Table of Content

25 September 2022, Volume 0 Issue 9

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Key technologies analysis for digital construction of space bending-torsional steel bridge

LI Jiulin, XU Hao, HE Huibin, LIU Tingyong, LI Qiangqiang

2022, 0(9):  1-5.  doi:10.13474/j.cnki.11-2246.2022.0254

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With the high-quality development of urban economy and environment, as the important element of urban transportation, the appearance design of bridges is more modern. The steel structure bridges with beautiful spatial bending and torsion structures are favored, which poses higher standard requirements and technical challenges for the design, fabrication and lean construction of complex bridges. Manufacturing and lean construction present higher standards and technical challenges. This paper takes the fully digital construction of the Xin Shougang bridge, the world's first example of a cable-stayed steel system bridge with bending and torsional steel towers, as the research object. Through the systematic research and application of key technologies of digital design, green intelligent construction and precise measurement and control, the refined and parametric collaborative design of steel tower segments and main beams has been realized which based on the modeling idea of “skeleton+template”. Segments are characterized by non-uniformly inclined spatial torsion and beams are characterized by variable section. The high-precision manufacturing of bridge components and the high-precision stress-free erection of steel tower segments are ensured through technologies such as adjustable parameters, virtual pre-assembly, and 3D laser scanning.

Circumferential seam detection and analytics of segment misplacement between rings of subway shield tunnels based on featured point cloud of bolt holes

LU Jianjun, LI Wenhai, YAN Zhanglin, BAO Yan, WU Xu, NI Shuxin

2022, 0(9):  6-11,22.  doi:10.13474/j.cnki.11-2246.2022.0255

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Segment misplacement is a common disease that occurs frequently in the whole life cycle of subway shield tunnels. Excessive misalignment may cause huge damages and leakage to the tunnel, which poses a great threat to the durability and safety of the subway tunnel. Existing method uses 3D laser scanning technology to extract cross-sections on both sides of the circumferential seam by determining the position of the circumferential seam for misalignment detection. Unfortunately, existing method still needs to convert the point cloud data into orthophoto images, and then label the image manually. Using such a method is inefficient and the accuracy could be easily affected by the operator. This study proposes a method for detecting circumferential seams of subway shield tunnels based on the featured point cloud of bolt holes. The proposed method make full use of the collected featured point clouds of shield tunnels without generating orthophoto images for detecting the position of circumferential seams accurately and quickly. The authors uses a subway project in Hangzhou as a case study to validate the proposed method. The results show that, compared with the traditional method, the proposed method is highly efficient and satisfies the accuracy requirements of engineering applications.

Quantitative study on spatial distribution characteristics of diseases in shield tunnel of urban rail transit

WANG Ning, REN Chuanbin, JIANG Weiling

2022, 0(9):  12-17.  doi:10.13474/j.cnki.11-2246.2022.0256

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With the continuous construction and operation of subways, China is gradually entering the subway operation and maintenance period, and subway disease detection and operation and maintenance have gradually attracted people's attention. With the increase of subway operation years, the disease also shows an aggravating trend. Obtaining comprehensive information on tunnel diseases through 3D laser scanning technology, and using spatial autocorrelation to analyze the geospatial distribution characteristics of subway tunnel diseases is of great significance for understanding the mechanism of disease formation and disease prevention. Based on the horizontal convergence data obtained by 3D laser scanning of a subway tunnel, the spatial autocorrelation analysis method is used to quantitatively analyze the distribution characteristics of the disease in geographic space, and the relationship with the surrounding hydrogeological environment is analyzed. The results show that the geospatial distribution of tunnel diseases presents a significant positive spatial correlation and spatial agglomeration characteristics, and the serious disease area is closely related to the hydrogeological environment around the tunnel. This paper provides an effective basis for studying the characteristics of the geospatial distribution of tunnel diseases, understanding the law of disease distribution and later disease management.

Track fastener detection method based on decision tree classification and region growth

GAO Hong, WANG Yong, TANG Chao, WANG Xiaojing

2022, 0(9):  18-22.  doi:10.13474/j.cnki.11-2246.2022.0257

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Due to the large amount of data and small size of rail fasteners, the detection of rail fastener diseases is heavy and inefficient. Therefore, a fast rail fastener detection technology is urgently needed. The rapid development of line structure laser technology has the characteristics of high resolution, high precision and high response. In this paper, the line structure laser measurement technology is used to quickly obtain the fine 3D point cloud of rail fasteners, and the decision tree classification and regional growing algorithm are used to analyze the 3D point cloud of the fine fasteners, so as to realize the fast detection of fastener diseases and the calculation of fastener geometric parameters. Using this technology to detect the rail transit fasteners of Guangzhou Line 18, the detection results show that the method has high detection efficiency and accurate detection results.

Application of video recognition and dynamic monitoring technology based on deep learning: taking the rail transit construction project as an example

WU Zhenzhen, TANG Chao, YANG Xiaofei

2022, 0(9):  23-28.  doi:10.13474/j.cnki.11-2246.2022.0258

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Based on the current situation of safety management and informatization construction of urban rail transit construction projects at home and abroad,this paper analyzes the difficulties faced by safety management in the current rail transit construction process and discusses the video recognition method based on Faster R-CNN,which introduces image space features to improve the recognition rate of unsafe behavior. Also,this paper builds the potential strong correlation relationship between the construction environment,equipment dynamic monitoring and hazard data based on the Apriori,so as to improve the efficiency of hazard discovery and disposal.On this basis,the author proposes the architecture of the safety management platform for rail transit construction,and introduces the application practice of the core modules of safety management,including safety risk management and video monitoring.The results show that the algorithm and platform described in this paper can effectively improve the safety information processing efficiency,reduce the overall incidence rate of safety accidents,and provide effective technical support for the safety management of urban rail transit construction.

Rapid detection technology for surface water leakage in subway tunnel

TIAN Youliang, FAN Tingli, TANG Chao

2022, 0(9):  29-33.  doi:10.13474/j.cnki.11-2246.2022.0259

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With the continuous increase of subway operation time and the rise of underground water level, the leakage of subway tunnel is becoming more and more serious, which has seriously affected the safe operation of subway tunnel. The traditional detection method is manual field inspection, which has low efficiency and poor accuracy. The water leakage detection method with high automation, high accuracy and high stability is the key to improve the manual detection method. Therefore, this paper proposes a deep learning method for water leakage detection using mobile laser scanning tunnels. The method consists of the following parts.①Water leakage data set is established by using the obtained tunnel lining point cloud.②Automatic leak detection is carried out by convolutional neural network based on mask region.The test results of Aoti East-Xinglong street of Nanjing metro line 2 show that the proposed method can realize automatic detection and evaluation of tunnel lining water leakage in two-dimensional plane, and provide intuitive display of water leakage information for inspectors.

Analysis and prediction on the structure deformation of cross river shield tunnel

LI Qiangqiang, JIANG Weiling, TANG Chao, XU Hao

2022, 0(9):  34-38.  doi:10.13474/j.cnki.11-2246.2022.0260

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In this paper, the correlation between structural deformation and water level of a shield tunnel is studied by analyzing the converging deformation and settlement data of multi-phase horizontal diameter of a shield tunnel in flood season obtained by 3D laser scanning technology. Discuss convergence deformation of shield tunnel under different water conditions and the trend of roadbed settlement, through the comparison analysis of monitoring data of flood season it is concluded that higher water conditions will cause tunnel horizontal diameter increase convergence deformation and subsidence, water level declines, horizontal diameter convergence deformation showed a trend of regression, and horizontal diameter convergence and sedimentation of shield tunnel reinforcement measures are put forward. Finally, in order to predict the convergence changes of tunnel horizontal diameter, the data of tunnel segment horizontal diameter in the past period were collected, and the gray algorithm program is run by python to predict the horizontal diameter of tunnel segment in the future, realizing the accurate prediction when the convergence accuracy of shield tunnel horizontal diameter is 1 mm.

Analysis of temporal and spatial changes of the central plains urban agglomeration based on luminous remote sensing data

CHENG Jiehai, HU Pan, YUAN Zhanliang

2022, 0(9):  39-44.  doi:10.13474/j.cnki.11-2246.2022.0261

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Based on the “NPP-VIIRS-like” luminous remote sensing data set, this paper uses the improved statistical data comparison method to extract the built-up area of the central plains urban agglomeration, and analyzes the temporal and spatial variation characteristics of the built-up area of the central plains urban agglomeration from 2002 to 2020 in combination with the center of gravity migration index and the typical landscape pattern index. Research shows that: ①The expansion intensity of the built-up areas of the central plains urban agglomeration is first fast and then slow, and the overall trend is declining. The center of gravity of the built-up area finally points to the southeast after several shifts, but it has always been located within the Zhengzhou metropolitan area.②The urban agglomeration in the central plains has developed rapidly. The total area of built-up areas has increased by 1.429 times between 2002 and 2020, and a large number of emerging towns have appeared between 2011 and 2012. After 2014, it has stabilized, and the connection between towns has become more and more close. ③The complexity of the spatial pattern of the built-up areas of the central plains urban agglomeration has increased year by year, and the degree of fragmentation has generally decreased. The expansion rate of the built-up areas in the Zhengzhou metropolitan area is significantly faster than that of the overall built-up areas of the central plains urban agglomeration.

Indoor adherent point cloud segmentation method based on joint optimization of minimal cut and deep learning

QIAN Jianguo, ZHANG Yuqi, TANG Shengjun, WANG Weixi, LI Xiaoming

2022, 0(9):  45-51.  doi:10.13474/j.cnki.11-2246.2022.0262

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With the development of digital city, the demand for 3D point cloud structuring as well as the accuracy requirement of urban 3D model reconstruction is getting higher and higher. How to effectively and accurately segment indoor semantic models and 3D reconstruction is a current hot research issue. Point cloud segmentation classification is an important basis for indoor point cloud structuring, and how to segment the adherent point cloud components accurately and use them for indoor point cloud structuring is a difficult problem in current urban modeling. This paper proposes a segmentation and classification method for indoor adhesion point cloud data, which firstly uses deep learning network to process indoor point cloud data, then classifies the point cloud data with labeled point cloud to get the target labeled point cloud, and uses Euclidean algorithm to cluster and segment the target point cloud, calculates the coordinates of each target centroid and horizontal radius by the enclosing box information of indoor semantic components. Finally, we use point cloud minimization to achieve accurate segmentation of the indoor adherent point cloud. In this paper, three sets of data obtained from indoor scenes are used to evaluate the accuracy and effectiveness of this segmentation method. The experimental results show that the segmentation optimization method proposed in this paper has high accuracy and data integrity.

A density-adaptive building boundary extraction method based on 3D point clouds obtained from oblique photogrammetry

LIU Yuqi, CHEN Guangliang, CAI Yuezhen, LI Minghao, CHEN Dingan, HU Xiaozhong

2022, 0(9):  52-57.  doi:10.13474/j.cnki.11-2246.2022.0263

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To tackle the problems of individual building segmentation, this paper proposes an automatic building boundary segmentation method for point clouds derived from the oblique photogrammetry. First, the ground and noise points are filtered out through the pre-processing stage. Then, the point clouds are voxelized for the segmentation. An improved Otsu method and the distance-based region-growing algorithm are integrated to apply to the voxelized point clouds for the boundary extraction. We verify the proposed method with two datasets captured in the Jiangmen and Zhanjiang of the Guangdong Province. The results show that the segmentation accuracy achieve 87.8% and 92.3% for Jiangmen and Zhanjiang datasets, respectively. This suggests that the proposed method is highly applicable to the building segmentation.

A new and improved method for road extraction from remote sensing images by fusing different scale features

YAN Zhiheng, REN Chao, LI Yi, XU Ninghui, ZHANG Shengguo

2022, 0(9):  58-62.  doi:10.13474/j.cnki.11-2246.2022.0264

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Aiming at the problem of inconspicuous fine road texture features and difficult information extraction in high-resolution remote sensing imagery, a new method of deep learning road extraction fusing different scale features is proposed and implemented. The method firstly introduces a CoT module to build a residual network to extract road features at different scales by making full use of local and global contextual information. Secondly, a feature pyramid attention module is built to fuse different levels of road feature information. Finally, a global attention upsampling module is used to recover road details in conjunction with the global context. The experimental results show that the proposed method is better than the existing methods in terms of recall and intersection ratio, and can extract the road information in remote sensing images more completely and accurately, which improves the efficiency of road extraction.

Object-oriented extraction of Sanya coral reef sediment information

WU Hongrong, ZHU Lanwei, SHI Dong

2022, 0(9):  63-67.  doi:10.13474/j.cnki.11-2246.2022.0265

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Coral reefs are of great significance to the study of marine ecological environment. The ecological environment of coral reefs can be evaluated by analyzing the distribution and health status of benthic materials. In this paper, an object-based image classification method is used to determine the optimal segmentation scale of different landforms through experiments. Among them, the optimal segmentation scale of terrestrial and deep-sea is 150, and the optimal segmentation scale of various benthic substances is 30. Furthermore, Sentinel-2A satellite remote sensing images are used to extract benthic materials from coral reefs in Sanya Coral Reef Nature Reserve, Hainan province, and confusion matrix is used to evaluate the accuracy of extraction results. The results show that the overall classification accuracy of benthic material extraction is 87.91%, and the Kappa coefficient is 0.83. The object-oriented classification method can effectively combine the texture characteristics and spectral characteristics of benthic material of coral reef and make full use of the combination characteristics of different bands of remote sensing image, and the extraction results can provide methodological support for reef protection and management in Sanya.

Observation of faulting slip of Hualian earthquake in Taiwan and kinematic mechanism analysis

LIANG Bin, WEI Guanjun

2022, 0(9):  68-73.  doi:10.13474/j.cnki.11-2246.2022.0266

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The ascending and descending Sentinel-1 SAR imageries are used to extract the co-seismic deformation field accused by 2018 Mw6.4 Hualian earthquake in Taiwan based on the D-InSAR method. The result shows that the maximum surface deformation is about 38.2 cm which belongs to uplift mainly, and the largest displacement difference between the hangingwall and the footwall is 50 cm. We construct the fault slip distribution models of the 2018 and 2021 Hualian earthquakes with the surface deformation obtained by the InSAR observation, and the results indicate that the fault of the 2018 Mw6.4 Hualian earthquake is a concealed west-dipping fault close to the Milun fault, the maximum is 1.8 m dominated by a left-lateral strike-slip movement with a small amount of thrust, the fault rupture propagate to the western erea of the Milun fault, which have an effect on seismicity of the Lingding fault and the Milun fault. The 2021 Hualian Mw6.0 earthquake occurred in the north of the Lingding fault, the maximum slip is 0.38 m a dominated by left-lateral strike-slip, both of two events have the high dip angle. With the redistribution of the static coulomb stress and the M-T diagram of two earthquakes,we find that the 2018 Hualian earthquake have triggered the 2021 Hualian earthquake,the stress transports and accumulats from high latitude to low latitude, the seismicity between the Hualian aera and the offshore remains active in short period,present the characteristics that the small earthquakes occur frequently and birth period of medium-strong earthquakes are short.

Rainfall landslide deformation prediction based on attention mechanism and Bi-LSTM

TANG Feifei, TANG Tianjun, ZHU Hongzhou, HU Chuan, MA Ying, LI Xin

2022, 0(9):  74-79,104.  doi:10.13474/j.cnki.11-2246.2022.0267

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Affected by seasonal rainfall fluctuations and the traction of adjacent points, the landslide displacement shows a step-like change trend. In order to predict the displacement effectively, the attention mechanism is introduced into bidirectional long-short term memory (Bi-LSTM) neural network prediction model in this paper. Firstly, a landslide monitoring cumulative displacement time series model is established to decompose the landslide cumulative displacement into a trend item and a period item. Then, the correlation coefficient among the landslide factor, the trend item and the period item are analyzed, and the polynomial regression is used to fit the trend item. For the period item prediction, the attention mechanism-based Bi-LSTM neural network prediction model is constructed. Taking a landslide data in Chongqing as an example, the experiment result shows that the proposed model has better robust generalization ability and can capture the correlation between different time series data effectively. The average absolute error of prediction accuracy is 0.088 mm, and the average mean square error is 0.042 mm. Compared with common long-short term memory neural network, the model proposed in this paper has higher prediction accuracy.

3D modeling of city-level complex buildings based on cross-around route

WANG Kaiqi, FANG Jun, WANG Zhenlin, GUO Haibin, YANG Zhensheng

2022, 0(9):  80-85.  doi:10.13474/j.cnki.11-2246.2022.0268

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At present, provinces and cities are accelerating the construction of national 3D real scene. Among them, the city-level real 3D modeling has higher accuracy requirements, richer display content and greater workload than the terrain-level. In view of the high and low dislocation and complex structure of the building scene, the improvement effect is not obvious by improving the overlap of UAV routes. There are still many flower deformation areas, which will increase the number of images, time-consuming flight and modeling process, and increase the production cost. Therefore, a 3D modeling method of urban real scene based on UAV cross-around route is proposed. The typical experimental sample area is selected for aerial photography modeling experiment, and the modeling efficiency, quality and accuracy are compared and analyzed with the conventional five-way route aerial photography method. The results show that the cross-around route aerial photography method can greatly reduce the number of images, save the time of aerial triangulation calculation and modeling, and improve the overall modeling efficiency. Moreover, the modeling quality is better and the overall accuracy is higher in the difficult areas such as the roof canopy of the building and the glass window, which meets the requirements of relevant standards and specifications.

The real 3D modeling method of UAV video loop shooting for towering ancient pagodas

ZHANG Maozheng, YAN Ningna, YUAN Yihong, SHANG Lihong, ZHAO Zhenwei

2022, 0(9):  86-92.  doi:10.13474/j.cnki.11-2246.2022.0269

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Aiming at the problem of real 3D modeling of towering ancient pagodas, a unmanned aerial vehicle (UAV) three-phase loop shooting video homogeneous frame modeling method is proposed. A small multi-rotor drone equipped with a single-lens camera is selected, and three phases of high, medium and low are arranged to capture video around the towering ancient pagoda and perform even frame processing. The Chengtian temple pagoda in Xingqing district, Yinchuan city, Ningxia, is selected as the test object for example modeling and compared with the widely used UAV photo-photographic oblique photography modeling method in 3 aspects: modeling efficiency, modeling air-three quality and overall model quality. The results show that the modeling effect of the method is better than the three-dimensional modeling effect of UAV oblique photography. On the basis of optimizing the acquisition process and simplifying the equipment conditions, the integrity of the model is guaranteed, and the modeling efficiency and modeling quality are improved.

BIM modeling of oil pipeline based on RGB-D depth image and LiDAR point cloud

NIU Pengtao, CAO Yi, QIAO Wenbin

2022, 0(9):  93-97,157.  doi:10.13474/j.cnki.11-2246.2022.0270

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Building information modeling (BIM) has been widely used to improve the management efficiency of complex pipeline systems. However, BIM modeling of existing oil pipelines often relies on design drawings or field mapping, which is time-consuming and laborious. Therefore, a BIM reconstruction method for oil pipeline based on RGB-D depth image and LiDAR point cloud data is proposed. Based on the rich semantic information provided by RGB-D image and the precise geometric information of LiDAR point cloud, the RGB image collected by depth camera is segmced to generate 3D semantic map. Then data fusion is realized by point cloud rough matching and precise matching. Finally, the BIM model making method of different structure pipeline components is given. The experimental results show that compared with the previous BIM reconstruction methods of pipelines, this method is more accurate and efficient, which is helpful for petroleum enterprises to implement information management for the metering and transfer stations containing complex pipelines.

A method for determining height difference threshold of 3D building change detection based on normal distribution

LI Rui, ZHOU Xiaoguang, HOU Dongyang

2022, 0(9):  98-104.  doi:10.13474/j.cnki.11-2246.2022.0271

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At present, the height difference threshold determination method in 3D building change detection is highly subjective and poorly generalized. In this paper, an adaptive method for determining height difference thresholds based on normal distribution is proposed. Firstly, based on the theory that the difference between changed and unchanged image elements in 2D change detection obeys normal distribution, the method assumes that the height difference of 2-phase digital surface model(DSM) obeys or approximately obeys normal distribution, and analyzes the distribution of height difference between changed and unchanged regions. Then, the method of calculating the height difference threshold using expectation and standard deviation is proposed based on the Laida criterion. Finally, using sliding window to dynamically calculate the height difference threshold. In two experimental areas, the building change detection results based on the proposed method improve the completeness, correctness and detection quality by 7.2%, 1.5% and 7.8% on average, compared with the empirical threshold method. This indicates that the method has good generality.

The method of bridge deflection outlier detection by fusing multi-sourced surveying data

CHEN Ruizhe, TU Wei, LI Qingquan, GU Yu, ZUO Xiaoqing, GAO Wenwu

2022, 0(9):  105-110.  doi:10.13474/j.cnki.11-2246.2022.0272

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Bridges are one of the most important transportation infrastructures as they guarantee the flow of people and goods, thus it is crucial for monitoring bridge safety. However, due to their intrinsic construction load as well as the extrinsic traffic load and environmental temperature, bridge deflection varies constantly. Moreover, the deflection outlier will cause a huge safety risk for bridges. The present detection methods for bridge deflection outlier still exist some limitations in the lack of synthetically considering both the extrinsic impact factors and the intrinsic variation features. Therefore, the paper proposes the detection method for bridge deflection outlier by fusing multi-sourced surveying data. It calculates and fuses the multi-sourced features based on temperature, bridge traffic load, and bridge deflection data. Besides, it utilizes the random forest model to judge whether the deflection is the outlier. The experimental results illustrate that the proposed method could get a good performance of the accuracy of 88.18%. In addition, the method's performance exceeds other classical machine learning models. In summary, the proposed method could help the bridge administrators detect the bridge deflection outlier to eliminate the safety risks, and further promote their maintenance and administration levels.

Updating entities for terrain-level 3D real scene by UAV laser point cloud data

LIU Huaguang, WANG Junjun, KOU Yuan

2022, 0(9):  111-114.  doi:10.13474/j.cnki.11-2246.2022.0273

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With the continuous development of 3D real scene construction, the requirement for the current situation of entities for terrain-level 3D real scene is increasing day by day. In order to solve the timeliness and high efficiency of geographical scene update, this paper uses unmanned aerial vehicle (UAV) to obtain the laser-point cloud data onto the changed pattern monitored by remote sensing satellites. TerraScan point cloud classification filter algorithm is used to extract ground points in batches, and CloudCompare Laplacian smoothing algorithm is used to smooth and eliminate discrete non-ground points. DEM is output, and finally entities for terrain-level 3D real scene update is achieved. The experimental results show that this method is high degree of automation, and reliable in precision. The updated 3D real scene is accurate and natural.

Application of oblique photogrammetry and inertial guidance RTK in confirmation of rural homestead right

RAN Kang, WANG Tao, HE Zhiwei

2022, 0(9):  115-118,166.  doi:10.13474/j.cnki.11-2246.2022.0274

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In view of the complex topography, fragmented land parcels, irregular shape of rural house bases, and the fact that most houses are in places with high and dense vegetation, the field operation is difficult and time-consuming and the signal of conventional RTK will be interrupted in the application, etc. This paper considers the advantages of oblique photogrammetry technology and inertial guidance RTK, and proposes a method of using the two measurements technology in rural homestead, aiming to solve the work of confirmation of rural homestead right in Guizhou province in an efficient way. In this paper, the experiment of confirmation of rural homestead right is carried out in Xinhua village, Dongdi township, Nayong county, Guizhou province, and the total station is used to observe the location of boundary points, boundary line and parcel areas in the study area with high accuracy, and the feasibility of the proposed method is elaborated from the following two perspectives. Firstly, the data obtained by using total station data and the graphical interpretation method of oblique photogrammetry technology are compared and analyzed statistically. Secondly, the data obtained by using total station data and the data obtained from the total station data and the inertial guidance RTK analysis method are compared and analyzed. The experimental results show that the results of the oblique photogrammetry graphical method meet the requirements of the graphical method 1∶1000 cadastral map in Regulations for Cadastral Survey in TD/T 1001—2012, and the results of the inertial guidance RTK analytic method meet the requirements of the analytic method secondary accuracy. Based on this, the method proposed in this paper shows advantages of good accuracy, high operability and low time consumption in confirmation of rural homestead right, and can provide a replicable reference method for confirmation of rural homestead right in complex area.

Exploring the idea of automatic modeling based on 3D laser point cloud

MA Yuanfang, LI Haipeng, JIA Guangjun

2022, 0(9):  119-122.  doi:10.13474/j.cnki.11-2246.2022.0275

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For the automatic application of point cloud data, especially in 3D automatic modeling, the traditional point cloud automatic processing technology is always difficult to achieve. Point cloud automatic modeling is a complex process, involving knowledge in many fields such as object recognition, point cloud processing and parametric modeling. Combined with 3D laser scanning technology, this paper summarizes and analyzes the 3D model results and construction methods of various industries and directions according to the different needs of different projects and application directions, Further,it puts forward several ideas and feasibility analysis of 3D laser point cloud automatic modeling, and analyzes the advantages and application direction of several automatic modeling ideas.

Monitoring and analysis of surface subsidence in Beijing by time series InSAR

GONG Gaotai, LI Jiahao, ZHOU Lü, LIU Zhirong, HUANG Liangke, LIU Lilong

2022, 0(9):  123-128.  doi:10.13474/j.cnki.11-2246.2022.0276

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Aiming at the phenomenon of surface settlement in Beijing, this paper uses the time series InSAR method to obtain the settlement rate field and cumulative settlement field during 2018—2020, and selects two subway lines in characteristic areas and different spatial spans for specific settlement analysis. The results show that: ①The phenomenon of uneven settlement in Beijing is obvious, which generally presents the spatial distribution characteristics of uplift in the west and settlement in the east.②There are three obvious settlement funnels, and the maximum cumulative settlement is -218.5 mm.③There are Jinzhan settlement funnel and Dougezhuang settlement funnel in Chaoyang district, and both settlement funnels show an expanding trend in the time span of this study.④There are different degrees of subsidence and uplift in metro lines 5 and 6. The subsidence phenomenon is related to the overexploitation of groundwater and underground space, and the regional uplift phenomenon is related to the supplement of groundwater by the South-to-North Water Transfer Project.

Adaptive filtering algorithm and its application based on the PPP technique for deformation monitoring in mining area

YANG Junshan, XIANG Xin, XIONG Xiaofeng, WANG Yanli, LI Xiaoqiang

2022, 0(9):  129-133.  doi:10.13474/j.cnki.11-2246.2022.0277

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The surface of the mining area is prone to cracking, movement, collapse and other disasters, causing great damage to the human and ecological environment of the mining area. Therefore, it is of great significance to study the surface monitoring in mining area. However, the accuracy of conventional filtering methods depends on the accuracy of prior model parameters. If the model parameters are not exact, the accuracy is difficult to meet the monitoring requirements. In view of this, an adaptive filtering algorithm for deformation monitoring in mining area based on the precise point positioning (PPP) technique is proposed, and the data collected in engineering practice of mining area is applied to carry out the practical experiments, then the superiority of the algorithm is verified. Results show that the proposed algorithm can effectively control the influence of dynamic model parameter deviation and improve the stability of monitoring data calculation. Meanwhile, the calculation accuracy is improved compared with the traditional filtering algorithm.

The key technologies for precision construction survey of super high-rise buildings

YANG Bogang, ZHANG Yi, XIE Yanfeng, WU Shuang

2022, 0(9):  134-140.  doi:10.13474/j.cnki.11-2246.2022.0278

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In the view of the fact that the traditional measurement technology can not meet the construction requirements of ultra-high complex structures,according to the characteristics and difficulties of super high-rise construction projects, through the summary of super high-rise construction measurement technology in China,new equipment and high-precision automatic transfer process method of super high-rise elevation are developed,and a set of key technologies for the construction measurement of Chinese “kilometer” super high-rise buildings are established.Combined with a number of new technologies such as precise GNSS measurement,GNSS positioning technology and intelligent total station,high-quality and high-precision measurement benchmarks,precise construction control points and fast and high-precision monitoring points are obtained. The integration of GNSS technology and super high-rise building construction monitoring is a major innovation of precise engineering measurement,and has broad application prospects.

Thematic color design of land use map: a case study of the color scheme design of the Classification of the Third National Land Survey

LIU Xiangyi, LU Zhongjin, TAI Xiangrong, WANG Hongbo

2022, 0(9):  141-144.  doi:10.13474/j.cnki.11-2246.2022.0279

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Based on the design principles of thematic map, this paper provides series of ideas of color design for land use map. Through a typical case study, the paper proposes a specific design scheme for the Classification of the Third National Land Survey, the feasibility of which is verified by making a sample map. The research in this project on color design of land use map can be used for the compilation of maps and atlases of the third national land survey, which will provide a reference scheme for optimizing map design, improving the expressiveness of land use map and the formulation of relevant industry standards.

A multi-person collaborative operation method for massive basic geographic information data update

LI Zhong, REN Dongyu, ZHOU Qi, LIU Hui, ZHANG Huaixiang

2022, 0(9):  145-151.  doi:10.13474/j.cnki.11-2246.2022.0280

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In order to solve the problems in the traditional multi-person collaborative update technical solution for massive basic geographic information data, and meet the requirements of operation efficiency and process data management in actual production, this paper proposes a multi-person offline collaborative operation method, which is extended based on the spatio-temporal database model, through the centralized storage and management of multi-temporal data during the update process, offline feature editing and collaborative state maintenance, collaborative conflict detection and processing, and local editing content submission, etc.,multi-person offline collaborative update operations are realized. A collaborative production operating system has been developed based on this method, which has been applied in a number of provincial and above database update projects with good application effects.

Planning-oriented 3D geographic entity data model and production technology

SHEN Zhengzhong, GE Weiliao, XIONG Chengli, CAI Zhigang

2022, 0(9):  152-157.  doi:10.13474/j.cnki.11-2246.2022.0281

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3D GIS provides a new kinetic energy for the new round of land spatial planning. 3D spatial data model is the foundation and key of the development and application of 3D GIS. Entity-oriented 3D model is an important expression of 3D spatial data model. This paper proposes a planning-oriented 3D geographic entity data model, and takes the production and application practice in Jiashan county, Zhejiang province as an example to elaborate the key technologies and application effects of entity production. This is significant to serve land spatial planning, improve spatial governance capacity, and promote modernization of governance system.

Curriculum ideology and politics of smart city: core elements and implementation strategies

ZHANG Xinchang, LI Shaoying, RUAN Yongjian

2022, 0(9):  158-161.  doi:10.13474/j.cnki.11-2246.2022.0282

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In the context of era when urban management is transitioning from digital to intelligent advanced stage, our team expands the general course of digital city in combination with the contemporary, cutting-edge, high-level, innovative and challenging talent cultivation requirements of “golden course”. Based on the digital city, we incorporate a large amount of theories and application cases for smart city realization, and upgrade its reconstruction into smart city. Patriotism, personal outlooks, social morality, professional ethics and other ideological and political elements are integrated into the teaching of the new curriculum, which imperceptibly cultivates students' national identity, institutional identity, national pride and dedication. Besides, the groundbreaking integration of the “Internet+” innovation, entrepreneurship competition mode also cultivates the students' thinking, courageous innovation, and teamwork capabilities, which can stimulate students to devote themselves to scientific research and innovation related to smart cities, so as to contribute to the national smart cities construction.

Application of single-beam integrated with INS bathymetric system in Yangtze River channel survey

SHA Hongliang, FEI Xinlong, YE Fei, CHEN Xugang

2022, 0(9):  162-166.  doi:10.13474/j.cnki.11-2246.2022.0283

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Nowadays, the single-beam bathymetric system and multi-beam bathymetric system have been widely used in the underwater topographic mapping of the Yangtze River, and people have higher and higher requirements on the accuracy of underwater topographic data of inland waterways. By using the single-beam integrated with inertial navigation system(INS)bathymetric system, the problem of low precision of traditional single-beam, complex installation and operation of multi-beam system and high requirement of water condition is solved well. In this paper, the practical application of single-beam integrated with INS bathymetric system in the survey of the Yangtze River channel is compared with the traditional single-beam and multi-beam survey data. The results show that single-beam integrated with INS bathymetric system can meet the demand of high precision survey of the Yangtze River channel very well.

Point cloud data simplification based on point-by-point advancing method

HE Kuan, SUN Rui, GUAN Yunlan, ZENG Chenxi

2022, 0(9):  167-169.  doi:10.13474/j.cnki.11-2246.2022.0284

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The paper proposes a point-by-point forward method to streamline point cloud data. The experimental research is carried out by the rabbit model, and the results show that the point-by-point forward method is significantly higher in speed and reduction rate than the Douglas-Peucker method in streamlining point cloud data.

The feasibility study of DEM production based on dense matching point cloud

HUANG Haozhong, SU Penghao, WANG Ran, WANG Feng, SHI Weiwei, ZHAO Jianfei

2022, 0(9):  170-174.  doi:10.13474/j.cnki.11-2246.2022.0285

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The direct outputs of UAV oblique photography usually include 3D mesh, TDOM, DSM and so on. However, DEM that can be used for design and planning can't be directly generated without manual edits. The dense matching point clouds produced by the oblique images processing procedure are not fully used. The dense matching point clouds, similar to the structure of LiDAR point clouds, may be freely to set the point density. Regardless of the data amount, the density of dense matching point cloud can be multiple time of that of LiDAR point cloud. Besides, the dense matching point clouds have texture information without separate color assignment, which has a certain auxiliary effect on artificial visual editing after automatic classification of ground points. This paper compares and analyzes the dense matching point cloud and LiDAR point cloud, separately based on the basis of the oblique photographed data and LiDAR data in the same survey area, and verifies the feasibility of dense matching point cloud for ground point filtering and DEM production in the housing area and sparse forest area.