Table of Content

25 October 2023, Volume 0 Issue 10

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Variation trend and comparative analysis of long-term vegetation cover in Mount Fanjing

YU Ting, YANG Ping, DENG Xing, LIU Suihua, ZHOU Yang

2023, 0(10):  1-6.  doi:10.13474/j.cnki.11-2246.2023.0287

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Mount Fanjing has a unique subtropical isolated island ecosystem and rich biodiversity. It is of great significance to study the long-term temporal and spatial evolution and change trends of its vegetation coverage for the ecological management of the reserve. Based on the GEE cloud platform, this paper uses the Landsat SR dataset for cloud removal and fusion processing, and uses the maximum composite method to synthesize the annual NDVI dataset. The vegetation coverage was inverted by the pixel dichotomy model, and the temporal and spatial evolution and trend of FVC in Fanjingshan National Nature Reserve were analyzed pixel by pixel by the linear regression trend analysis method and Sen+Mann-Kendall trend analysis method, and compared the difference between the two trend analyses. The results show that: ①In the past 30 years, the vegetation coverage of Fanjingshan National Nature Reserve showed a “U”-shaped growth trend, which first decreased and then increased, with a growth rate of 3.46%, and the overall vegetation coverage improved significantly.②In terms of spatial distribution, the vegetation coverage of Fanjingshan National Nature Reserve is high in the middle and low in the surrounding areas. The area of vegetation improvement (accounting for 94.80%) is much larger than the area of vegetation degradation (accounting for 5.20%). ③The change trends of vegetation coverage in Fanjingshan National Nature Reserve obtained by the two trend analysis methods are basically similar, but the Sen+Mann-Kendall trend analysis method is 2.18% more sensitive to significant changes.

Analysis of area change and driving forces for the Eling Lake at the source of the Yellow River

LI Na, WANG Lin, WEN Guangchao, WANG Junlei, WU Yinwen

2023, 0(10):  7-13,33.  doi:10.13474/j.cnki.11-2246.2023.0288

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Lake is one of the important structures that constitute the ecosystem.Exploring the changes of the area of Eling Lake at the source of the Yellow River and analyzing its driving factors can provide theoretical basis and technical support for the ecological protection and environmental governance of the Yellow River Basin.Combined with meteorological,vegetation coverage,land use types and other factors,a series of Landsat remote sensing images from 2001 to 2020 are selected to carry out the analysis and research on the area change of Eling Lake and its driving force by using NDWI,Mann Kendall test,Pearson correlation analysis and other methods.The results show that the average area of Eling Lake from 2001 to 2020 is 639.10 km²,the maximum value is 676.28 km² in 2012,and the minimum value is 595.92 km² in 2001.The change of lake area has roughly gone through four stages: stability period (2001—2004),expansion period (2004—2012),contraction period (2012—2017) and expansion period (2017—2020),showing an overall expansion trend.In space,the area change in the southwest of Eling Lake has been the most obvious in the past 20 years,with an area expansion of 20.41 km² compared with the previous year in 2018.During the shrinking period of the lake,the lake boundary in the southwest region shows a trend of continuous contraction.The changes in basic geological conditions and meteorological conditions are the main reasons for the change in the area volume in the southwest region.According to the correlation between various factors and lake area,the driving factors of the area change of Eling Lake from 2001 to 2020 can be ranked as follows: precipitation>temperature>vegetation coverage>evaporation>land use type.Rainfall and temperature are the main influencing factors on the changes in the area of Eling Lake.

Assessment of eco-quality in the Three Gorges Reservoir area based on RSEI suitable for autumn and winter

JIANG Jundi, LI jia, CHEN Yanming, LAN Qiuping, CHEN Feng, GAO Jiandong, LIU Yinfeng

2023, 0(10):  14-19.  doi:10.13474/j.cnki.11-2246.2023.0289

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RSEI is an ecological index that can evaluate ecological environment quality in a rapid, real-time, quantitative, and multi-temporal manner, while RSEI has the problem of inadequate inversion characterization of ecological quality in autumn and winter seasons. In response to this problem, a RSEI suitable for autumn and winter seasons is proposed. First, the four indicators of RSEI are analyzed by using geographic detectors to see if they are applicable to the inversion of ecological quality in the autumn and winter seasons. Then the vegetation cover, vegetation health index, surface water content index, surface temperature and air quality index are used to construct the RSEI applicable to the autumn and winter seasons, and the applicability is verified. The final inversion and spatio-temporal analysis of the ecological and environmental quality of the Three Gorges Reservoir area in autumn and winter show that: ①The ecological and environmental quality of the reservoir area show an overall trend of improvement; ②The ecological and environmental quality of 77% of the area is relatively stable;③The ecological environment of the reservoir area is predicted to show an overall trend of future and continuous improvement.

Analysis of spatio-temporal evolution characteristics of water bodies in Dongting Lake Basin based on multi-source time series images

ZHOU Zaiwen, HE Zhenming, JIANG Songyu, XIANG Longwei, PENG Li

2023, 0(10):  20-27.  doi:10.13474/j.cnki.11-2246.2023.0290

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Lakes are important land resources, and the study of the dynamic changes of lake waters is conducive to providing an important guarantee for the development and utilization of regional water resources and the stability of ecological balance. Based on Google Earth Engine, using multi-source remote sensing data from 1989 to 2022 as the data source, in normalized difference water index (NDWI), modified normalized difference water index (MNDWI), automatic water extraction index (AWEI_sh) and the water index (WI₂₀₁₅) selects the optimal water body index from the four commonly used water body indexes to extract the water body of Dongting Lake Basin. Combined with various data such as precipitation, temperature, population density and land use in the basin to explore the Dongting Lake analysis of water body evolution characteristics and driving forces in the lake basin. The results show that, from 1989 to 2022, the water body area in the Dongting lake area showed an overall downward trend in the wet and dry seasons, and the three major lake areas all had different degrees of reduction, with an average reduction of 93.27 km²and 140.15 km². The area of lakes in the basin is the result of the combined effects of natural climate change and human activities. Precipitation and temperature are important natural factors affecting the area of lakes. The increase in population and the transfer of land use types caused by reclamation of lakes are the human factors for the reduction of lake area.

Multi-scenario simulation and spatial-temporal analysis of landuse based on PLUS model

HU Juncong, HE Huagui, CHEN Zhaoxia

2023, 0(10):  28-33.  doi:10.13474/j.cnki.11-2246.2023.0291

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Based on the land use data of Heyuan city from 2009 to 2018, the PLUS model is used to simulate the land use in 2030 under three typical scenarios, and the spatial autocorrelation of land use change, the correlation of driving factors and the migration of gravity center are discussed with the example of cultivated land. The results show that the cultivated land, building land and traffic land will expand and the overall land value is higher than the other two scenarios under the natural development scenario. In the ecological protection priority scenario, the main source of urbanization expansion land is cultivated land, garden land and other agricultural economic land, while in the economic development scenario, it is forest land. The spatial and temporal characteristics of cultivated land and its change are more in the north and less in the south, and the center of gravity of this kind of land will move northward.

Visual spatial relationship model for unmanned platform

HUANGFU Runnan, TIAN Jiangpeng, YOU Xiong, TU Yicheng

2023, 0(10):  34-39,66.  doi:10.13474/j.cnki.11-2246.2023.0292

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Visual spatial relationship refer to the spatial relations obtained through visual sensors. When the cognitive subject changes from a human to an unmanned platform, describing and recording spatial relationships explicitly is the key for unmanned platform to realize scene understanding and spatial reasoning. Focusing on the current situation of the lack of visual spatial relationship model for unmanned platform, we integrate the classification, model and algorithm about spatial relationship in cartography and machine vision, propose a visual spatial relationship model for unmanned platform. We construct datasets incorporating the visual spatial relationship model, train the visual spatial relationship prediction model, and compare the visual spatial relationship detection capabilities of different models, which verified the completeness of the dataset constructed based on the visual spatial relationship model as well as the validity of the model in enhancing the visual spatial relationship detection capabilities. This study can improve the current problem of spatial relationship inconsistency in the field of machine vision, and has certain research significance in improving the visual relationship detection of unmanned platform, realizing the spatial relationship record and map model construction.

Road side multi-object recognition by integrating point cloud and panoramic image

WANG Buyun, LI Hongwei, ZHAO Shan

2023, 0(10):  40-46.  doi:10.13474/j.cnki.11-2246.2023.0293

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In order to automatically and accurately identify objects such as vehicles,garbage cans and rod-shaped traffic facilities from point clouds,this paper proposes a roadside multi-object recognition method that integrates point clouds and panoramic images,and makes full use of spatial geometry information in point cloud data and semantic information in panoramic images to improve the accuracy of target recognition. Firstly,the panoramic image is segmented to obtain the two-dimensional mask of the object in the image. Then,the laser point cloud is projected to generate a panoramic depth map,and the corresponding candidate point cloud is obtained using the depth image as the medium. Finally,for the problem of angle occlusion and occlusion caused by camera shooting,through analyzing the continuity and integrity of the target in 3D space,secondary clustering of candidate point clouds is carried out,and finally the classification of the target is completed. Experimental results show that the accuracy rates of the three types of targets are 96.64%,92.68% and 90.74% respectively,which prove that the proposed method can effectively identify vehicles,garbage cans and rod-shaped traffic facilities in urban scenes by integrating semantic information in images with spatial geometry information in point clouds.

A large scale online UAV mapping algorithm for the dense point cloud and digital surface model generation

YANG Jiaqi, FAN Dazhao, YANG Jiabin, YANG Xingbin, JI Song

2023, 0(10):  47-53.  doi:10.13474/j.cnki.11-2246.2023.0294

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Aiming at the problem that UAV image acquisition of dense point cloud and DSM is taking too much time and point cloud quality and processing speed are difficult to balance, a large scale online UAV mapping algorithm for the dense point cloud and digital surface model generation is proposed. Firstly, the loose coupling between SLAM and RTK information is used to estimate the image pose online. Then, we use multi-view image pose information in depth space discrete sampling, discrete sampling depth through the current pixel are projected to candidate for getting the matching cost. We use a symmetrical census cost function to compute cost volume, and considering multiple view shade relations joint generation value calculation to save time and improve the accuracy of matching cost. Finally, we propose an incremental cost accumulation strategy to constraint depth range on the current frame using the previous frame depth, to decrease online computation time consuming, and combined with a parabolic curve fitting method to get the higher accuracy and completeness of final depth, the final dense point cloud and DSM results are obtained by projecting the depth map to the object space after drying. The experimental results of three groups of UAV images in typical areas show that our method not only can satisfy the requirements of online computing, but also the accuracy and completeness of point cloud and DSM result are good.

SfM-based video frame images under complex shaped ancient buildings three-dimensional reconstruction method

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

2023, 0(10):  54-60.  doi:10.13474/j.cnki.11-2246.2023.0295

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A low-cost, simple and efficient method of 3D reconstruction of video frame images based on structure from motion (SfM) is proposed for the problem of realistic 3D modeling of complex shaped ancient buildings. Firstly, a single-lens consumer-grade UAV is selected to obtain high-resolution video frame images by designing and planning a reasonable flight path, and generate detailed 3D models of complex shaped ancient buildings using SfM algorithms. Taking the Ming dynasty drum tower in Xingqing district, Yinchuan city, Ningxia as an example, we quantify the variability of the three platforms in terms of modeling efficiency and modeling quality, and explore the optimal platform using strategy. The results show that the 3D reconstruction method can efficiently achieve the acquisition of fine texture on the surface of complex heterogeneous ancient buildings and the reconstruction of realistic 3D models, in which the modeling effect of ContextCapture platform is better than PhotoScan and RealityCapture platform, and the modeling quality and texture clarity are better, so it is recommended to use ContextCapture platform for 3D reconstruction. The method in this paper can provide a basis for the 3D reconstruction strategy for the conservation of complex heterogeneous ancient buildings, which has the prospect of wide application.

Texture mapping for real-scene 3D model and real-time video image fusion

YANG Song, CHEN Chongcheng

2023, 0(10):  61-66.  doi:10.13474/j.cnki.11-2246.2023.0296

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Aiming at the problems of fragmentation of video texture, obvious fusion boundary difference and poor real-time performance of video stream when merging real-time video and real-time 3D model, an improved real-time 3D model and real-time video image fusion method is proposed. Firstly, we use oblique photogrammetry technology to construct a real-scene 3D model, build streaming media to realize real-time transmission of video images to 3D scenes, match the corresponding relationship between video pixels and real-scene model fragment vertices. Then introduce a flattening mapping strategy that takes into account the depth of the scene to eliminate texture splitting when the video is integrated into the model. Finally the transition at the fusion seam is smoother based on the distance mask. The experimental results show that the mapping strategy proposed in this paper has an excellent fusion effect, which can eliminate the fragmentation phenomenon of the fusion screen and the abrupt feeling of the fusion boundary, and the frame rate of the scene is above 50 frame/s in the case of fusion of multi-channel video. The system has a good carrying capacity and real-time performance is good, and the results can be applied to construct a digital twin scene of real-time fusion of virtual and real.

Real-time 3D reconstructive techniques for 2D LiDAR

CHEN Tianyu, SUN Lishuang, CHE Defu

2023, 0(10):  67-73.  doi:10.13474/j.cnki.11-2246.2023.0297

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The development of LiDAR ranging technology provides a new technical means for the acquisition of 3D spatial data, which enables people to realize the transformation from traditional manual single-point data acquisition to continuous automatic data acquisition, greatly improving the speed and accuracy of measurement. However, the current 3D LiDAR data acquisition equipment has the disadvantages of expensive price, poor mobility, large data volume and long time for 3D reconstruction. In this paper, a two-dimensional laser scanner is proposed to obtain the three-dimensional point cloud through the spatial coordinate transformation alg orithm. The rotation and translation matrix obtained from the point cloud registration is optimized through the quaternion algorithm, and the optimal rotation and translation matrix is obtained through multiple iterations, so as to improve the speed and accuracy of point cloud registration. The experimental application analysis results show that the real-time 3D reconstruction method of two-dimensional laser radar proposed in this paper has the characteristics of low cost, high accuracy and fast 3D reconstruction, and meets the mapping requirements of on-site low-cost, real-time and accurate 3D reconstruction.

High-resolution remote sensing image classification based on multi-feature collaborative deep network

HU Chunxia, NIE Xiangyu, LIN Cong, FU Junhao, CHU Zhengwei

2023, 0(10):  74-79,104.  doi:10.13474/j.cnki.11-2246.2023.0298

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The classification of high-resolution remote sensing image (HSRI) based on deep convolutional neural network (DCNN) is one of the hotspots in remote sensing intelligent interpretation technology. However, existing classification networks rarely exploited the collaborative effect of multi-features, and cannot capture the complex spatial relationships of ground objects in HSRI. In order to further utilize spatial information and improve classification accuracy, we propose a multi-features collaborative deep network (MFCDN). In the proposed method, multi-type shallow features are first extracted as the input of MFCDN. Then, the multi-scale feature extraction module is utilized to extract the feature information of different spatial scales. Next, after dynamic weighting by channel and spatial attention mechanisms, multiple feature extraction layers and down-sampling layers are used to extract semantic information and perform feature fusion by element-by-element addition. Finally, the classification results are obtained through the multilayer perceptron combined with the Softmax function. Experimental results demonstrate that the proposed MFCDN outperforms other related methods in teams of classification accuracy and generalization performance.

Extraction of curved metro tunnel section based on point cloud

XU Jingtian, SHAN Siao, YU Ruihan, WU Lei, CHEN Gang

2023, 0(10):  80-84,122.  doi:10.13474/j.cnki.11-2246.2023.0299

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3D laser scanning technology has been widely used in the deformation monitoring of metro tunnels during the operation period. In view of the problems and shortcomings of common methods for obtaining the central axis of metro tunnel,based on the elevation difference of metro tunnel point cloud,this paper extracts the tunnel crown point cloud and fits the curve,and uses the crown axis instead of the central axis to extract the curved metro tunnel section continuously. Aiming at the problems of complex process and low efficiency of traditional section denoising methods,a radius filtering denoising algorithm based on the geometric characteristics of tunnel section is improved,and the denoised section points are compared by ellipse fitting. The experiment is carried out with the point cloud data of a curved metro tunnel in Wuhan. The results show that the method of extracting the curved metro tunnel section by replacing the central axis with the crown axis is accurate and reliable,and the improved section denoising algorithm is simple and efficient,which can improve the efficiency of tunnel deformation monitoring.

Ground extraction of oblique photography point cloud in construction site based on improved cloth simulation filtering algorithm

WANG Peng, XIN Peikang, LIU Yin, YU Fangqiang

2023, 0(10):  85-90,110.  doi:10.13474/j.cnki.11-2246.2023.0300

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There are a large number of non-ground points in the origin oblique photography point cloud of the construction site. Therefore, it is necessary to adopt appropriate algorithms to filter the non-ground points and extract the ground points. Most of existing filtering algorithms are designed for LiDAR point clouds, and generally have defects like complex parameter settings and poor terrain adaptability. On the basis of cloth simulation filtering (CSF) algorithm, this paper proposes an improved CSF algorithm combining target detection algorithm and terrain analysis method for oblique photography point clouds,implements automatic filtering and ground extraction of oblique photography point clouds in complex scenes.Taking a construction site in Shenzhen as an example, the experimental results show that the type Ⅰ, type Ⅱ error and total error of the improved algorithm proposed in this paper are significantly lower than those of the conventional algorithm, which are 1.11%, 6.36% and 2.39% respectively,and the Kappa coefficient reaches 93.45%,which effectively improves the precision and robustness of the ground extraction of oblique photography point clouds in the construction site.

Research of visible light positioning system based on BES-RBF neural network

WANG Lingyan, QIN Ling, GUO Ying, XU Yanhong, ZHAO Desheng

2023, 0(10):  91-97,128.  doi:10.13474/j.cnki.11-2246.2023.0301

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With the rapid development of science and technology, positioning in the ideal visible channel model can no longer meet the practical application requirements. The positioning system model established in this paper considers the direct link of visible light and a reflection of irregular walls.Based on this single LED lamp model, a bald eagle search algorithm is proposed to optimize of radial basis network (BES-RBF). The positioning system first optimizes the initial weights and thresholds of the radial basis function (RBF) neural network through the bald eagle search algorithm to make the structure of the optimized RBF neural network more stable. Then, the fingerprint database data consisting of the light power values received by each PDs of the receiver is introduced into the optimized RBF network model for training, and the positioning model is established. After the location information is obtained, some points are corrected by WKNN to obtain the final location information. In 3 m×3 m×3 m space, the simulation results show that, the average positioning error of the algorithm proposed in this paper is 5.54 cm, and 80% of the positioning error is within 4.5 cm. Compared with other positioning algorithms, the positioning accuracy has been significantly improved.

GNSS-IR multi-satellite dual-frequency combination soil moisture inversion combined with machine learning

NIE Shihai, WANG Long, WANG Mengke, LI Peng, LIANG Lei, HUANG Danni, LIU Bin

2023, 0(10):  98-104.  doi:10.13474/j.cnki.11-2246.2023.0302

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In order to improve the accuracy of soil moisture inversion and overcome the shortcomings of soil moisture inversion based on single satellite and single frequency point, this paper proposes a soil moisture inversion method based on GNSS-IR multi-satellite dual-frequency combination combined with machine learning. By using the SNR of GNSS satellite L1 and L2 frequency points as the data source, the soil moisture inversion is studied. The BP and RBF neural network algorithms are used to construct the soil moisture prediction model, and compared with the linear regression prediction model. The experimental results show that:①Compared with the single satellite, the soil moisture inversion of multi-satellite combination increases the effective satellite utilization rate and improves the accuracy of soil moisture inversion. ②The correlation coefficient between L1 and L2 dual-frequency mean fusion delay phase observations of multi-satellite combination and soil moisture is 0.956, which is better than the inversion results of L1 and L2 frequency points. ③The prediction accuracy of BP and RBF neural network models is better than that of ULR model.

3D and 2D LiDAR scan calibration method in heavy-haul railway detection equipment

CAO Haibin, WANG Xinping, WANG Wenbin, ZHANG Zhengjun, YIN Taijun, ZENG Shan

2023, 0(10):  105-110.  doi:10.13474/j.cnki.11-2246.2023.0303

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The heavy-haul railway has a large traffic volume, heavy load and fast line wear and deterioration. In order to ensure the transportation safety,it is necessary to carry out static inspection and measurement on the line frequently and regularly.The mobile 3D laser system based on rail can quickly scan and efficiently obtain the 3D reality of railway passage,which is becoming a new method of heavy haul railway infrastructure measurement and detection. However,due to the limitation of the low accuracy of 3D laser data,it cannot accurately measure the track profile. This project designed a heavy duty railway inspection equipment integrating 3D phase laser scanner and 2D line laser scanner. In this paper,the calibration method of 3D and 2D laser scanner is proposed. Experimental result shows that the method can realize the accurate fusion of 3D laser data and 2D line laser data better less than 2 mm,which lays a good data foundation for the subsequent integrated measurement and analysis of railway infrastructure based on millimeter high-precision 3D laser point data.

The development status and key technologies of intelligent check for “problem maps”

LIANG Yu, ZUO Dong

2023, 0(10):  111-116.  doi:10.13474/j.cnki.11-2246.2023.0304

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In order to promote the development of the surveying and mapping geographic information industry and the research progress of intelligent check for problem map under the premise of protecting national territorial sovereignty and geographic information security, this paper summarizes the development status of problem mapcheck and analyzes the pain points of problem map intelligent check.This study proposes key technologies such as obtaining training samples through geospatial big data mining technology, which includes a unified map review and unified calculation model. This paper is able to have positive references and promotion effect on the progress of intelligent check of problem map.

Shallow water depth measurement based on fusion of active and passive optical satellite remote sensing data

ZHANG Chunling, LI Youzhi, ZHANG Gang, QIU Zhenge

2023, 0(10):  117-122.  doi:10.13474/j.cnki.11-2246.2023.0305

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Aiming at the bathymetric error caused by the uncertainty of water surface elevation in dual-medium stereo photogrammetry, a technical route of shallow water depth measurement based on fusion of active and passive optical satellite remote sensing data is proposed, and the bathymetric model of integrating active ICESat-2 laser altimetry data and passive WorldView-3 stereo image pair data is studied. Firstly, the sea surface elevation is extracted from ICESat-2 laser altimetry data as the starting position for water surface elevation correction of WorldView-3 stereo image pair data. Then the appropriate water depth correction is added using the quadratic polynomial of the area network parity. A shallow water bathymetry experiment is carried out on the fusion of active and passive optical satellite remote sensing data in South China Sea. The results show that the root mean square error (RMSE) of the active and passive fusion bathymetry model is less than 0.70 m. The active-passive fusion bathymetric model realizes high-precision shallow water bathymetry without measured control points.

The measurement method for the silt dam technical index based on the principle of field of vision

YANG Xiangwei, JIN Meijun, LUO Ke, MA Chen, WANG Kang, TIAN Yuansheng, ZHANG Ping

2023, 0(10):  123-128.  doi:10.13474/j.cnki.11-2246.2023.0306

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In the Loess Plateau, the construction of a silt dam is an essential component of erosion management. The goals of the research presented in this paper are as follows: providing technical data for dynamic assessment of silt dam stability and operation management; developing measurement methods that are efficient and accurate for technical indicators of silt dams; and mastering the changes that occur in technical parameters due to the complex operating environment of silt dams. Based on the field-of-view principle, this paper builds four types of mathematical geometric models of silt dams, such as length, area, height, and slope, and designs feature image acquisition and screening, feature target interpretation, and data extraction schemes to carry out an example measurement study of silt dam technical indicators. The maximum error of the measurement method developed in this paper is -3.48%, and the measurement accuracy of different types of indicators varies. The average measurement error for dam crest length, dam crest width, water transfer culvert, and siltation elevation is less than 1%; the average error for spillway and open channel is less than 2%; and the average error for dam height, siltation area, and dam slope ratio is less than 3.5%. The silt dam technical index measurement method proposed in this paper is well-designed, with small measurement errors and efficient and accurate measurement characteristics.

Research on calculation model of soil and rock volume of mine ecological restoration using aerial survey data

ZHANG Ge, GOU Yuanpei

2023, 0(10):  129-134.  doi:10.13474/j.cnki.11-2246.2023.0307

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In the process of mine ecological restoration, large-scale calculation of earth and rock quantity is involved, and the calculation of earth and rock quantity can usually adopt two methods: scatter method or digital elevation model method. With the development of UAV aerial survey technology, scatter method is also called point cloud method. This paper aims at the reliability of calculation accuracy of earth and rock in the process of ecological restoration in mines. In this paper, the point cloud data of UAV aerial survey data is used to establish the triangulation irregular network model by taking the terrain property line as the characteristic line, giving full play to the advantages of easy operation and many applicable software. This paper studies the method of building the calculation model of soil and rock volume, and verifies the accuracy by comparing and analyzing the calculation results of DEM data, and obtains the complete model building method, so as to get the calculation results of soil and rock volume quickly and accurately, which has great popularization value.

The adaptive simplification of rail profile point cloud using fusion clustering algorithm

ZHANG Haishan, ZHANG Zhengjun, SONG Zongying, LIU Hongli, JIANG Dazuo, ZENG Shan

2023, 0(10):  135-139.  doi:10.13474/j.cnki.11-2246.2023.0308

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To address the problems of large data volume,strong noise,and abundant outliers in the raw structured light rail profile point cloud data,this paper proposes a rail point cloud adaptive simplification method that combines Euclidean clustering with various traditional filtering methods. A clustering segmentation method based on the Euclidean distance of point clouds is proposed to identify and simplify invalid scattered point data. A statistical filter combined with uniform voxel down sampling is used for initial noise reduction. Based on this,Segmentation of noise by Euclidean clusters,an adaptive pass-through filter that automatically acquires the filtering range is used to remove rail bottom adhesion data to ensure the efficiency and accuracy of point cloud registration. The proposed method can effectively simplify invalid data and reduce noise,achieving a point cloud simplification rate of about 94%,while retaining the effective profile features of the original point cloud,which lays the foundation for high-precision identification of point cloud registration and wear points.

The application of free base station vehicle scanning measurement system in the quality inspection

WEN Zhengbing, MAO Mingkai

2023, 0(10):  140-144,149.  doi:10.13474/j.cnki.11-2246.2023.0309

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Vehicle laser scanning technology in poor operation need to set up the base stations post-processing decomposition, and can only be carried out within a certain range in the base station to collect, limitation is very big, in order to solve this situation, this paper proposes a free base station scanning technology, by adding RTK module, using the tracks of fixed point of single point positioning solution to correct the post-processing, and very good solve the problem of the accuracy, This method eliminates the labor time cost caused by the erection of base station, Improved scanning efficiency by half, reduced staffing costs by half,and the scanning can be planned freely, which further optimizes the scheme of vehicle-mounted mobile scanning for the inspection work, and improves the inspection efficiency. The test results show that the accuracy of this scheme is comparable to that of the base station erection scheme, and the scanning efficiency is greatly improved.

Application of line segment detector algorithm in extracting building contour lines from airborne LiDAR

LIU Jianxing, HU Quanyi, LE Meiyan, SHU Sihong

2023, 0(10):  145-149.  doi:10.13474/j.cnki.11-2246.2023.0310

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To address the problem of time-consuming and low accuracy of extracting building contour lines from airborne LiDAR point cloud data, this paper proposes an (line segment detector)LSD-based method for extracting building contour lines from airborne LiDAR. The method first rasterizes the classified building point clouds to obtain the binary image.Then, the binary image is expanded and eroded to eliminate the voids generated by the rasterization. Finally, the LSD algorithm is used for straight line detection to obtain the regular building contour lines. Using the measured data for verification, the proposed method can detect the building contour lines with sub-pixel accuracy, which is about 50 times more efficient than the traditional Canny algorithm.

Application of 3D realistic geospatial scene in natural resources monitoring

HUANG Mingwei, LI Mengmeng, CHEN Chao, YU Yao

2023, 0(10):  150-153.  doi:10.13474/j.cnki.11-2246.2023.0311

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In order to accelerate the construction of a unified monitoring system for provincial natural resources, we provide high-quality monitoring results and geographic information services by building a real 3D digital base that can be interconnected with real scenes. Under the framework of unified survey, with carrying out the monitoring of natural resources, we study the practical application of natural resources survey and monitoring based on 3D realistic geospatial scene. Taking natural resources monitoring provincial pilot of Changshu city for instance, the paper uses the technology of 3D realistic geospatial scene in order to provide the protection and management of natural resources in Changshu. The pilot results show that the multi-scale, time-series, and related 3D technology of real scene has strong expressiveness, accurate analysis results, and excellent monitoring effect, which can support the natural resource monitoring application scenarios with high quality.

Building mesh model facade trimming in real 3D modeling

YANG Yonglin, LIU Dong, LIU Yang, SHI Xian, WANG Shuangyu, TAN Tian

2023, 0(10):  154-157.  doi:10.13474/j.cnki.11-2246.2023.0312

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As the data base in the construction of 3D real scene in China, 3D real scene model plays an extremely important role. Mesh model of building is an important data in the real 3D model, and its quality directly affects the use effect of the real 3D model. Based on practical engineering experience, a mass mesh model facade dressing method is proposed. Firstly, vector contours of the building are collected based on ContextCapture 3D model. Secondly, the parametric modeling software is used to generate the flat three-dimensional vector plane of the building in batches, and the adsorption of the building facade to the three-dimensional vector plane is automatically completed to make the building facade structure flat. Finally, taking the restored building mesh model as reference, the texture mapping of the building mesh model is carried out in ContextCapture software, and the batch update of the building mesh model is completed. The effectiveness and efficiency of the proposed method are verified by several test scenarios.

A multi-source land subsidence monitoring data fusion method and its application

GAO Jiandong, WANG Yong, AN Jianglei, JIANG Jundi

2023, 0(10):  158-162,172.  doi:10.13474/j.cnki.11-2246.2023.0313

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In this paper, the fusion of multi-source ground subsidence monitoring data is carried out by using three technical means: precision level, GNSS and time-series InSAR. Firstly, the spatial and temporal references of the three monitoring means are unified, then the Bland-Altman method is used to analyze the consistency of monitoring results, and the model relationship among monitoring data is established by the surface fitting method, and the surface monitoring results that integrated the advantages of precision level, GNSS and time-series InSAR are obtained. The results show that the main subsidence areas in the study area are located in Anguo town, Longgu town, Zhuzhai town, Datun street and Fengxian Sub-Fengcheng street of Pei county, and mineral resource exploitation is the main factor leading to regional subsidence. The maximum subsidence rate during the monitoring cycle is 29.8 mm/a, and the subsidence area with ground subsidence rate over 10 mm/a is 2 018.8 km², accounting for 61.9% of the total area.

Retrieval analysis of atmospheric precipitable water vapor from multi-system GNSS in the Guangdong-Hong Kong-Macao Greater Bay Area

ZHU Xiaowu, DUAN Hongshan, CHEN Guoheng, LIU Lei

2023, 0(10):  163-167.  doi:10.13474/j.cnki.11-2246.2023.0314

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GNSS water vapor detection is an important technical means to reflect the formation and evolution of severe weather. In order to expand the operational application of Marine observation in the Guangdong-Hong Kong-Macao Greater Bay Area mainly based on BDS, this paper took coastal cities in the Greater Bay Area as an example, and selected August, which was heavily affected by Marine disasters such as typhoons, storm surges and heavy rainfall, to analyze the variation characteristics of multi-system GNSS atmospheric precipitation (PWV)using GPS,BDS,GLONASS,Galileo retrieval.The results show that, compared with radiosonde data, the correlation coefficients of each satellite system are all greater than 0.9, showing strong correlation and high inversion accuracy; Combined with the actual rainfall monitoring of meteorological stations in the experimental area, the accumulation of PWV will produce rainfall. The average PWV of all satellite systems in August is 53～60 mm, which is consistent with the spatial distribution of actual rainfall.Therefore, comprehensively considering the advantages of GNSS in ocean observation and disaster prevention and mitigation, it provides ideas for the layout of near-shore multi-mode GNSS network.

Comprehensive reform and practice of cultivating innovative talent for surveying and mapping specialty in local universities

CHENG Xiaoqian, ZOU Youfeng, CHENG Gang, GUO Baoyu

2023, 0(10):  168-172.  doi:10.13474/j.cnki.11-2246.2023.0315

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The cultivation of innovative talents in surveying and mapping is not only the requirement forthe talent fostering mode of colleges anduniversities in the new era, but also an important measure for China to implement the powerful talent strategy in surveying and mapping geographic information.At present,the cultivation of surveying and mapping talents in colleges and universities exists such phenomena as “valuing theory over ability” “valuing knowledge over quality”“shaping commonality and lacking individuality”which leads to the problems of weak innovation consciousness, insufficient innovative thinking and weak innovation ability among students. Based on the connotation of innovative talents, the school of the author has established the “1+4+5”surveying and mapping talent training model of “one center, four integration, and five party building+” to strengthen the improvement of innovation awareness and innovation ability, which has achieved remarkable results. It provides a reference example for the reform of talent training in similar universities, and is of certain theoretical and practical significance.

Application of the backpack laser scanning on steep reservoir bank monitoring: taking the typical reach of the reservoir area of Baihetan hydropower station

YE Fei, ZHANG Shiming, SUN Zhenyong, ZHENG Yahui, SHI Yicheng

2023, 0(10):  173-176.  doi:10.13474/j.cnki.11-2246.2023.0316

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Aiming at the problems of steep bank and reservoir bank slope, narrow and complex terrain, high vegetation coverage, high monitoring accuracy of hydrology and sediment, and the difficulty, low efficiency and high risk of traditional manual measurement, this paper proposes a 3D laser scanning system observation method with mobile backpack.Taking the typical reaches of Baihetan hydropower station as an example, the application test of the mobile backpack 3D laser scanning system is carried out.The results show that the moving backpack 3D laser scanning system has a median error of 0.024 m, a median error of 0.044 m, and a relative area difference of 0.24%. The accuracy meets the technical requirements, and the work efficiency is 3.75 times higher than that of manual walking, and it is more suitable for the monitoring of the steep bank reservoir.

Study on construction measurement and control technology of quasi-rectangular shield tunnel

JIANG Leilei, HU Shangheng, XU Jiaohuang

2023, 0(10):  177-181.  doi:10.13474/j.cnki.11-2246.2023.0317

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The characteristics of quasi-rectangular shield tunnel are analyzed. The differences are contrasted and analyzed with the traditional circular shield tunnel. The construction measurement methods of quasi-rectangular shield tunnel are optimized. Three-dimensional laser scanning technology is introduced to measure the section, which solved the problem that the common section scanning technology could not accurately extract the center of the single side tunnel, The measurement and extraction of quasi-rectangular section are successfully completed.