Bulletin of Surveying and Mapping

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UAV debris flow disaster detection technology based on fine reconstruction of multi-camera

ZOU Yang, DONG Xiujun, ZHANG Guangze, LI Jianqiang, LI Xiangdong, LI Tianyu

Bulletin of Surveying and Mapping 2024, 0 (1): 1-5. DOI: 10.13474/j.cnki.11-2246.2024.0101

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In recent years, geological disasters have occurred frequently in the southwest region, and unmanned aerial vehicle aerial survey technology has obvious advantages in geological disaster detection. This article uses a suspended fixed wing unmanned aerial vehicle as a platform, equipped with a five lens multi-camera to detect and obtain relevant parameters such as debris flow morphology, channels, sources, and zoning in Longmen gully, Liangshan prefecture. The advantages of five lens multi-camera photography and the specific application methods and effects of drone aerial survey technology in debris flow disaster detection are elaborated and discussed. The main understanding is as follows: ① Compared with traditional monocular cameras, five lens multi-camera photography has the advantage of being able to collect data from multiple different angles of vertical and tilt, and the obtained high-definition image data is finely reconstructed to generate orthophoto images. The texture of the 3D model is more comprehensive and has higher resolution.② By using refined reconstruction of orthophoto images and three-dimensional models, a total of 21 sources of landslides, collapses, rock heaps, and dangerous rocks in the debris flow disaster area are interpreted. The net and dynamic reserves of each source material are estimated based on the average thickness and area, providing a data basis for prevention and control design. ③The unmanned aerial vehicle aerial survey technology has advantages such as flexibility, strong emergency response, large survey range, strong traceability, and low flight cost, and has high promotion value and significance in disaster detection.

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Refined identification method and practice of unmanned aerial vehicle for geological hazards in small-scale mountainous areas

HUANG Haifeng, ZHANG Rui, ZHOU Hong, YI Wu, XUE Ronghua, DONG Zhihong, LIU Qing, DENG Yonghuang, ZHANG Guodong

Bulletin of Surveying and Mapping 2024, 0 (1): 6-11. DOI: 10.13474/j.cnki.11-2246.2024.0102

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In this paper, aiming at the geological disasters in small-scale mountainous areas, such as landslides and collapses, a set of refined hidden danger identification method based on small UAV photogrammetry is proposed. Firstly, carry out at least two drone photogrammetry operations for the work area, and obtain refined results such as realistic 3D models, digital orthophoto images (DOM), and digital surface models (DSM) after processing.Secondly, the main focus is on detecting changes in DOM and DSM in two phases to achieve disaster body recognition.Once again, summarize the common characteristics of disaster bodies and establish identification indicators for typical disasters.Then, based on the identification markers, the three-dimensional visual interpretation method is mainly used to identify the pregnant body. Finally, identify or eliminate potential hazards through ground inspections. Applying this method to the left bank slope area of the Xietan River in Zigui, the head of the Three Gorges Reservoir, and 10 different types of hidden dangers are identified, which proves the feasibility of the method.

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Multi-source remote sensing landslide hazard identification method driven by knowledge graph

LI Yongxin, WANG Defu, MA Zhigang, FAN Yajun, YANG Benyong, LIU Li, LUO Chao

Bulletin of Surveying and Mapping 2024, 0 (1): 12-18. DOI: 10.13474/j.cnki.11-2246.2024.0103

Abstract （212）

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Remote sensing technology plays an important role in the field of geological disaster prevention and control. With the development of aerospace technology, more remote sensing data can be obtained and effectively applied to the identification of geological hazard bodies, especially in the identification of landslide hazards. Comprehensive use of InSAR and optical remote sensing data to identify geological hazards is a hot topic in recent research. The traditional recognition process relies entirely on the work experience of interpreters, with strong subjectivity and no fixed recognition logic to follow. Based on SBAS-InSAR and optical satellite imagery, this paper analyzes the process of landslide hazard identification, and constructs the Knowledge graph and identification extraction matrix model of landslide identification. Under the logic drive of the Knowledge graph, the regional spatial characteristics of landslide hazards identified by the combination of “optical remote sensing+InSAR” are analyzed, providing a reference implementation scheme with the significance of semi quantitative extraction of indicators for landslide wide area identification, and realizing the identification process of landslide hazards from completely subjective to semi quantitative. Experiments show that this method can provide reference for relevant research and practical engineering applications, and has certain application value.

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Study on land use change and spatiotemporal variation of carbon storage in Beijing-Tianjin-Hebei based on InVEST model

PENG Yunni, SANG Huiyong, ZHAI Liang, ZHANG Ziyi, DUAN Jinjiang

Bulletin of Surveying and Mapping 2024, 0 (1): 19-24,31. DOI: 10.13474/j.cnki.11-2246.2024.0104

Abstract （137）

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The increase in atmospheric CO ₂content is an environmental issue of widespread international concern, and human activities change land use patterns, and land-use/land-cover (LULC) changes further affect terrestrial ecosystem structure, function, and carbon cycling. With the support of global land cover data GlobeLand30, This paper analyzed the land use changes in Beijing-Tianjin-Hebei from 2000 to 2020, used InVEST model to imitate the Spatiotemporal changes of carbon stocks, and used the spatial autocorrelation analysis to study its zoning. The results show that:①From 2000 to 2020, the largest change area in Beijing-Tianjin-Hebei region is cultivated land and artificial surface, with an area decrease of 340 222.124 hm ²and an area increase of 246 333.493 hm ²respectively. ②The total carbon reserves of Beijing-Tianjin-Hebei in 2000, 2010 and 2020 are 1 666.47×10 ⁶、1654.63×10 ⁶、1632.88×10 ⁶ t, the main reason for the decline in carbon storage are the loss of arable land and the expansion of artificial land surface. ③The high value of carbon storage is mainly distributed in mountain and forest areas with relatively high altitude, while the low value areas of carbon reserves are mainly concentrated in central Beijing, the coastal zone of Tianjin and Hebei and the eastern Cangzhou, southern Tangshan. ④The results of local autocorrelation show that the high value areas of carbon reserves are clustered in the north and west of the study area. Among the regions with low to low aggregation, Dongli district of tianjin city and Hanshan district of Handan city, Hebei province show a relatively obvious weakening trend.

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An evaluation model of ecological management effectiveness combining ecological and social benefits for desertified land of northwest in Liaoning, China

WANG Yuxin, SUN Hao, XU Peng, MENG Jian, WANG Sihan, WANG Chaoqun, WU Ruixiang

Bulletin of Surveying and Mapping 2024, 0 (1): 25-31. DOI: 10.13474/j.cnki.11-2246.2024.0105

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Northwest Liaoning is an important ecological barrier to prevent the Horqin sandy land from invading the North China Plain and the Northeast China Plain. It is of great significance to evaluate the effectiveness of ecological management. To evaluate the effectiveness of desertified land ecological management, weestablish an evaluation model for the effectiveness of desertified land management, whith takes ecological and social benefits into account. Using multi-source remote sensing data and ground survey statistics, a comprehensive model is established to evaluate the effectiveness of desertified land ecological controlin northwestern Liaoning. Based on the cross-validation between remote sensing data and field survey results, the rationality of the key technologies are analyzed. The results show:① By using Landsat and Sentinel-2 data, it is a cross-validation of the singleand comprehensive index of ecological benefit estimated by the model, there is a strong correlation between the results of the same index, and the Pearson coefficient is between 0.61 and 0.84, p<0.01. ②The FVC estimated by the model and the vegetation coverage of the field survey also have a strong consistency, the Pearson coefficient is 0.76, p is 0.016, which shows the rationality of the key technology of the model. ③The model is used to evaluate the effectiveness of desertification land ecological management in ten counties in northwestern Liaoning, the changes are unstable in time and space. In summary, the effectiveness evaluation model established can better integrate the ecological and social benefits of desertification land management, and provide references for other ecological management effectiveness evaluations, but the model parameters need to be adjusted for different regions.

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The inversion and application of forest height of multi-source remote sensing data in Guangxi-ASEAN region

XIE Kaiyi, CHEN Ruibo, WANG Zhili, WANG Qun, BAO Junfan, ZHU Ningning

Bulletin of Surveying and Mapping 2024, 0 (1): 32-37,64. DOI: 10.13474/j.cnki.11-2246.2024.0106

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Forest ecosystems play a critical role in regulating the ecological climate and carbon cycling, and forest height is a fundamental parameter for assessing their functional capacity. However, the acquisition of forest canopy height using single remote sensing data is subject to various constraints. Therefore, in this paper, we use high-quality discrete forest canopy height points from the spaceborne laser altimeter ICESat-2, combined with Sentinel-1, Landsat-8, and terrain data, to establish regression models of forest canopy height with different combinations of image features by using the random forest method, analyzing the impact of each feature on forest height inversion, and applying the model to forest canopy height mapping in Guangxi. The experimental results indicate that multisource remote sensing data effectively enhance the accuracy of forest canopy height estimation. Among the utilized remote sensing data, the feature importance descends in the order: optical features, terrain features, SAR features. The combination of “L8+SRTM+Sentinel-1+neighborhood mean” features achieves the highest accuracy in canopy height estimation, with the inclusion of neighborhood mean feature yielding the best results. The random forest model demonstrates precision in mapping forest canopy height.

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Sub-pixel correlation-based slope monitoring using multi-temporal optical remote sensing images: a case study of Xiluodu hydropower station

YE Jiang, LI Caiyi, GAO Hongqi, XU Weihong, XIANG Nansong

Bulletin of Surveying and Mapping 2024, 0 (1): 38-43,108. DOI: 10.13474/j.cnki.11-2246.2024.0107

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The monitoring of high slope in hydropower plant is a key issue in disaster prevention and control of hydropower plant. The use of satellite remote sensing technology for reservoir landslide monitoring is an important way to solve the problem. The use of subpixel correlation algorithm to obtain the ground deformation displacement field can overcome the phase decorrelation factors in SAR images, and has great potential application in the monitoring of hydropower station slopes. In this paper, Google Earth images from 2015 to 2019 and Sentinel-2 images from 2019 to 2022 were used as data sources, and the slope deformation variables were calculated by the phase correlation algorithm. The trend error such as orbit error was removed by constructing a first-order polynomial surface fitting model, and the slope deformation values of the downstream slope of Xiluodu Station in 2016, 2017, and 2019 were obtained. The analysis showed that the slope deformation values obtained from two images had the same trend, and were in good agreement with the measured data of valley width. The results of this paper verified the feasibility of applying the subpixel correlation matching technique, based on multi-temporal remote sensing data, for monitoring the slope deformation of large hydropower plants.

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Solid waste identification of Zhuhai-1 hyperspectral satellite remote sensing data based on optical flow estimation: a case study of Jiyuan demonstration area in Henan province

ZHANG Pengqiang, SUN Yifan, CHANG Qinghao, LIU Bing, YU Anzhu

Bulletin of Surveying and Mapping 2024, 0 (1): 44-50. DOI: 10.13474/j.cnki.11-2246.2024.0108

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A solid waste identification method based on optical flow estimation for hyperspectral satellite remote sensing data is proposed in this paper.Firstly, this paper rethinks hyperspectral data from the perspective of sequence data, and proposes to introduce DeepFlow optical flow estimation technology to extract brightness change information of spectral dimension as a more discriminative spectral motion feature. Then, the extracted spectral motion features are combined with the original spectral features and input to the commonly used support vector machine for solid waste recognition to improve the recognition accuracy. Finally, a specific method of post-processing for solid waste identification is proposed to improve the identification effect. In this paper, the remote sensing data of “Zhuhai-1” hyperspectral satellite is used, and the experiment is carried out by taking Jiyuan demonstration area in Henan province as an example. The experimental results show that the proposed method can quickly and accurately identify the industrial solid wastes stacked in the open air in a wide range, and preliminarily lock the 11 regional risk points in Jiyuan demonstration area where there are solid wastes left and illegal stacking behaviors, and the accuracy is better than the traditional spectral feature extraction and classification methods. Thus, the time and workload are significantly saved for the later manual on-site investigation of solid waste and “waste clearance” action.

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The progress of risk assessment of power transmission corridor using LiDAR

ZHANG Ruizhuo, TANG Jie, ZHANG Si, SHU Huangyan, ZHANG Di, ZHONG Ruofei, SUN Liming

Bulletin of Surveying and Mapping 2024, 0 (1): 51-57. DOI: 10.13474/j.cnki.11-2246.2024.0109

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Transmission corridor environmental monitoring and risk early warning is a crucial research topic of power grid disaster prevention and resistance. Under the development and promotion of LiDAR, Internet of Things, UAV and computer technology, it has become an important development trend to utilize various new remote sensing monitoring and inspection means to carry out large-scale and intelligent inspection in transmission corridor. Comprehensively analyzing a variety of different monitoring data for power line safety risk assessment and disaster early warning research has been one of the research hotspots in the construction of smart grid. In this article, the research status and development trend of using LiDAR technology for the safety risk detection in transmission corridor, and their advantages and disadvantages are systematically expounded. And problems and challenges faced by the safety risk assessment of power transmission corridors are summarized.

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Research on frost heave deformation prediction of high railway foundation combined with PS-InSAR technology and multivariable LSTM neural network

LI Xin, WEI Guanjun, ZHANG Delong

Bulletin of Surveying and Mapping 2024, 0 (1): 58-64. DOI: 10.13474/j.cnki.11-2246.2024.0110

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Aiming at the problem that traditional deformation monitoring and prediction are difficult to achieve large-scale monitoring and accurate prediction, a method combining PS-InSAR technology and multi-variable long Short term memory (M-LSTM) neural network is proposed to monitor and predict the frost heave deformation of high railway foundation. Firstly, PS-InSAR technology is used to obtain the spatial distribution characteristics of subgrade frost heave. Then, Pearson correlation coefficient method is used to optimize three kinds of frost heave induced factors, and the obtained data are preprocessed to compose the training data. Finally, LSTM is introduced to construct an intelligent and multivariable frost heave prediction model to accurately predict the frost heave deformation trend of subgrade. The results show that PS-InSAR technology is reliable in large-scale deformation monitoring. The prediction accuracy of M-LSTM model is higher than that of the traditional neural network model, and the mean determination coefficient ( R ²), mean absolute error (MAE) and mean root mean square error (RMSE) are 0.973,0.024 mm and 0.035 mm, respectively. It shows that M-LSTM model has good application value in frost heave deformation prediction of high railway foundation, and also provides a new idea for frost heave deformation prediction of subgrade.

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Indoor scene point cloud segmentation based on improved supervoxel and graph cut

GU Ying, LI Lin, ZHU Haihong

Bulletin of Surveying and Mapping 2024, 0 (1): 65-71. DOI: 10.13474/j.cnki.11-2246.2024.0111

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Indoor scene point cloud segmentation is the basis for the perception,understanding,analysis and application of 3D scenes. Although the current indoor point cloud segmentation method can be applied to many scenes,it lacks the ability to adapt to the segmentation of different structures,and the bottleneck of undersegmentation cannot be avoided when dealing with segmentation of near parallel surfaces. Therefore,a method based on improved supervoxel and graph cut is proposed,through the neighborhood selection,normal vector calculation,feature distance measurement,and spatial connectivity constraint and segmentation of supervoxel local adjacency graph,an adaptive mechanism for processing the relationship between adjacent parallel surfaces is constructed,which realizes the effective segmentation of point cloud in complex indoor scenes,and the above-mentioned undersegmentation phenomenon is overcome. Finally,the proposed method is verified by four indoor scene point clouds,and compared with the existing methods. Experimental results show that the proposed method improves the accuracy and recall of point cloud segmentation in complex indoor scenes,and verifies the adaptability and effectiveness of the method to different structural segmentation.

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Geostationary satellite nighttime cloud detection method by fusing spectral threshold and image techniques

WEN Gang, ZHOU Fangrong, MA Yi, WANG Yifan, WANG Guofang, MA Yutang, ZHU Longchang, LI Chunming, WU Lei

Bulletin of Surveying and Mapping 2024, 0 (1): 72-76. DOI: 10.13474/j.cnki.11-2246.2024.0112

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To address the problem of nighttime cloud detection, based on the geostationary meteorological satellite Himawari-8 image data, we analyze the spectral characteristics of cloud image elements and image features, and propose a geostationary satellite nighttime cloud detection method that integrates spectral thresholding and image technology, realizing the rapid and accurate detection of geostationary satellite nighttime clouds. Using MODIS cloud products and CALIPSO radar data, the cloud detection results are qualitatively analyzed and quantitatively verified. The results show that:① The cloud detection results are basically consistent with the distribution of MODIS's cloud product MYD06;② The algorithm's average cloud detection accuracy at night reaches 80.3%;③ The cloud detection accuracy at night in different seasons varies more obviously with the seasons, and reaches up to 83.3% in summer, which can distinguish between cloudy and non-cloudy regions at night in different seasons. Therefore, the geostationary satellite nighttime cloud detection method that integrates spectral thresholding and image technology can effectively realize nighttime cloud detection and provides a new idea for nighttime cloud detection applications.

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ORB-SLAM3 algorithm based on binocular depth screening

FU Qiang, TENG Xianyun, JI Yuanfa, REN Fenghua, KONG Jianming

Bulletin of Surveying and Mapping 2024, 0 (1): 77-82. DOI: 10.13474/j.cnki.11-2246.2024.0113

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Aiming at the problem that feature points in ORB-SLAM3 algorithm are easily lost and have low accuracy, which in turn leads to large errors in motion trajectory of binoculars in complex scenes, this paper designs an improved ORB-SLAM3 algorithm. Firstly, the adaptive corner point detection technology is introduced in the ORB feature matching algorithm to increase the number of feature point acquisition. Secondly, the optical flow method is used to track the image features to improve the success rate of key frame creation. Then the region search is done with the feature points as the center to improve the real-time performance, the bi-directional left-right consistency test is used to screen the optimal parallax, the Prosac algorithm is applied to remove the mis-matched point pairs. Finally, the depth information is combined with the key frame. the depth information is combined with the key frame screening to improve the quality of key frames and optimize the camera pose. The improved algorithm has good robustness and positioning accuracy in absolute trajectory error.

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Satellite images stereo matching algorithm based on deep learning

LI Dongrui, TONG Xin, LI Wentao, SONG Xinyu, LIU Jiebing

Bulletin of Surveying and Mapping 2024, 0 (1): 83-88. DOI: 10.13474/j.cnki.11-2246.2024.0114

Abstract （129）

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Satellite images stereo matching is one of the important steps for large-scale earth surface reconstruction, there are relatively few existing studies, and there are problems such as poor matching effect and poor model generalization ability. A deep learning-based satellite image stereo matching algorithm is proposed to perform stereo matching, including dataset construction, building stereo matching network, multi-level transfer learning and post-processing. Dataset construction contains disparity offset and and cropping. The cropped patches are then fed into attention volume network, which includes deep feature extraction, attention volume construction, disparity estimation. The network is trained by multi-level transfer learning, adapts to different data sources, and predicts the disparity maps. The false matches are filtered out by post-processing. The experiments were carried out with Jilin1-GF02 and Jilin1-GF04 images. The accuracy of the disparity maps obtained from the experimental results is better than one pixel. It shows that the algorithm proposed in this paper can obtain accurate and efficient results, which determines the generation of subsequent high-quality digital surface model.

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Tightly coupled GNSS RTK/INS integration positioning based on MEMS IMU

XIE Qing, ZHANG Quan, ZHANG Hongping, CHEN Dezhong, LI Zhijun, CUI Yulu

Bulletin of Surveying and Mapping 2024, 0 (1): 89-95. DOI: 10.13474/j.cnki.11-2246.2024.0115

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In order to improve the poor GNSS positioning stability in complex environment, a low-cost and high-precision positioning method with IMU assisting RTK for autonomous driving is proposed. MEMS IMU M39 and tactical IMU Pos320 are used in simulation experiments. Through simulating interruption of multiple groups of measured vehicle data, INS position drift error, ambiguity fixing time and fixing accuracy are obtained. The ambiguity fixing time and positioning accuracy under three conditions of no inertial navigation assistance, M39 assistance and Pos320 assistance are statistically and analyzed. The results show that M39 can assist RTK to achieve instantaneous ambiguity fixing with 5 s GNSS outage. When the outage is 10 s it still can reduce the convergence time of ambiguity to 1/4. Also, with assistance of MEMS IMU, the number of incorrect ambiguity is significantly reduced, and the proportion of high-precision positioning within 10 cm is increased from 62.25% to 98.44%. Experiments show that MEMS IMU assisted RTK can accelerate the speed of ambiguity fixing and improve the accuracy and reliability of navigation and positioning in autonomous driving.

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Spatio-temporal evolution of rural settlements distribution pattern and its driving forces in the Yellow River Basin under the background of rural revitalization

SHAN Yamin, LI Heying, ZHANG Jianchen, TANG Lingjun, GUO Jianzhong, WANG Guangxia, WANG Jiayao, ZHANG Hanwen, ZHENG Haohua

Bulletin of Surveying and Mapping 2024, 0 (1): 96-101. DOI: 10.13474/j.cnki.11-2246.2024.0116

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The study uses land use data from 1980 to 2020 in the Yellow River Basin and employs landscape indices, kernel density estimation, land transfer matrix, and geodetector to analyze the spatio-temporal evolution and driving forces of rural settlements at the scale of urban agglomerations.The results show that: ① The overall land use scale of rural settlements is expanding, mainly converted from dry land; The density of rural settlements in the urban agglomeration of the Central Plains changes mostly. With the exception of the Guanzhong Plain urban agglomeration, the shape of the rural settlements in the other six urban agglomerations became more regular. ② The spatial distribution of rural settlements shows that “the southeast is agglomerated, and the west and north are scattered”, showing a more intensive development trend, among which the urban agglomeration in the Central Plains changes mostly.③ Rural settlements are mainly distributed below 1 km above sea level and 2～5 km away from rivers, and their scale is inversely proportional to the distance from roads; Roads are the main factors affecting the distribution of settlements in Lanxi, Ningxia-Yanhuang, Guanzhong Plain and Shandong Peninsula urban agglomerations, while elevation is the main factor affecting the distribution of settlements in Hubao-Eyu, Jinzhong and Central Plains urban agglomerations.

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Efficient visualization of 3D city scenes combining hierarchical level of details and potential visible sets

XU Hai, HE Biao, KUAI Xi, TANG Aowei, LI Zeyu, WAN Yuan

Bulletin of Surveying and Mapping 2024, 0 (1): 102-108. DOI: 10.13474/j.cnki.11-2246.2024.0117

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The visualization of 3D city scenes is a key technology in digital cities, and it is also an important link in the provision of various smart services in smart cities. However, the amount and complexity of data in 3D city models grows geometrically, which imposes a heavy burden on data organization and visualization of urban 3D scenes, in the current city-level visualization platform based on game engine and geographic information system technology, this kind of data is difficult to load and visualize at one time. Aiming at this problem, this paper proposes a method for efficient visualization of 3D urban scenes that integrates hierarchical levels of detail(HLOD) and potentially visible sets(PVS), which realizes the efficiency of dynamic scheduling and loading of large-scale complex 3D urban scenes and the visual consistency of 3D visualization. A case study is carried out in the Qianhai area of Shenzhen. The results show that the average occlusion removal rate of the potentially visible sets calculation method based on adaptive partition proposed in this paper is as high as 76.6%, which can greatly remove and reduce the amount of model data loaded into a 3D city scene; Integrating the dynamic scheduling of HLOD and PVS, the rendering visualization frame rate is basically maintained at around 60 FPS, which can meet the efficient and smooth visualization experience of 3D urban scenes.

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Noise-resistant extraction of tunnel excavation axis under point cloud density feature constraints

ZHI Zhiyang, LI Aiguang, DU Zhigang, RUAN Qinglin, ZHAO Yipeng

Bulletin of Surveying and Mapping 2024, 0 (1): 109-114. DOI: 10.13474/j.cnki.11-2246.2024.0118

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The original point cloud data of the tunnel acquired by 3D laser scanner often contains a lot of irrelevant points, which has a great impact on the extraction of tunnel axis, and at the same time, it is difficult to meet the real-time demand for on-site construction. For the above problems, an efficient and automatic method is proposed to extract tunnel axis by taking the density characteristics into consideration. Firstly, the density characteristics of the tunnel point cloud are counted, and different constraint coefficients are generated based on the different density of the point cloud region, and the constraint coefficients are used as the basis for the selection of the axial fitting points; after the top-view projection and the RANSAC processing, the central axis of the projected plane is obtained; after the side-view projection, the location of the vault is obtained, and based on that, the central axis is adjusted to the center of the tunnel; and the central axis is adjusted to the center of the tunnel by using the RANSAC linear fitting is used again to realize the prediction of the axis of the different zones.The results show that according to the density characteristics of the tunnel point cloud in the specified area,the method can quickly and accurately extract the axes in the tunnel point cloud with a lot of noise, and it is applicable to excavated tunnels in different zones with good adaptability.

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Two-dimensional change measurement algorithm of crack under micro shooting condition

YANG Chengxiang, DING Yong, LI Denghua

Bulletin of Surveying and Mapping 2024, 0 (1): 115-119,125. DOI: 10.13474/j.cnki.11-2246.2024.0119

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Structural crack change is a common disease in building structures. In view of the shortcomings of the existing two-dimensional crack detection technology under macro photography, this paper designs a target that can adapt to macro photography according to the equivalent physical model of crack change, and develops a two-dimensional crack change detection algorithm. The algorithm consists of target target location, distortion parameter correction, crack parameter calculation and other parts. A micro-range image acquisition device is designed by combining raspberry pie and camera. Based on the indoor test verification, the measurement accuracy of the crack width change under the micro-distance photography is within 0.1 mm.

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Quantitative detection technology of pipe damage based on laser point cloud data

LI Yi, CAI Yi, DONG Siqi, ZHAO Zhiyang, CHEN Qi

Bulletin of Surveying and Mapping 2024, 0 (1): 120-125. DOI: 10.13474/j.cnki.11-2246.2024.0120

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Using the pipe laser scanning technology, 3D information of point clouds on the inner surface of the pipeline can be obtained, which solves the problem that traditional pipeline video detection methods are difficult to quantify. Aiming at the characteristics of point cloud data of pipeline damage defects, point cloud filtering algorithms such as statistical filtering and radius filtering are used to achieve point cloud deletion at pipeline damage locations. Based on RANSAC algorithm, cylindrical surface projection of pipeline point cloud data and 2D planar expansion of pipeline point cloud data are implemented. Through grid filtering and region growth algorithms, pipeline point cloud data damage defect detection and automated analysis are achieved. The measured data verify the reliability and effectiveness of the method, which can accurately identify the location of pipeline damage, and calculate parameters such as damage area, longitudinal length, and circumferential length.

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UAV image matching based on improving the ORB algorithm

LI Bing, LAI Zulong, SUN Jie, DING Kaihua

Bulletin of Surveying and Mapping 2024, 0 (1): 126-130,149. DOI: 10.13474/j.cnki.11-2246.2024.0121

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This paper addresses the problem of unstable feature point extraction and pixel-level feature point localization accuracy faced by the ORB algorithm when encountering changes in illumination. To improve the ORB algorithm, a self-adaptive threshold method based on foreground-background contrast is proposed in conjunction with existing sub-pixel localization techniques. In order to avoid the error caused by the need for manual threshold setting in RANSAC algorithm, this paper introduces the MAGSAC++algorithm into the feature matching process for false match elimination. Experimental results show that the improved algorithm can obtain a larger number of matches, has better robustness to changes in illumination, and improves matching accuracy by at least 7%.

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The application of UAV LiDAR in transmission line flat section surveying and mapping

HUANG Yulin, LIU Longfei, ZU Weiguo, TAN Jinshi

Bulletin of Surveying and Mapping 2024, 0 (1): 131-135. DOI: 10.13474/j.cnki.11-2246.2024.0122

Abstract （102）

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This paper investigates the application of UAV LiDAR technology to the mapping of transmission line flat sections in view of the problems of large workload, high risk in the field, difficulty in measuring ground point elevations in vegetation-covered areas and difficulty in measuring cross-crossing conductors in traditional transmission line flat sections. Firstly, the principle and advantages of UAV LiDAR are analysed, and then key technologies such as UAV LiDAR field data acquisition, laser point cloud filtering to build DEM, 3D feature acquisition, elevation information extraction and rapid mapping of flat sections are studied in depth. The results show that the method can achieve high accuracy and intelligent mapping of flat sections, with a two-fold increase in efficiency, and provide technical support for transmission line path optimisation. It has great economic and social benefits, and is worthy of application and reference.

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Research on surveying and mapping for 3D cadastre and its standardization

XU Hongxiu, YANG Yuzhong, WANG He, WU Hongtao, TAN Xinyu

Bulletin of Surveying and Mapping 2024, 0 (1): 136-140. DOI: 10.13474/j.cnki.11-2246.2024.0123

Abstract （113）

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In view of the traditional land management mode based on cadastral and cannot well meet the increasingly tense demand of urban space management, this paper first analyzes the research status of 3D cadastre at home and abroad, and puts forward the technical route to solve the difficulties and pain points of three-dimensional land management based on 3D cadastral mapping. Then, based on this research content to conduct the exploration of 3D cadastral standardization, this paper mainly introduces the compilation process and main content for Technical Regulation of 3D Cadastre & Pproperty Unit Surveying and Mapping, and the research route and the standardare applied to the typical cases, so as to prove the feasibility of the technical route and the applicability of the standard.

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Performance evaluation of static and kinematic precise pointing positioning with six systems fusion

ZHAI Yan, YANG Li, LIN Wei

Bulletin of Surveying and Mapping 2024, 0 (1): 141-144,160. DOI: 10.13474/j.cnki.11-2246.2024.0124

Abstract （67）

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This paper analyzes the performance of static and kinematic PPP of combined GPS,GLONASS,Galileo,BDS-2,BDS-3 and QZSS with global 100 stations evenly distributed. The results show that multi-system fusion greatly reduces the convergence time and improves the positioning accuracy. The average convergence time of horizontal, vertical and three-dimensional components of GPS-only and six-system fusion static PPP is 18.5, 18.0, 19.0 min and 11.5, 12.0 and 12.5 min, respectively, and the one-hour positioning accuracy is 1.9, 2.2, 2.1 cm and 1.2, 1.5 and 1.4 cm, respectively. The average convergence time of horizontal, vertical and three-dimensional components of GPS-only and six-system dynamic PPP is 34.5, 33.5, 36.0 min and 15.0, 15.5 and 16.5 min respectively, and the positioning accuracy after convergence is 1.9, 2.6, 2.3 cm and 0.9, 1.6 and 1.3 cm respectively.

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Sensitivity analysis of influencing factors of open-pit mine slope stability based on grey correlation

CHEN Lanlan, XIAO Haiping, LIU Xinyu, LIU Wei

Bulletin of Surveying and Mapping 2024, 0 (1): 145-149. DOI: 10.13474/j.cnki.11-2246.2024.0125

Abstract （55）

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Under the interaction of various internal and external factors, the stability of open-pit mine slope will show different states. Effective analysis of the sensitivity and size of different influencing factors to the slope has important application value for guiding the safe production and prevention of the mine. Based on the analysis of the rock properties, geological structure, hydrological conditions, topography and external factors of the slope of Yuebao open-pit mine, this paper puts forward the key influencing factors of the slope stability of the open pit mine, mainly including the gravity V and internal friction angle ψ. According to the results of the orthogonal test, the sensitivity model of the influencing factors based on the grey correlation analysis is established for five indicators, such as cohesion c, slope top load q, and slope ratio m. The research results show that the sensitivity of the five main influencing factors to the slope stability is as follows: c>ψ>m>V>q. The research results can provide scientific basis for scientific prevention and control of open-pit mine slope.

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Application of SBAS-InSAR technology in deformation monitoring of mountain in Kunming South Railway Station

LI Zerun, XI Wenfei, ZHAO Zilong, LIU Haihong, ZHANG Yuying, ZHANG Liting

Bulletin of Surveying and Mapping 2024, 0 (1): 150-154. DOI: 10.13474/j.cnki.11-2246.2024.0126

Abstract （85）

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Landslide has a serious impact on human safety. The traditional landslide deformation monitoring has high cost, time consuming and low efficiency. The synthetic aperture radar interferometry (InSAR) landslide deformation monitoring technology can improve efficiency and save cost. Based on SBAS-InSAR technology, we process 24 sentinel-1 rail drop data from January 1,2019 to December 31,2019, obtained the deformation rate of the study area as -11.56~13.08 mm/a, processing of the sentinel 2 optical data using the pixel dichotomous model, obtained the vegetation coverage of the region in 2019.The deformation of the study area was combined with six typical deformation points. The results of the study show that, the west side of the mountain is the main deformation area, small area variable with high vegetation cover, large area shape variable with low vegetation cover. This study is of great significance for the safety monitoring of Kunming South Railway Station.

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Study on the estimation of lateral breakthrough error in horizontal control survey of super long tunnel

SI Dagang, XIONG Wenhao, ZHANG Shijie, MA Qian, MIAO Peipei, LIU Jianqi

Bulletin of Surveying and Mapping 2024, 0 (1): 155-160. DOI: 10.13474/j.cnki.11-2246.2024.0127

Abstract （112）

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For the super long tunnel with the opposite excavation of more than 20 km, the construction environment inside the tunnel is complex, and there are few comprehensive analysis cases of the factors affecting the lateral breakthrough error inside and outside the tunnel. There are also no relevant standards and specifications for the control survey of super long tunnel, making it difficult to control the lateral weaving in the tunnel measurement. In order to predict the lateral breakthrough error for the construction of super long tunnel, the sources of lateral breakthrough error were analyzed, and the influence of control survey outside and inside the tunnel on lateral breakthrough error was studied. The influence values of GNSS outside the tunnel, angle measurement error, distance measurement error, etc., on lateral breakthrough were estimated,and simulation calculation experiments inside the tunnel were designed,taking into account factors such as alignment error and observation error. Under the conditions of different angle measurement accuracy and different traverse lengths,the mean square error values of lateral breakthrough for different tunnel lengths within the range of 20～30 km were derived and simulated.The results show that improving the accuracy of angle measurement has a significant effect on the gain of lateral breakthrough accuracy,and the simulation results are accurate and reliable.Taking a 2 km tunnel length as the dividing interval,recommended values for the mean square error of lateral breakthrough outside and inside the super long railway tunnel are obtained.

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The method of correcting the tilt position and pose of the measuring tower for immersed pipe installation

CHENG Yipin, GUAN Minglei, ZHANG Dejin, LIU Guohui, TIAN Chenyang, ZHANG Yihong

Bulletin of Surveying and Mapping 2024, 0 (1): 161-165. DOI: 10.13474/j.cnki.11-2246.2024.0128

Abstract （93）

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In the process of sinking and docking construction of sunk pipe joint, the relative geometric position of measuring tower and pipe joint changes slightly due to the deformation of pipe joint body, thus affecting the positioning accuracy of sunk pipe installation. The inclination meter monitoring equipment is installed on the pipe joint body and the measuring tower structure respectively to calibrate the inclination meter installed in the pipe joint under the same coordinate system. In the process of sinking pipe docking, the positioning inclination error of the measuring tower is monitored and corrected in real time. Through comparison and verification, the method can effectively reduce the influence of pipe joint deformation on the positioning accuracy of sinking pipe installation, and obtain good application results, which can provide reference for the construction decision of sinking butt.

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The representation method of Chinese historical maps in public publications

ZHOU Xinwei, HUANG Long, WU Jiatong

Bulletin of Surveying and Mapping 2024, 0 (1): 166-168,174. DOI: 10.13474/j.cnki.11-2246.2024.0129

Abstract （63）

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Chinese historical map is the map that can best express the origin and changes of Chinese territory. It is related to national security,territorial integrity and national dignity, and has serious political nature, rigorous scientific, strict legality and strong professionalism.But now, the map review and return rate of Chinese historical map is high, and the occurrence rate of “problem map” of map monitoring is high. This paper fully analyzes the representation characteristics of Chinese historical maps in historical geography academic monographs and history textbooks, and deeply studies the relevant policies and technical requirements, then systematically expounds the public representation methods and requirements of Chinese historical maps from the aspects of the comparative expression of historical and modern contents, historical territory and historical place names. It will provide reference for the compilation, supervision and use of public Chinese historical maps, and promote the healthy and prosperous development of China's historical map to a certain extent.

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Urban emergency shelter planning based on GIS spatial quantitative evaluation of flood resilience

JIANG Fengshan, FU Xingfeng, ZHAO Lei, XIE Zhiqiang, WANG Zhanhui

Bulletin of Surveying and Mapping 2024, 0 (1): 169-174. DOI: 10.13474/j.cnki.11-2246.2024.0130

Abstract （114）

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In the context of global climate change and accelerated urbanization, the occurrence of extreme weather leads to frequent urban floods and becomes a major natural disaster threatening public life and property. Therefore, improving the ability of cities to face storm floods is the main task in the process of urbanization. This paper takes the five districts in the main city of Kunming Yunnan province as the research area, through the relevant analysis of flood-prone points and refuge sites, based on the relevant analysis of the shortest escape path planning, health, and medical facilities distance and other factors, studies the effective flood emergency planning method, and improves the flood prevention capacity of Kunming by enhancing the resilience of urban flood. The research results show that there are still some hidden dangers of flood and waterlogging in Kunming. In recent years, with the continuous updating of urban planning, the drainage system of the main urban area of Kunming has a certain resistance to extreme rainstorms, but there is still room for improvement.

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