Acta Geodaetica et Cartographica Sinica

Ubiquitous perception and space mapping

YANG Yuanxi, WANG Jianrong

2023, 52(1): 1-7. doi:10.11947/j.AGCS.2023.20220405

Asbtract ( )

HTML ( )

PDF (4971KB) ( )

References | Related Articles | Metrics

Ubiquitous sensing is the foundation of smart earth and smart city construction. The ubiquitous sensing is divided into active sensing and passive sensing in this paper, and the characteristics of the two kinds of sensing information are analyzed. The former has space-time datum information which is usually regular, accurate and reliable, while the latter usually does not have the support of time and space datum, and the data is scattered, disorderly and inaccurate. The importance of spatio-temporal datum of ubiquitous sensing is discussed in order to discover the valuable knowledge, and the relationships among the ubiquitous sensing and the satellite photogrammetry as well as geographic information are analyzed, and the key technologies of the integration of the ubiquitous sensing information and satellite photogrammetry as well as the geographic information are sorted out.

Preliminary location accuracy assessments of GF-14 stereo mapping satellite without ground control points

WANG Jianrong, YANG Yuanxi, HU Yan, LÜ Yuan, YANG Xiuce, LU Xueliang, CAO Bincai

2023, 52(1): 8-14. doi:10.11947/j.AGCS.2023.20220255

Asbtract ( )

HTML ( )

PDF (10779KB) ( )

References | Related Articles | Metrics

GF-14 is one of the highest mapping accuracy satellites in China, and is adopted advanced multi-load integrated for earth observation technology, which is mainly used for high accuracy location and mapping 1∶10 000 geographic information products on a global wide. In this paper, the payload, ground processing flow and its performance were briefly introduced, then the geometric performance of the satellite images was evaluated using different fields including domestic and foreign areas. As a result, the location accuracy without ground control points (GCPs) of single strip can reach 1.8 m in horizontal and 0.80 m in vertical elevation in domestic areas and 1.76 m in horizontal and 0.82 m in vertical elevation in foreign areas, which can reach the best known level in international optical photogrammetry on location accuracy without GCPs.

High-precision on-orbit geometric calibration of the GF-14 satellite dual-line-array cameras

LU Xueliang, WANG Jianrong, YANG Xiuce, LV Yuan, HU Yan, WEI Yongqiang, CAO Bincai

2023, 52(1): 15-21. doi:10.11947/j.AGCS.2023.20220347

Asbtract ( )

HTML ( )

PDF (3716KB) ( )

References | Related Articles | Metrics

On-orbit geometric calibration is a key link for satellites to achieve high-precision positioning. In this paper, based on the 1∶2000 digital calibration test field in Ningxia, the calibration parameters of the dual-line-array cameras are calculated as a whole by the alternate iteration of forward intersection and backward intersection, and the high-precision on-orbit geometric calibration of the dual-line-array cameras of the GF-14 satellite is achieved. The calibration results were tested by using many testing fields around the world. The test results show that after high-precision geometric calibration, the accuracy of the direct forward intersection of the GF-14 satellite image can reach 2.34 m in plane and 1.97 m in elevation without ground control.

On the calculation and comparative analysis of tropospheric delay from CRA40 product

ZHOU Yaozong, LOU Yidong, ZHANG Weixing, LIANG Hong, SHI Chuang, WU Di, CAO Yunchang

2023, 52(1): 22-31. doi:10.11947/j.AGCS.2023.20210370

Asbtract ( )

HTML ( )

PDF (10104KB) ( )

References | Related Articles | Metrics

As the release of China's first generation 40 a (1979—2018) global atmosphere and land reanalysis (CRA40) by China meteorological administration (CMA) in December 2020, the suitability, method and performance of CRA40 in tropospheric delay ray-tracing is initially investigated in this paper. Tropospheric delays in zenith and 5° elevation directions at 231 international GNSS service (IGS) and 213 crustal movement observation network of China (CMONOC) stations during the year of 2018 from CRA40 and two ECMWF reanalysis (ERA-Interim and ERA5) are ray-traced and evaluated by GNSS zenith total delay (ZTD) products and inter-comparison in globe and China area, respectively. The change law from the CRA40 zenith wet delay (ZWD) and slant wet delay (SWD) accuracy is also analyzed over China. The results show that the CRA40 ZTD difference RMS is about 1.40 cm, and it is slightly better than ERA-Interim in globe and similar to ERA-Interim in China area. By taking the ERA5 slant total delay (STD) as a reference, the CRA40 STD difference RMS is about 10.83 and 12.30 cm in globe and China area, respectively, which is not significantly different from ERA-Interim. The CRA40 ZWD and SWD accuracy over China is related to the climatic types, and the accuracy during winter is obviously better than that during summer in monsoon climate areas.

Monitoring of coastal sedimentation changes based on GNSS and GNSS-IR

WANG Xiaolei, NIU Zijin, HE Xiufeng, LI Runchuan

2023, 52(1): 32-40. doi:10.11947/j.AGCS.2023.20210414

Asbtract ( )

HTML ( )

PDF (10399KB) ( )

References | Related Articles | Metrics

Coastal settlement monitoring usually uses the Global Navigation Satellite System (GNSS) positioning technology to measure at present. However, it only reflects the sediment settlement below the station base, and the settlement information above the station base cannot be obtained. In coastal areas, sediments accumulate rapidly, and settlement changes greatly under compaction and alluvium. Therefore, it is necessary to monitor the settlement above the base in order to obtain the overall coastal settlement information. With the continuous development of GNSS, a new GNSS interactive reflectometry (GNSS-IR) technology has been proved to be able to use multipath effect for reflector height monitoring. Because the base of GNSS station is deep and the base length remains unchanged, the ground height change obtained by GNSS-IR technology can reflect the settlement above the base. Therefore, the paper use GNSS-IR technology to measure the subsidence changes above the base; At the same time, the settlement below the base change is obtained by using GNSS positioning technology, and then the total settlement change is obtained by using GNSS-IR and GNSS positioning technology. The Mississippi River Delta with large sediment thickness is selected as the test area, and the data of FSHS, GRIS and MSIN stations are selected for analysis. The results show that GNSS-IR can be used to measure the settlement rate above the base, and the corrected total settlement rate is equivalent to the relative sea level rise rate, which can better estimate the flood susceptibility and land loss.

Precise positioning method for seafloor geodetic stations based on the temporal variation of sound speed structure

ZHAO Shuang, WANG Zhenjie, NIE Zhixi, HE Kaifei, LIU Huimin, SUN Zhen

2023, 52(1): 41-50. doi:10.11947/j.AGCS.2023.20210326

Asbtract ( )

HTML ( )

PDF (2832KB) ( )

References | Related Articles | Metrics

At present, GNSS-Acoustic (GNSS-A) combined technology is widely used in positioning for seafloor geodetic stations. Based on sound velocity profiles (SVPs) data, the equal gradient acoustic ray-tracing method is applied in high-precision position inversion.However, because of the discreteness of the SVPs used in the forementioned method, it ignores the continuous variation of sound velocity structure in time domain, which worsens the positioning accuracy. In this paper, the time-domain variation of sound speed structure (SSS) has been considered, and the cubic B-spline function is applied to characterize the perturbed sound velocity. Based on the ray-tracing theory, an inversion model of “stepwise iteration & progressive corrections” for both positioning and sound speed information is proposed, which conducts the gradual correction of seafloor geodetic station coordinates and disturbed sound velocity. The practical data were used to test the effectiveness of our method. The results show that the root mean square (RMS) errors of the residual values of the traditional methods without sound velocity correction, based on quadratic polynomial correction and based on cubic B-spline function correction are 1.43, 0.44 and 0.21 ms, respectively. The inversion model with sound velocity correction can effectively eliminate the systematic error caused by the change of SSS, and significantly improve the positioning accuracy of the seafloor geodetic stations.

A multi-baseline PolInSAR forest height inversion method taking into account the ground scattering effects and parametric linear

LIN Dongfang, ZHU Jianjun, LI Zhiwei, FU Haiqiang, LIANG Ji, ZHOU Fangbin, ZHANG Bing

2023, 52(1): 51-60. doi:10.11947/j.AGCS.2023.20200581

Asbtract ( )

HTML ( )

PDF (10624KB) ( )

References | Related Articles | Metrics

Affected by the insufficient information of single baseline observation data, the three-stage method assume the ground-to-volume ratio (GVR) to be zero so as to invert the vegetation height. However, this assumption introduces much biases into the parameter estimates which greatly limit the accuracy of the vegetation height inversion. Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR. Nevertheless, there are many geometry parameters that share similar values in a multi-baseline model, which lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm. To this end, we propose a new step-by-step inversion method applied to the multi-baseline observations. Firstly, an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data, and the regularized estimates of model parameters are obtained by regularization method. Then, the reliable estimates of GVR is determined by the mean square error (MSE) analysis of each regularized parameter estimation. Secondly, using the estimated GVR extracts the pure volume coherence, and then inverting the vegetation heights from the pure volume coherences by least squares estimation. The experimental results show that the new method can improve the vegetation height inversion result effectively. The inversion accuracy is improved by 26% with respect to three-stage method and the conventional solution of multi-baseline. The results have demonstrated the feasibility and effectiveness of the new method.

Scale-adaptive Cauchy robust estimation based on progressive optimization and its applications

LI Jiayuan, ZHANG Yongjun, AI Mingyao, HU Qingwu

2023, 52(1): 61-70. doi:10.11947/j.AGCS.2023.20210415

Asbtract ( )

HTML ( )

PDF (5064KB) ( )

References | Related Articles | Metrics

Robust estimation is a basic technology in geometric processing and survey adjustment. Traditional iteratively reweighted least squares (IRLS) cannot handle problems with high outlier rates (≥50%); Random sampling consensus (RANSAC) type algorithms can only obtain approximate solutions and are time consuming. This paper proposes a progressively optimized scale-adaptive Cauchy robust estimation model. First, a scale parameter is introduced into the typical Cauchy kernel function to control its robustness. Second, the proposed method uses the control parameter to filter out some observations with the large residuals in each iteration and reduce the true outlier rate. Then, a “coarse to fine” IRLS method is used for optimization in a progressive manner. In the iterative process, the control parameter is continuously reduced to improve the robustness. This paper also applies the proposed model in several important tasks of photogrammetry, including mismatch removal, image orientation, and point cloud registration. Extensive experiments show that the proposed model is robust to more than 80% outliers when the gross errors conform to an approximately uniform or random distribution, and is 2~3 orders of magnitude faster than RANSAC.

Main body, edge decomposition and reorganization network for building change detection

YE Yuanxin, SUN Miaomiao, ZHOU Liang, YANG Chao, LIU Tianyi, HAO Siyuan

2023, 52(1): 71-81. doi:10.11947/j.AGCS.2023.20210350

Asbtract ( )

HTML ( )

PDF (9809KB) ( )

References | Related Articles | Metrics

Traditional neural network methods for building change detection tend to produce the saw-tooth boundaries, and they are difficult to accurately identify change boundaries in dense building areas. To address that, this paper proposes a change detection method based on main body, edge decomposition and reorganization network. The proposed method performs change detection by respectively modeling body and edges features of buildings, which is on the basis on the characteristics of strong similarity between the body pixels and weak similarity between the edge pixels. In the definition of the proposed method, we first yield dual-temporal multi-scale difference features using a Siamese ResNet structure, and then separate the body features and edge features of buildings by learning a flow field. Subsequently, a feature optimization structure is designed to refine the body and edge features using the body and edge tags. Finally, the optimized body and edge features are reorganized to generate an end-to-end change detection model. Experiments have been performed by using the publicly available building dataset LEVIR-CD, and the results show that the proposed method can accurately identify the boundaries of changing buildings, and obtain better results compared with the methods based on U-Net network and these combining spatial-temporal attention.

Iterative nearest edge algorithm for aerial image road dataset preparation

YANG Dongfang, ZHAO Jiawei, LI Yongfei, XIAO Peng, YANG Jinglan

2023, 52(1): 82-92. doi:10.11947/j.AGCS.2023.20210331

Asbtract ( )

HTML ( )

PDF (10729KB) ( )

References | Related Articles | Metrics

The quality and efficiency of dataset preparation are common basic issues that are concerned in the field of remote sensing image intelligent processing. Aiming at the difficulty of preparing the road extraction dataset for aerial image, this paper proposes an iterative algorithm for the optimization of the nearest edge feature to prepare the road extraction dataset for aerial image. The algorithm first establishes the homography transformation relationship between aerial image and satellite image through manual assistance, and projects the satellite image onto the aerial image to realize the coarse registration of the satellite image to the aerial image based on the four-point method. Then, the edge detection operator is used to extract the edge features of the image after the rough registration. Finally, the precise registration of the image is completed by the iterative nearest edge optimization algorithm, which improves the preparation accuracy of the road dataset of the aerial image. At the end of the thesis, a road extraction dataset preparation experiment is carried out, which proves that the road dataset preparation method proposed in this paper can significantly improve the efficiency of road dataset preparation while meeting the accuracy requirements of the dataset.

Accurate and lightweight cloud detection method based on cloud and snow coexistence region of high-resolution remote sensing images

ZHANG Guangbin, GAO Xianjun, RAN Shuhao, YANG Yuanwei, LI Lishan, ZHANG Yan

2023, 52(1): 93-107. doi:10.11947/j.AGCS.2023.20210686

Asbtract ( )

HTML ( )

PDF (10440KB) ( )

References | Related Articles | Metrics

Cloud detection is a critical stage in remote sensing image preprocessing. However, when there is snow on the underlying surface of scenes, the general cloud detection methods wouldbe easily affected. As a result, the cloud detection accuracy of these methods would reduce.Furthermore, most available cloud detection datasets are of medium-resolution and do not focus on the cloud and snow coexistence study areas. As a result, a cloud detection dataset has been created and released based on high-resolution cloud-snow coexistence remote sensing images.Meanwhile, this study suggests a convolution neural network termed RDC-Net for cloud detection in high-resolution cloud and snow coexistence images. The RDC-Net contains the reconstructible multiscale feature fusion module for multiscale cloud feature extraction, the dual adaptive feature fusion module for effective cloud feature representation reconstruction, and the controllably deep gradient guidance flows module for unbiased network gradient descent guidance. Benefiting from the above technical components, the network can enhance the robustness of cloud detection in complicated regions and facilitate lightweight deployment of the network. The experimental results show that the RDC-Net has an excellent anti-interference capacity for highlighted ground objects and has outstanding detection performance for thin clouds and clouds over snow. Furthermore, the RDC-Net has fewer parameters and floating-point operations, making it acceptable for industrial production and application.

Segmentation of linear map objects using sequential convolutional neural network

YANG Min, CHEN Guo, LI Lianying, HUANG Haoran, MIAO Jing, YAN Xiongfeng

2023, 52(1): 108-116. doi:10.11947/j.AGCS.2023.20210317

Asbtract ( )

HTML ( )

PDF (6372KB) ( )

References | Related Articles | Metrics

Segmentation of linear objects based on their morphological characteristics is a pivotal pre-step for adaptive generalization. Existing studies mainly use hand-crafted features, such as length, angle, and curvature, to describe the local structures of linear objects, and further to identify different patterns based on manual-defined rules or machine learning methods. In this study, we propose a structural recognition and segmentation method for linear objects using deep learning. First, a linear unit (also known as lixel) composed of two adjacent points is considered as the processing unit, and each linear object is discretized into a two-dimension sequence in which the differences between the horizontal and vertical coordinates of each lixel are encoded. Then, a sequential convolutional neural network (SCNN) is established to predict the types of each lixel. Finally, the segmentation results of different morphological characteristics are obtained by merging the adjacent lixels with the same type using an iteration method. Experiments were conducted on two datasets of 1∶50 k administrative boundaries and 1∶250 k mountain roads, and the consistency ratios of segmentation results were 91.25% and 85.65%, respectively, outperforming the traditional methods based on backpropagation artificial neural network and Naïve Bayes. Overall, our method can effectively avoid the subjectivity that exists when designing the hand-crafted features, and is more adaptable to the segmentation of linear objects with different scales and types.

Linear building pattern recognition combining Gestalt principles and convex polygon decomposition

WEI Zhiwei, DING Su, TONG Ying, CHENG Lu, LIU Yang

2023, 52(1): 117-128. doi:10.11947/j.AGCS.2023.20210286

Asbtract ( )

HTML ( )

PDF (6771KB) ( )

References | Related Articles | Metrics

Building patterns are important local structures characterizing urban areas. Building patterns in previous studies are mostly recognized based on the Gestalt principles in which buildings are considered as a whole. However, human vision is also proved as a parts-based system, and some visually aware patterns may fail to be recognized with the existing methods. This paper first combines Gestalt principles and the convex polygon decomposition to recognize linear patterns. First, the linear patterns are defined based on the triples and Gestalt principles. Second, linear patterns are recognized combining the convex polygon decomposition, and the buildings' orthogonal features are considered in their decomposition. The experimental results show that proposed method is effective to recognize the linear patterns in study area. Compared with the existing methods, the accuracy and recall have increased by 15.7% and 30.5%, respectively.

Non-navigational TIN-DDM automatic generalization algorithm considering topographic forms and terrain features

JI Hongchao, DONG Jian, LI Shujun, ZHANG Zhiqiang, WEI Yuan

2023, 52(1): 129-141. doi:10.11947/j.AGCS.2023.20210367

Asbtract ( )

HTML ( )

PDF (14511KB) ( )

References | Related Articles | Metrics

Aiming at the problems of the current non-navigational TIN-DDM automatic generalization algorithm cannot fully take into account the accuracy of seabed topographic forms recognition and the adequacy of seabed terrain features maintenance, based on the analysis of the concept of TIN-DDM rolling ball transformation, this paper introduces the concept of topographic forms recognition range into the correlation model of TIN-DDM point topographic type and rolling ball radius, and through the micro (macro) scale of TIN-DDM point topography quantitative identification and evaluation, and a non-navigational TIN-DDM automatic generalization algorithm considering topographic forms and features is proposed. First, apply the local Delaunay influence domain to the range constraints of TIN-DDM point topographic forms recognition, and establish an association model of topographic forms and rolling ball radius for micro-topography; Then, the sampling points are classified into the type of topography on a macro scale by analyzing the numerical change law of the critical rolling ball radius, and the correlation model between the topographic forms and the critical rolling ball radius for the macro-topography is established. Finally, using the critical rolling ball radius as the link, the correlation between the topographic type determination of TIN-DDM points and the continuous expression of topographic forms is demonstrated, and a quantitative evaluation index for seabed terrain features of TIN-DDM points is designed for submarine topographic forms recognition, and a TIN-DDM automatic generalization model based on TIN-DDM points to evaluation index is established. The experimental results show that the algorithm can effectively maintain the features of the seabed terrain on the basis of identifying topographic forms.

A quantum evolutionary algorithm for spatial optimization of facility allocation

ZHOU Xinxin, YUAN Linwang, WU Changbin, HAN Peipei, HUANG Jing, YU Zhaoyuan

2023, 52(1): 142-154. doi:10.11947/j.AGCS.2023.20210295

Asbtract ( )

HTML ( )

PDF (6339KB) ( )

References | Related Articles | Metrics

Spatial optimization of facility allocation that aims to form the spatial layout and dispatch plan of facilities is a typical high-dimensional multi-peak NP-Hard combinatorial optimization problem based on geographic information, operational research modeling, and urban planning. It is essential to improve the plan's quality to design and enhance the spatial optimization algorithm of facility allocation. This paper analyzes the critical characteristics in service facility allocation spatial optimization, introduces a real coding quantum evolution algorithm, and mainly establishes tetraploid quantum chromosome coding operator and capacity constraint operator for formulating the quantum evolution algorithm for spatial optimization of facility allocation (QEA-SOFA). Based on the emergency facility spatial optimization experiment, the QEA-SOFA algorithm can effectively improve the equality of the relocation optimization of emergency facilities by 66% compared with the real-coding genetic algorithm. The result demonstrates that the QEA-SOFA algorithm has better global search capability for high-dimensional multi-peak spatial optimization problems and has a more extensive search scale for local search of heterogeneous spatial regions, which reveals that the quantum evolution mechanism has a great deal of potential in solving geospatial optimization problems.

Residents' travel heterogeneity and urban mobility structure

DUAN Xiaoqi, ZHANG Tong, TIAN Youliang, LIU Peilin, WAN Qiao, QIN Yongbin

2023, 52(1): 155-166. doi:10.11947/j.AGCS.2023.20210368

Asbtract ( )

HTML ( )

PDF (8655KB) ( )

References | Related Articles | Metrics

The urban mobility structure could produce dynamic changes in the process of residents' travel. Discovering urban mobility structure has become a hot issue in urban geography and traffic geography, which is of great significance for urban planning and management, line allocation, traffic estimation, etc. Traditional urban structure discovery methods usually consider a single factor, and lack of research in considering the heterogeneity of residents' travel. Based on the auto-encoder model, this paper proposes a representational learning method considering the heterogeneity of residents' travel to detect the urban mobility structure. Our method realizes the fusion of static attribute information and dynamic travel information and introduces the multivariate Gaussian distribution model to complete the whole process from node expression to community expression considering the residents' travel heterogeneity between different communities, finally can achieve more accurate representational results. The experimental results show that the proposed method can more accurately discover the urban mobility structure and the residents' travel patterns. Compared with the traditional methods, it is proved that this method has unique advantages in the mining of residents' travel behavior.

Research on remote sensing image retrieval based on deep learning features

ZHOU Weixun

2023, 52(1): 167-167. doi:10.11947/j.AGCS.2023.20210106

Asbtract ( )

HTML ( )

PDF (722KB) ( )

Related Articles | Metrics

Hierarchical mixture model based high-resolution remote sensing image segmentation method

SHI Xue

2023, 52(1): 168-168. doi:10.11947/j.AGCS.2023.20210147

Asbtract ( )

HTML ( )

PDF (720KB) ( )

Related Articles | Metrics

Research on SLAM based on LiDAR/visual fusion (LV-SLAM)

CHEN Shoubin

2023, 52(1): 169-169. doi:10.11947/j.AGCS.2023.20210184

Asbtract ( )

HTML ( )

PDF (736KB) ( )

Related Articles | Metrics

Research on multi-sensor fusion pedestrian navigation and localization algorithm based on intelligent terminal

YE Junhua

2023, 52(1): 170-170. doi:10.11947/j.AGCS.2023.20210188

Asbtract ( )

HTML ( )

PDF (724KB) ( )

Related Articles | Metrics

Model optimization of multi-system and multi-frequecny un-combine PPP and method of ambiguity resolution

YUE Caiya

2023, 52(1): 171-171. doi:10.11947/j.AGCS.2023.20210189

Asbtract ( )

HTML ( )

PDF (755KB) ( )

Related Articles | Metrics

Research on deep learning models for hyperspectral image classification

PU Shengliang

2023, 52(1): 172-172. doi:10.11947/j.AGCS.2023.20210203

Asbtract ( )

HTML ( )

PDF (729KB) ( )

Related Articles | Metrics

Tectonic deformation and rheological structure around the southern Tibetan Plateau based on the GPS observations

TIAN Zhen

2023, 52(1): 173-173. doi:10.11947/j.AGCS.2023.20210498

Asbtract ( )

HTML ( )

PDF (754KB) ( )

Related Articles | Metrics

Research on the key technologies of GNSS RT-PPP & RTK and their integrated service method

SHU Bao

2023, 52(1): 174-174. doi:10.11947/j.AGCS.2023.20200618

Asbtract ( )

HTML ( )

PDF (737KB) ( )

Related Articles | Metrics

Table of Content