ( )  

References | Related Articles | Metrics

The problem of Point-Feature Label Placement is one of the difficulties in data visualization. Large correlation and overlap among the labels of dense point features lead to the low efficiency of labeling and unreasonable labeling results. Fully mining the local spatial distribution characteristics and label correlation of dense point features, this paper proposes an automatic point feature label placement algorithm considering spatial distribution and label correlation of point features. Firstly, we build a label association model by mining the spatial distribution characteristics of point features and the label correlation; Secondly, the spatial clustering algorithm based on label association model is used to describe and analyze its global spatial distribution characteristics, which divides a single dataset into several independent sub-datasets to eliminate the interference and ambiguity among independent datasets in the overall solution; Finally, the labeling order rules based on the ascending order of label association model are constructed by using the local spatial distribution characteristics of point feature and the label correlation, which is used to guide the solution of the approximate optimal solution of label placement in the multi-hierarchy metaheuristic algorithm. The experimental results show that:when the label density range from 5% to 40%, the efficiency of the new algorithm is improved by 10.41%~28.92%, and the label quality evaluation value has dropped by 5.5~35.9, which effectively improves efficiency and quality of label placement.

Summary of PhD Thesis

Distinction and inversion of copper and lead concentration in soil in view of frequency domain spectroscopy

FU Pingjie

2022, 51(2):  312-312.  doi:10.11947/j.AGCS.2022.20200417

Asbtract ( )   HTML ( )   PDF (707KB) ( )  

Related Articles | Metrics

Study on the mixed pixel effect on passive microwave snow depth retrieval

LIU Xiaojing

2022, 51(2):  313-313.  doi:10.11947/j.AGCS.2022.20200430

Asbtract ( )   HTML ( )   PDF (690KB) ( )  

Related Articles | Metrics

Research on the surveying data quality control of high-speed railway track control network

YAN Guangfeng

2022, 51(2):  314-314.  doi:10.11947/j.AGCS.2022.20200441

Asbtract ( )   HTML ( )   PDF (710KB) ( )  

Related Articles | Metrics

Research on GNSS time synchronization method based on precise point positioning

Lü Daqian

2022, 51(2):  315-315.  doi:10.11947/j.AGCS.2022.20200458

Asbtract ( )   HTML ( )   PDF (709KB) ( )  

Related Articles | Metrics

Research on hierarchical segmentation method of high-resolution remote sensing image based on minimum spanning tree model

LIN Wenjie

2022, 51(2):  316-316.  doi:10.11947/j.AGCS.2022.20200439

Asbtract ( )   HTML ( )   PDF (692KB) ( )  

Related Articles | Metrics