Table of Content

25 September 2021, Volume 0 Issue 9

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DMSP-OLS and NPP-VIIRS night light image correction in China

GUAN Jingyun, LI Dong, WANG Yafei, WANG Xinyun

2021, 0(9):  1-8.  doi:10.13474/j.cnki.11-2246.2021.0264

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Based on the improvement of the traditional invariant target area correction method, this study selects the four-phase radiometric calibration reference image to perform saturation correction and time series continuity correction for DMSP-OLS images.The threshold method was used to remove the background noise and abnormal values of the NPP-VIIRS image, and the dynamic range of the light radiation value is compressed by the logarithmic transformation so that the brightness distribution is closer to the DMSP-OLS data.Then the NPP-VIIRS image was uniformly corrected through the BiDoseResp function model, and the long-time sequence of night light images from 1992 to 2019 was obtained.Finally, the accuracy of the calibration results is verified in terms of qualitative, quantitative, and the correlation between the corrected image and the socio-economic parameters.The results show that the improved correction method improves the severe saturation of DMSP-OLS images, and makes it obtain the longitudinal comparability of long-term series.The BiDoseResp function model can fit the regression between DMSP-OLS and logarithmic transformation NPP-VIIRS well.The corrected long-term sequence of light image data is highly consistent with the socio-economic parameters. The correction results are of great value to promote the wide application of long-time sequence night light images and to deepen the research of long-term sequence scientific problems.

Atmospheric correction of inland lake water based on Sentinel-2 satellite data

MU Chao, LIU Zhenyu, MENG Dan

2021, 0(9):  9-14.  doi:10.13474/j.cnki.11-2246.2021.0265

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Referring to the historical measured remote sensing reflectance data, the atmospheric correction of inland lake water acquired by Sentinel-2 satellite is carried out by correction algorithms Acolite, FLAASH and C2RCC. The experimental results show that, numerically, the correction results of C2RCC are in the same order of magnitude as the measured results, and the correction results of Acolite and FLAASH are overestimated. In terms of the variation trend of spectral curve, the correction results of C2RCC are similar to the measured data, and the correction results of Acolite and FLAASH are abnormal. Therefore, it is recommended to use C2RCC atmospheric correction for Sentinel-2 inland water data. If only the first five wavebands are considered, the curve trend of the correction result of Acolite is close to the measured spectrum. As the correction result is overestimated, it is recommended to use the band ratio to eliminate the overestimation.

3D point cloud indoor plane element extraction and optimization methodology

SONG Jinyang, QIAN Jianguo, TANG Shengjun, WANG Weixi, LI Xiaoming

2021, 0(9):  15-20,27.  doi:10.13474/j.cnki.11-2246.2021.0266

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The accurate extraction and relationship restoration of indoor plane elements is an important basis for the automatic semantic reconstruction of indoor models. This paper proposes an indoor plane element extraction and optimization method for complex three-dimensional point clouds, which firstly uses area growth and RANSAC planar hybrid segmentation methods to segment indoor point cloud data; and then uses spatial location information of indoor semantic components as well as bounding box and normal vector information, the planar elements of the segmented plane are extracted accurately; then the extracted walls are optimized to achieve the merging of shared walls and solve the problem of indoor wall redundancy; finally, the spatial location information of doors and walls is used to restore the door-wall association relationship. In the experimental part, two sets of experimental data are used:one set is the laser point cloud data of a teaching floor of Shenzhen University, the other set is the standard data of International Society for Photogrammetry and Remote Sensing (ISPRS), and the validity and reliability of the method of this paper are verified by evaluating the experimental results.

An optimized Faster R-CNN small target detection method

CHENG Rui, GAO Jian, XING Qiang, SUN Zhongchang

2021, 0(9):  21-27.  doi:10.13474/j.cnki.11-2246.2021.0267

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Image object detection is a popular direction in computer vision and digital image processing. Its main task is to find out the object of interest in the image and determine the location and category of the object. The current mainstream object detection algorithms are mainly based on deep learning models, and it has become a trend to solve many disciplinary problems. This article uses a method based on the combination of the regional convolutional neural network (Faster R-CNN) deep learning algorithm and related image processing algorithms,using ResNet50 and ResNet101 as the backbone network and using feature pyramid networks to monitor the changes of vehicles in Wuhan during the new crown epidemic to analyze the intensity of internal activities in Wuhan during the epidemic. The results show that the accuracy rate of the image detection method in this paper is 0.96, the recall rate is 0.915, and the average accuracy is 0.853 8.The vehicle number changes before the epidemic (November 17, 2019) and during the epidemic (February 22, 2020) is as follows:Wuhan Convergence Center (263 and 32 vehicles), Wangjiazui Overpass (89 and 44 vehicles), Xinxing Industrial Park (554 and 347 vehicles), Jingkai Future City (188 and 57 vehicles). The epidemic has led to a decrease in population travel and vehicle activities in Wuhan.

Scanning ray truncation method for removing the noise point cloud inside buildings

WANG Guo, LI Feng, CHEN Chao, CAI Qingkong, YANG Yalun

2021, 0(9):  28-31.  doi:10.13474/j.cnki.11-2246.2021.0268

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Due to different styles of furniture and occlusion, the distribution of noise point cloud inside buildings is more complex and adhesion with building facade, which make it difficult to be removed by interactive way. In order to solve this problem, a scanning ray truncation method is proposed in this paper. Firstly, the building surface is segmented, and then the intersection between the scanning ray composed of the scanning center point and the point cloud and the building facade is obtained. By comparing the length of the scanning ray with the distance between the scanning center point and the intersection point, the scanning ray can be cut off by the building facade, so as to remove the interior noise point cloud automatically while maintaining the original sampling interval. The experimental results show that the proposed method can effectively remove the interior noise points.

ORB-SLAM method based on local adaptive threshold extraction feature points

LI Guojun, XU Yanhai, DUAN Jiewen, HAN Shilei

2021, 0(9):  32-36,48.  doi:10.13474/j.cnki.11-2246.2021.0269

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Localization and mapping of intelligent driving vehicles is one of the key technologies of intelligent driving vehicles. Aiming at the problem of feature points extracted as fixed threshold in ORB-SLAM a local adaptive threshold method is proposed to extract feature points.Firstly, the calculation method of local adaptive threshold is described, and the adaptive threshold is set by image contrast.Secondly, Gaussian image pyramid is constructed on the basis of FAST algorithm and gray-scale centroid method is adopted to solve the scale invariant and rotation problem of feature points. The image grid area is divided in each layer of image pyramid and the contrast of each layer of image grid area is calculated to set the local threshold of each grid area.Finally, feature points are extracted in each image grid area and stored in quadtree structure.The test results show that the number of feature points extracted by the proposed algorithm is 61.9% more than that extracted by the original algorithm in cloudy days, and 23.3% more than that extracted by the original algorithm in sunny days.In cloudy and well-lit scenes, the fluctuation of the number of feature points extracted by this algorithm is less than that of the original algorithm.

High-resolution remote sensing image classification based on multi-feature popular discrimination embedding

YANG Sufang, DU Lin

2021, 0(9):  37-42.  doi:10.13474/j.cnki.11-2246.2021.0270

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In order to solve the problem of poor accuracy of single feature classification caused by the "same spectrum foreign body, same body foreign spectrum" of high-resolution remote sensing image, a high-resolution remote sensing image classification method based on multi-feature manifold discrimination embedding is proposed in this paper. Firstly, the spectral features and LBP texture features of high-resolution image data are extracted. Then, through the joint spectrum of sample data, the spatial distance of texture features and the corresponding category information, the inter class and intra class graphs of image objects are constructed to learn the discriminative manifold structure on high-resolution images, so as to ensure that the features of different features in the embedded space are separated as far as possible, the same ground features are closely clustered to ensure the similarity of spectral and texture features of the same ground features, and complete the effective extraction of spectral and texture identification features, so as to fully mine image features and effectively improve the classification accuracy of images. Experimental results on GF-2 remote sensing data set show that the proposed algorithm can effectively fuse multiple features, and the classification accuracy can reach 93.41%, which is better than the traditional methods.

Application of UAV tilt photogrammetry technology for demarcation of nature reserve

ZHOU Yangyang, XU Shangzhao, CHEN Bin, ZHANG Qingfeng

2021, 0(9):  43-48.  doi:10.13474/j.cnki.11-2246.2021.0271

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With the implementation of integration and optimization of natural protected areas, as well as the progress of boundary surveying and piles setting, the requirements for current status and accuracy of boundary surveying results are increasing. In order to solve the problems in traditional demarcation work, such as not advanced monitoring technology, labor-intensive work, inaccurate results, and unobjective boundaries, etc. This paper proposes a research proposal on the basis of drone tilt photogrammetry, Google map and digital orthophoto, human surveying is liberated while combining the photogrammetry and field surveying, and the boundaries of nature reserve that meet the accuracy requirements would be rapidly identified and extracted. A case study of Beijiang special rare fish provincial nature reserve in Shaoguan is performed, the 1:500 real-scene 3D model is obtained, which could possibly provide clear and reliable background data for the work of "building a special ecological reserve in northern Guangdong with high standards, and do well in the optimization and integration of nature reserves". The results show that the technology is advanced and mature, with a high degree of automation, and can meet the accuracy requirements of boundary surveying. It has broad exploration potential and application prospects, and is easy to be promoted.

Application of MSSA in GPS coodinate series analysis

QIAN Wei, YUE Jianping

2021, 0(9):  49-52,63.  doi:10.13474/j.cnki.11-2246.2021.0272

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The coordinate series of four CMONOC stations located in Yunnan province are selected as the experimental objects, and the multichannel singular spectrum analysis(MSSA) is used to interpolate its missing data and extract its seasonal signal. The results show that the precision of iterative interpolation of MSSA is better than 1.5 mm in the horizontal direction and 4 mm in the vertical direction, both better than cubic spline interpolation and the superiority is still not be lost when the missing rate of the sequence increases and the continuity decreases. Comparing MSSA and leastsquare fit methods to extra ctseasonal signal extraction effect and analyze its residual sequence and power spectrum, it is found that MSSA can effectively extract different periodic signals and is more suitable for time-varying seasons with inconstant amplitude signal.

Monitoring land subsidence in Wuhan city based on Sentinel-1

HUANG Jiabin, GUO Yunkai, LUO Weimao

2021, 0(9):  53-58.  doi:10.13474/j.cnki.11-2246.2021.0273

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Due to the construction of underground space planning projects in major cities, there are different degrees of land subsidence geological disasters. In this paper, sentinel-1A data from June 2020 to March 2021 in the main urban area of Wuhan city is selected as the data source, and the small baseline set technology is used to monitor the surface deformation in this area. The results can provide basic support for the prevention and control of land subsidence and the occurrence and development of disaster chain.

Detection and extraction of urban road intersections using GPS trajectories of floating vehicles

MENG Qiuyu, SONG Ziang, WANG Jin, GE Zhijin

2021, 0(9):  59-63.  doi:10.13474/j.cnki.11-2246.2021.0274

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Road intersection plays an important role in transport hub and road network, it's also the basic data of geographic information system. GPS trajectory data of floating vehicles is easy availability and low cost, but the data contains certain amounts of noises. To alleviate the impact of noise and improve compute efficiency of GPS data, this paper proposes a method to detect and extract urban road intersections. Construct data index based on the k-nearest neighbors (KNN) algorithm. Estimate the angles between vectors and coarsely detect road intersections. And then apply three clustering algorithms (K-means, DBSCAN and hierarchical clustering algorithms) to fine extracted road intersections. We test the proposed method on GPS dataset from Chengdu city to evaluate its performance. This research can be effectively used in practical intelligent transportation scenarios.

Application of 5G and high-precision positioning in military logistics warehousing application

GUO Ling, DU Weiwei, LIU Ling, LI Rui, WAN Ping

2021, 0(9):  64-67,97.  doi:10.13474/j.cnki.11-2246.2021.0275

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Military logistics warehousing has the effect of accelerating the circulation of military materials and improving the efficiency and quality of military logistics. Its modern information construction requires the support of communication technology and positioning technology. With the development of 5G communication technology and high-precision positioning technology, research the integration of BDS, UWB and 5G communications are important for the modernization of military logistics and warehouse applications. According to the needs and characteristics of military logistics warehouse construction, we research the independent and controllable indoor and outdoor high-precision combination, 5G communication mode, seamless indoor and outdoor positioning, the overall system architecture and the integration of positioning network and 5G communication. The impact of the construction of high-precision positioning network and 5G communication network on the development of military logistics and warehouse construction is proposed.

Dam deformation prediction model based on IBA-ELM model

CHEN Youliang, CHEN Yang, XIAO Gang, TAO Jianhui

2021, 0(9):  68-73.  doi:10.13474/j.cnki.11-2246.2021.0276

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Aiming at the problems of strong nonlinear relationship in dam deformation monitoring data and low precision of traditional dam prediction model, a dam deformation prediction model based on improved bat algorithm (IBA) and optimized extreme learning machine (ELM) is proposed by using the improved bat algorithm to select the optimal parameters as the connection weights and thresholds of the extreme learning machine(IBA-ELM). The IBA-ELM model is applied to an engineering case, and the accuracy of IBA-ELM, BA-ELM and GA-ELM model prediction results are evaluated through the prediction and analysis of dam monitoring data of a reservoir. The average absolute errors between predicted values and measured values are 1.178 3, 0.459 8 and 0.335 6, IBA-The prediction accuracy of ELM model is higher than the other two models, which indicates that IBA-ELM model can effectively improve the prediction ability of dam deformation and has certain application value.

The visual analysis of multi-source vector spatial data usability evaluation

CHEN Huanxin, MA Chao, ZHANG Jicai, CHEN Changlin, QIN Zhiqiang, MA Jingzhen, WANG Yaqun

2021, 0(9):  74-78.  doi:10.13474/j.cnki.11-2246.2021.0277

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This paper introduces visual analytics to the evaluation of multi-source vector spatial data usability, which offers the environment of visual analysis to the user. Analyzing the feasibility from concept and technique, the paper formulates the basic principles. Visualizing the multi-source spatial data, the usability evaluation is driven by user requirements, and then the relevant model program is triggered to calculate and visualize. Visual analysis can link the user demand, human cognition and usability evaluation models together through interactive interface. With the help of visual analytics, user can explore different aspects and details of multi-source vector spatial data, and then make scientific plan of data use based on obtaining the hidden knowledge. The experiments indicate that this method holds higher efficiency and better experience feeling.

Simplification of tilt photogrammetry 3D model and service release

ZHANG Huixia, LI Hao, LI Jinhong, ZHAO Fei

2021, 0(9):  79-82.  doi:10.13474/j.cnki.11-2246.2021.0278

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In order to provide services for relevant departments in population management and realize smart community. In this paper, we study the simplification and attribute query of three dimensional model of inclined photography in residential area. Through the simplification of three dimensional model data by layers and households, we establish a database, and release the simplification model and real 3D model on the network, so as to query the information of each house separately, and realize the beautification of pop-up window and the display of photo information through programming technology. Finally, a practical example shows that the method is feasible. The purpose of this study is to provide support for relevant departments to carry out population management services and realize smart community.

Expansion law analysis of Taiyuan built-up area in recent 50 years based on long time series of remote sensing data

ZHAO Hengyang, LIU Xin, ZHAO Shangmin

2021, 0(9):  83-88.  doi:10.13474/j.cnki.11-2246.2021.0279

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Based on remote sensing images of Taiyuan from 1973 to 2020, artificial visual interpretation and Google historical image correction are used to extract built-up areas. The compactness, expansion intensity, expansion speed and gravity center transfer model are introduced to analyze the spatiotemporal evolution characteristics of built-up areas in Taiyuan in the past 50 years. The main driving factors of expansion of Taiyuan built-up area are analyzed. The results show that:① From 1973 to 2020, the built-up area of Taiyuan has expanded by 15.12 times, with an average annual increase of 7.85 km²/a. The compactness of the built-up area is generally low and the expansion is obvious in the north-south direction. The center of gravity migrates more than 3500 m along the southwest direction of about 30°. ② The main factors causing the expansion of Taiyuan built-up areas are economy and population expansion, among which GNP and per capita GDP play a key role.

Image overlap calculation model and application in oblique photogrammetry

ZHAO Zhixing, LU Xiaohong, TIAN Xin, LIU Zhiqi

2021, 0(9):  89-92.  doi:10.13474/j.cnki.11-2246.2021.0280

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According to the position structure of the multi-lens cameras in the tilting aerial camera, the relationship between the corresponding coverage area of the oblique image, course, lateral overlap degree and flight speed, exposure interval time, route interval and other parameters is analyzed. On this basis, a formula for calculating the overlap degree of images taken by cameras at any number, any angle and any position is derived. The result proves that this method improves the accuracy of setting parameters of tilt photography and provides a necessary basis for the quality assurance of the later process.

Exploration on the production of high-resolution continuous DEM data based on LROC NAC images

MA Ding, ZHAO Shangmin, CHENG Weiming

2021, 0(9):  93-97.  doi:10.13474/j.cnki.11-2246.2021.0281

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DEM data with high-resolution and continuous surface is the main data source for obtaining lunar morphological features and performing digital terrain analysis. A region of Chang'E-5 candidate landing region is selected as the experimental area. First, high-resolution DEM data and corresponding DOM images are generated based on LROC NAC stereo images, ISIS3 and Stereo Pipeline software, and compared with Japanese SELENE (KAGUYA) TC images; Then, Inverse Distance Weighting, Radial Basis Function and Empirical Bayesian Kriging are used to interpolate the hollow areas of DEM data and cross validation analysis was performed for three different interpolation methods. The results show that the resolution of DEM and DOM generated in this study is about 3.5 m, which is obviously clearer than that of 7.4 m resolution Japanese TC images, and has stronger terrain expression ability; Radial Basis Function interpolation is the best method for hollow interpolation, and the mean square error of cross-validation is 0.26 m. The study has a certain role in accurately acquiring lunar morphological features and locating detectors, and provides a reference for high resolution continuous DEM data generation in other regions.

Long-term NDVI spatio-temporal variation trend and its response to climate in Xishan coalfield, Shanxi province

QI Danning, HU Zhengjun, ZHAO Shangmin

2021, 0(9):  98-102,107.  doi:10.13474/j.cnki.11-2246.2021.0282

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The study of vegetation changes in mining disturbed areas can provide a theoretical basis for ecological restoration in mining areas. This paper takes the Xishan coalfield in Shanxi province as the research area, establishes a comparative experimental area, and uses MODIS/NDVI (2001-2019) to combine the temperature and precipitation climate factors of the same period to analyze the temporal and spatial changes of the vegetation index and the relationship with meteorological factors. The comparison is carried out to explore the vegetation changes in the areas disturbed by mining. The research results show that:① In the past 19 years, the vegetation in the Xishan coalfield, the indirect impact area and the verification area showed an increasing trend, but the average NDVI of the Xishan coalfield was 11.42% lower than that in the verification area. ② The growth rate of vegetation in Xishan coalfield is -5.53% compared with natural ecological conditions. ③ The NDVI values of the Xishan coalfield and the verification area are both affected by two climatic factors, temperature and precipitation, but the correlation with precipitation is higher, that is, it is more affected by precipitation.

Application of Kalman filter in GNSS monitoring of ground subsidence in Xishan coalfield of Shanxi province

ZHANG Shifang, ZHANG Jin

2021, 0(9):  103-107.  doi:10.13474/j.cnki.11-2246.2021.0283

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Taking one working face of Xishan coalfield in Shanxi province as the experiment area, this paper processes and evaluates the GNSS (global navigation satellite system) monitoring data about mining ground subsidence using two Kalman filter methods (usual Kalman filter and total Kalman filter), on the basis of analyzing the data characteristics of GNSS monitoring data, and compares the distribution status of root mean square error (RMSE) of the two Kalman filter methods. The research results show that the tendency is similar between the filter results of the two methods and the observation values, although a few abnormal points exist. The difference between the filter results and the observation values becomes higher when the subsidence larger, and the difference for the total Kalman filter is much lower than the usual Kalman filter, especially for the monitoring points in the large subsidence area. The RMSE values increase with the rise of the subsidence for the monitoring points, and the increasing velocity for the total Kalman filter is much lower than the usual Kalman filter. The maximum RMSE value for the total Kalman filter is lower than 0.1 m, but it is approximate to 0.4 m for the usual Kalman filter.

Comparative analysis of hyperspectral remote sensing abnormal target detection methods

WANG Deqiang, ZHAO Deliang

2021, 0(9):  108-111.  doi:10.13474/j.cnki.11-2246.2021.0284

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This paper is based on the theory of hyperspectral remote sensing abnormal target detection, mainly explores several existing abnormal target detection methods, through the experimental comparison and analysis of the detection performance of each algorithm, in order to get a better detection method, and provide more support for hyperspectral remote sensing abnormal target detection. In this paper, through the experiment of three groups of data, and from the detection rate and false alarm rate, the area under the ROC curve and the running time of the algorithm, the detection performance of the above-mentioned anomaly detection algorithms is compared and analyzed. Finally, the detection effect of the algorithm based on the statistical model and the representation model is compared and analyzed, so as to obtain the more suitable for different data Detection method.

A mobile laser scanning 3D point cloud reconstruction for metro tunnels based on inertial navigation and CPⅢ control points

DING Xiaobing, GAO Zhiqiang, YANG Kun

2021, 0(9):  112-115,129.  doi:10.13474/j.cnki.11-2246.2021.0285

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Before the initial operation of metro tunnels, the construction quality and zero-state of tunnels need to be inspected. The traditional method uses a total station to measure feature points and sections of tunnel, which is heavy-workload, low-efficiency and single-result.To solve the above problems,this paper proposes a mobile laser scanning 3D point cloud reconstruction method for metro tunnels based on inertial navigation and CPⅢ control points, and then verifies the accuracy of point cloud of tunnel section,central axis and track centers, which meets the requirements of tunnel planning acceptance measurement. At the same time, this method can simultaneously obtain the horizontal diameter, pipe wall image, vertical section and cross section of the tunnel, which not only improves the operation efficiency, but also can be used as the zero state file of rail transit structure, so as to provide detailed basic data for metro tunnel tunnel planning acceptance measurement and later operation and maintenance.

Geomorphic features updating in small and medium scale by using high-resolution stereo mapping image

MA Yuanzheng, DOU Guanxin, LIU Yue, WU Yanping

2021, 0(9):  116-119.  doi:10.13474/j.cnki.11-2246.2021.0286

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Geomorphologic updating by using high-resolution stereo mapping satellite remote sensing image has great application potential in medium and small-scale geomorphic features updating because of its advantages of large coverage area and short updating period. In this paper, WorldView-2 and ZY-3 satellite images are respectively used to explore the technological process of small and medium scale geomorphic renewal based on high-resolution stereo mapping satellite images, and the experimental verification is carried out in different experimental areas. The results show that the proposed technical scheme can meet the accuracy requirements of 1:50 000 topographic map updating, and the updating efficiency is improved by about 25%.

Cross section extraction of tunnel point cloud based on ransac algorithm

DING Ge, YAN Lishuang, PENG Jian, ZHU Chuanguang, HUANG Xueting

2021, 0(9):  120-123.  doi:10.13474/j.cnki.11-2246.2021.0287

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Because it is difficult to get the best linear parameters by least square method by fitting all points, including "outliers", this paper presents a method based on RANSAC algorithm to estimate the parameters by random sampling the observed values, the "inner point" of the model is a consistent set until a sufficient consistent set is obtained under a certain number of iterations. The boundary of tunnel point cloud is extracted based on the method of central axis, which provides a reference for the application of 3D laser scanning in production.

Accuracy evaluation of GPS, BDS and GPS+BDS precise point positioning

LI Jiangang, LI Honghui, CHAI Xiangjun, WANG Tianyu

2021, 0(9):  124-129.  doi:10.13474/j.cnki.11-2246.2021.0288

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In view of the completion of BeiDou satellite network, it is necessary to evaluate and analyze the system performance of BDS. The 31 day observation data collected by multi GNSS experience network is selected to compare and analyze the precision of static and dynamic precise point positioning under different conditions of GPS, BDS and GPS+BDS. The experimental results show that the accuracy of GPS and BDS single system static PPP in N, E, U direction is better than 4, 4, 7 cm, respectively; GPS+BDS combined system static PPP accuracy in N, E, U direction is better than 3, 3, 6 cm; GPS single system dynamic PPP accuracy in N, E, U direction is better than 5, 5, 10 cm; BDS single system dynamic PPP accuracy in N, E, U direction is better than 5, 6, 12 cm; GPS+BDS integrated system dynamic PPP accuracy is better than 4, 4, 8 cm in N, E, U direction. So the integrated system can improve the stability and accuracy of positioning compared with single system, and the advantages of the combined system are more obvious in the case of dynamic PPP.

Automatic detection method of position and posture of high bridge piers based on detecting projection line of point cloud

HAN Fuqing, GUO Guohe, YANG Chengkun, WU Yongsheng, WANG Weili, LI Cailin

2021, 0(9):  130-135,150.  doi:10.13474/j.cnki.11-2246.2021.0289

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At present, there are some problems in the verticality detection methods of super-high bridge piers, such as high risk factors, difficult to guarantee the accuracy, or low automation and working efficiency. In view of the above problems, this paper presents an automatic detection method of position and posture of high bridge piers based on 3D laser scanning and massive point cloud. This method first layers massive pier point clouds in two directions, then selects layered files to detect the point clouds projection line and divides the pier surface buffer area according to the conditions, and finally automatic extracts the pier surface point cloud based on the buffer area and detected the position and posture. In this paper, an example of the position and posture detection of a high-speed bridge in a mountainous area is carried out. The experimental results show that this method has the advantages of no contact, high automation, high work efficiency and wide detection range.

Research on classification standard of natural resources: a case study in Yangshuo county, Guangxi

HUANG Jingjin, YANG Zhengbei, TANG Changzeng, REN Jianfu, LI Xindong, LI Cheng, HUANG Linghai, PAN Zhengqiang, ZHOU Guoqing

2021, 0(9):  136-139,156.  doi:10.13474/j.cnki.11-2246.2021.0290

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The unified classification standard of natural resources is an important content in the construction of natural resources survey and monitoring system. For a long time, Chinese land, mineral, forest, wetland, grassland, water and other administrative departments have used different definitions and classification conflicts. This paper analyzes the characteristics and problems of natural resources classification standards in different majors and periods by sorting out the common natural resources classification standards in China. In combination with the pilot investigation and monitoring of natural resources in Yangshuo, Guilin, Guangxi, and the overall planning of natural resources management, this paper puts forward the compilation idea of the classification system, classification code and definition of the unified classification standard of natural resources according to the existing classification systems of various natural resources and the principles of scientific nature, applicability and cohesion. Finally, from the point of view of the natural, management and ecological attributes of natural resources entity classification standard system are recrganized.

Application of two-dimensional Hash algorithm in geospatial data batch subdivision

XU Yifeng, CHEN Yu, CHENG Baoyin, ZHANG Meng

2021, 0(9):  140-144.  doi:10.13474/j.cnki.11-2246.2021.0291

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After the coordinate transformation of divisive geospatial data, it's necessary to re-divided in the new coordinate system. For the batch data, the search efficiency can be improved when judging the overlap of old and new mapsheets by the fast search algorithm. Firstly, the relationship between the old and the new mapsheets is established and the overlapping judgment method and the file storage mode of the segmented elements are determined. Then, the algorithm of constructing two-dimensional Hashtable with center point coordinates of new mapsheet as key-words and finding overlapped mapsheets is proposed. Finally, the algorithm design idea is realized, and the correctness and effectiveness of the algorithm are verified by computational examples in the paper. Compared with traditional methods, this algorithm has higher execution efficiency and is an ideal alternative algorithm.

Classification standard system of natural resources survey and monitoring in Guangdong province

YANG Nana, ZHANG Xinchang, ZHU Ziyang, CHUN Jin, JIN Shicheng

2021, 0(9):  145-150.  doi:10.13474/j.cnki.11-2246.2021.0292

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The classification of natural resources is the foundation of natural resources management and land spatial planning, and is the prerequisite for conducting survey and monitoring work. It should follow the concept that mountains, rivers, forests, fields, lakes and grasslands are a community of life. This article first comprehensively analyzes the current status and problems of existing natural resources classification standards, and then combines with the characteristics of Guangdong to conduct a preliminary discussion on the natural resources survey and monitoring classification standards of Guangdong province, and strives to solve the problems of different concepts, overlapping contents, and contradictory indicators in the existing natural resources classification. With a view to provide ideas for the ongoing pilot work of natural resources survey and monitoring in Guangdong province, and at the same time provides certain inspiration for the formulation of national natural resources classification standards.

Discussion and practice of surveying online teaching for non-surveying and mapping majors

GUO Wei, CUI Ximin, LI Jing, LI Jun, YUAN Debao, YAN Yueguan

2021, 0(9):  151-156.  doi:10.13474/j.cnki.11-2246.2021.0293

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In response to the coronavirus pneumonia, universities across the country responds to the call of the Ministry of Education "stop classes, but not stop teaching and learning". The large-scale online teaching practice is facing many challenges, but also for promoting education and information teaching ushered in a rare opportunity. How to improve the quality of personnel training and ensure the effect of online teaching is an important issue in the process of online teaching. This paper proposes a model based on BOPPPS and online teaching, which is used in surveying teaching for non-surveying and mapping majors. It aims to summarize some experience of online teaching in colleges and universities during the epidemic period, and provides theoretical basis and practical cases for the follow-up surveying information teaching.

Feasibility study on the application of 3D laser scanning technology in the direction of building facade digital acquisition and elevation drawing

HE Xiaodong

2021, 0(9):  157-159,164.  doi:10.13474/j.cnki.11-2246.2021.0294

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The three-dimensional (3D) laser scanning technology is used to collect the data of the building facade. The complete point cloud data of the building facade can be obtained by splicing, denoising, and extracting the collected 3D point cloud data. In this paper, the 3D laser scanner is used to obtain the data of the building facade quickly, and obtain the high-precision 3D point cloud. The position and size of each auxiliary object of the building facade can be drawn accurately and clearly by importing the 3D point cloud data into CAD for drawing to ensure the accuracy and usability of the elevation drawing.

Application of 3D laser scanning technology in evenness analysis of high-speed railway tunnel

TANG Dongyue, XIAO Shu'an, ZHOU Xinghua, ZHU Shuipeng

2021, 0(9):  160-164.  doi:10.13474/j.cnki.11-2246.2021.0295

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High-quality tunnel lining evenness not only has a vital impact on the second lining waterproof construction,but also guarantees the tunnel's linearity, uniform structural force, and lasting and effective waterproofing system during operation.The 3D laser scanning system is a comprehensive measurement technology that integrates optical, mechanical, electrical and information technology widely used in tunnel engineering in modern times. It provides a new and implementable method for the evenness analysis of the tunnel surface thanking to its rapid on-site massive point cloud collection and analysis capabilities. This paper focuses on the practice of combining high-density 3D laser scanning point clouds with 3D tunnel design and computer algorithms in Deqing tunnel, which realizes high-precision,exhaustive and visual evenness analysis.

Research on deformation monitoring based on Leica MS60 and depth image

MIN Xing, LUO Haitao, BAI Wenfeng

2021, 0(9):  165-168.  doi:10.13474/j.cnki.11-2246.2021.0296

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Leica MS60 can obtain not only high-precision single point coordinates, but also point cloud and image data. All these data, with their respective advantages, are in a common coordinate system, and this brings convenience for deformation monitoring. The telescope camera is used to gather the images of the monitoring area to form a panoramic image, and then combine the point cloud to construct a depth image. The three-dimensional displacement vectors of the area are obtained by multi-period depth image matching. The monitoring method based on depth image provides a new idea for deformation monitoring.