Table of Content

25 November 2022, Volume 0 Issue 11

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Monitoring technology of collapse and landslide disasters based on high-precision spatio-temporal information

HE Wei, ZHANG Lunning, ZENG Lu, ZHAO Qing, YU Guoxin, ZHU Keying, LI Kexin

2022, 0(11):  1-7.  doi:10.13474/j.cnki.11-2246.2022.0316

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China is a country with frequent geological disasters like landslides, mudslides, and so on, which bring great threats to the property and life safety of our people over the years. For this reason, the early warning of geological disasters has always been a difficult research problem in the emergency direction of China. With the construction and networking of global satellite navigation systems such as BeiDou and GPS, GNSS technology has gradually become an important means to provide spatio-temporal position information. It has the characteristics of real-time data, low power consumption of equipment, convenient construction, and so on, and has formally become an ideal technical means to solve the problems of geological disaster monitoring and early warning. In this paper, based on GNSS spatial and temporal information data including BeiDou and GPS and GLONASS, it constructed a medium-long baseline millimeter-level accuracy landslide monitoring solution method for geological disaster monitoring, and determined the carrier phase solution model of double-difference observation. Finally, with the field application in Xinpu area of Chongqing, it realized the millimeter landslide disaster monitoring and early warning based on high-precision spatio-temporal information. It provided data support for the prediction of geological disasters in this region and technical support for people's production and life.

Analysis of deformation evolution characteristics of Baige landslide before and after disaster based on improved TS-InSAR method

YU Bin, LI Song, XIE Lingxiao, JIA Hongguo, KANG Miaohang, LIU Yuxin, LIAO Mingjie, ZHANG Rui

2022, 0(11):  8-12.  doi:10.13474/j.cnki.11-2246.2022.0317

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From October to November 2018, the Baige landslide in the upper reaches of Jinsha River collapsed twice, causing a barrier lake, and there is still significant creep deformation. This paper proposed an improved TS-InSAR (ITSI) approach to acquire the landslide area's time series creep deformation measurements. Based on the SAR image data obtained by Sentinel-1A satellite from September. 2017 to March. 2021, the pre-disaster and post-disaster time series processing are carried out, and the annual average creep velocity field (the pre-disaster extreme value is 9.71cm/a, and the post-disaster extreme value is 25.42cm/a) and cumulative creep deformation measurements (the extreme value is over 13cm in the pre-disaster period, and it reaches 61cm within two years after the disaster) are extracted then. Combined with the deformation time series measurements obtained, the creep deformation's time series evolution characteristics are emphatically analyzed subsequently. The results indicated that the Baige landslide was gradually stable in the two years after the disaster. In addition, the monitoring results shew that the Xiaomojiu landslide in the 5km upstream of the Baige landslide is also active. The relevant results would like to provide a reference for the research in disaster prevention and reduction in this region.

Identification of geological potential landslides in Cang Mountain by combining SBAS-InSAR technique and information entropy

ZHU Zhifu, GAN Shu, ZHANG Jianming, YUAN Xiping, WANG Ruibo, ZHANG Xiaolun

2022, 0(11):  13-19.  doi:10.13474/j.cnki.11-2246.2022.0318

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In response to the problem of high hidden landslide hazards in southwest China, it is difficult to identify the problem comprehensively by traditional technology. This paper took Dali Cang Mountain as the research object and used SBAS-InSAR technique to identify landslide potential in Cang Mountain between January 2019 and ation between different slope grades and slope stability. Finally, based on the remote sensing images of typical potential landslide areas and the deformation time series maps of sampling points, the spatial and temporal evolution trends of slope stability and deformation inducing factors are discussed. The experimental results show that ① The deformation rate in the study area is -155.6 to 92.4mm/a during January 2019 to April 2021, and 13 unstable potential landslides exceeding -30mm/a are identified. ② The information entropy is greater than 0.8 when the grade of slope is Ⅳ,Ⅴ, the slope stability is weak and the uneven deformation is serious, which maintains high consistency with the existing literature conclusions, confirming the reliability of the model. ③ The deformation trend of typical potential landslide area shows obvious seasonal changes, and rainfall and snow and ice melt are the main factors leading to slope instability.

Landslide susceptibility evaluation considering sample sensitivity

Lü Beiru, PENG Ling, LI Qiaomin

2022, 0(11):  20-25.  doi:10.13474/j.cnki.11-2246.2022.0319

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As natural geological phenomena of involving great danger, landslides have seriously threatened people's lives and property. Therefore, it is very important to predict the susceptibility of landslide scientifically and accurately. With the development of machine learning, the prediction of landslide susceptibility based on machine learning has become a research hotspot. But in the real situation, the area ratio of non-landslide and landslide area is very large, which makes the application of machine learning model exist serious sample imbalance problem. In order to obtain the most balanced landslide sample set, the performance of multiple machine learning models on different proportion of positive and negative landslide sample set is analyzed. The multigraded cascade forest model is trained on this sample set and used to predict the landslide susceptibility in the study area. The final prediction results are close to the real distribution, which shows that the method presented in this paper is effective.

Mangrove forest species classification based on the UAV hyperspectral images

YI Lina, ZHANG Guifeng, WEI Zheng, WANG Mianqing, LIU Jinke, WANG Liujing

2022, 0(11):  26-31.  doi:10.13474/j.cnki.11-2246.2022.0320

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In recent years, mangrove forest community species losses and functional degradation have become more and more serious. In order to timely and accurately extract the spatial pattern and distribution information of mangrove forest, this paper first extracts the vegetation area based on the UAV hyperspectral image of Futian mangrove nature reserve in Shenzhen using the normalized difference vegetation index and intertidal mangrove index, and then selected the band combination using the best index method. The pixel-based support vector machine classification (SVM) and object-oriented image classification (OOC) methods are used to accurately identify mangrove species. The experimental results show that the overall accuracy of SVM classification and OOC methods are 81.03%, and 85.58% respectively. In conclusion, The OOC methods can effectively remove the salt and pepper noise, makes full use of the spectral, shape and texture information of the object, and provides more accurate mangrove distribution information.

SANet:real time semantic segmentation method of LiDAR point cloud based on spatial attention mechanism

WANG Weiqi, YOU Xiong, SU Mingzhan, ZHANG Lantian, ZHOU Xueying, ZHAO Yao

2022, 0(11):  32-38.  doi:10.13474/j.cnki.11-2246.2022.0321

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Semantic segmentation is an important basis for intelligent robots to move from perceptual intelligence to cognitive intelligence. The current semantic segmentation methods for point cloud data have poor real-time performance and low accuracy. In this article, we systematically analyze the difference between the range images generated by spherical projection of point cloud and common images, and provide ideas for the design of real-time semantic segmentation neural network. Through the analysis, we find that the range images have the characteristics of strong spatial correlation. This article combines the strong spatial correlation with attention mechanism, then proposes a real-time semantic segmentation method SANet based on spatial attention mechanism. SANet can efficiently aggregate spatial distribution features and context features. And the model parameters are less, which can meet the real-time requirements. Experiments on the SemanticKITTI dataset show that SANet has both good real-time performance and high accuracy compared with other excellent algorithms. The spatial attention mechanism proposed in this article significantly improves the accuracy of semantic segmentation of LiDAR point cloud by efficiently aggregating spatial distribution features and context features, which can provide auxiliary support for autonomous driving and other robot applications.

Multispectral image change detection based on spatial context and slow feature analysis

WANG Xiaowen, DAI Chenguang, ZHANG Zhenchao, JI Hongliang

2022, 0(11):  39-43.  doi:10.13474/j.cnki.11-2246.2022.0322

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To improve the accuracy of multispectral change detection, a method combining spatial context and slow feature analysis is proposed. First, an adaptive spatial context extraction algorithm is used to construct an adaptive region around the pixel to explore the context information around the pixel. Then through the iterative slow feature analysis, the change intensity between paired pixels is quantitatively calculated from the paired adaptive region around the corresponding pixel. The separability of the changed area and the unchanged area is enhanced. Finally, the change intensity image is generated, and the Otsu threshold method is used for binary classification, and the change intensity map is divided into binary change detection maps. Experiments use images from the Landsat 7 satellite TM sensor to compare with four algebra-based and transformation-based methods. The results demonstrate that the method in this paper performs better in terms of reducing omission errors and improving recall rate.

GNSS RTK adaptive reference station switching method

SONG Xiaodi, WANG Lei, LIN Gaoyu, HE Feiyang, GUO Jiming

2022, 0(11):  44-48,89.  doi:10.13474/j.cnki.11-2246.2022.0323

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In medium-long baseline GNSS kinematic relative positioning, the correlation of errors between the reference station and the rover station decreases with the increase of the baseline length. Consequently, the ambiguity parameters cannot be fixed instantaneously, which may decrease the precision of positioning. In multiple reference station scenarios, we can adaptively switch the reference station to a closer one to form a more rational baseline to guarantee the precision of RTK positioning. Aiming at solving the re-convergence of positioning results caused by reinitiating ambiguity after switching reference stations, a method of adaptively switching GNSS RTK reference stations in real time is proposed in this paper. By imposing the double-difference ambiguity between the two reference stations before and after switching, the precise prior information of double-difference ambiguity between the new reference station and rover station is derived, thus circumventing the ambiguity re-initialization after switching reference stations and maintaining the continuity of high-precision positioning results. The method described in this paper can be used in real-time positioning and can meet the demand for large-scale RTK high-precision continuous positioning. Numerical examples using data of Hong Kong CORS stations show that the proposed method can solve the re-convergence issue of positioning solutions after switching stations and continuous high-precision positioning results can be obtained after switching reference stations.

A method of 3D map inversion using smart phone GNSS signal-to-noise ratio

JIANG Xinwei, WANG Shitai, YANG Shini, YIN Min, ZHOU Guoqing, ZHANG Boyu, MA Yue

2022, 0(11):  49-56.  doi:10.13474/j.cnki.11-2246.2022.0324

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Based on the variation characteristics of smart phone GNSS signal-to-noise ratio around buildings, this paper analyzes its relationship with the occlusion of buildings to GNSS signals, and puts forward a probability subtraction inversion algorithm of two-dimensional probability map and a voxelized inverse algorithm of adjacent boundary points of building height, and then studies the inversion of three-dimensional map using a large number of observation data. The inversion accuracy is analyzed. The experimental results show that on the 5m grid map, taking the GNSS signal-to-noise ratio data of satellites with an altitude angle of more than 5°, the accuracy tends to be stable when reaching 9000 epoch. The comprehensive effect of building center coordinates, building area, corner position and building height retrieved at 12000 epoch is the best. The center position error is 1.16~1.74m, the area error is 1.12%~2.39%, and the absolute mean value of corner error is 5.00~5.30m, the root mean square error is 5.82m and the building height error is 0.04~2.1m. The goal of 3D map inversion using GNSS signal-to-noise ratio data of intelligent mobile terminal is basically realized.

Spatio-temporal monitoring of black soil land degraded grassland by remote sensing

LIU Yunfeng, QIN Kun, Lü Huiling, CHEN Siyu

2022, 0(11):  57-61.  doi:10.13474/j.cnki.11-2246.2022.0325

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Accurate and timely monitoring the spatio-distribution characteristics of black soil land degraded grassland is of great significance to the restoration and management of grassland degradation in Qilian Mountains. Based on Landsat 8 OLI images and threshold method, we try to extract the scope of black soil land degraded grassland, and analyse spatio-temporal variation from 2014 to 2019 in northwestern part of Yeniugou township, Qilian county. The results show that the scheme has a certain reliability. During 2014 and 2019, the black soil land degraded grassland has improving trend in northern gentle slope part and central flat parts, and worse trend in western part and northwestern gentle slope part. The improving grassland depends on human intervention, and the deterioration grassland may be affected by many factors, such as water heat hole effects, rodent damage and so on.

Dynamic cloud detection based on multi-scale retinal image enhancement

CHEN Farong, FANG Songsong

2022, 0(11):  62-66,143.  doi:10.13474/j.cnki.11-2246.2022.0326

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Cloud detection is the basis of various quantitative remote sensing products of meteorological satellites. Whether it is weather analysis based on cloud images, inversion of various atmospheric and surface parameters, sand, dust, fire and other disaster detection based on cloud removal, accurate cloud detection in images, especially details such as thin clouds and cloud edges is required. Aiming at the refined cloud detection of geostationary satellites, this paper proposes a dynamic cloud detection method based on multi-scale retinal image enhancement. The clear sky radiation background field is applied to enhance and extract the cloud detail information of the radiation difference through the multi-scale image enhancement and the maximum inter-class difference method. This paper uses 75 MODIS cloud detection products from 2021 to 2022 as the verification data to verify the algorithm accuracy. The overall algorithm accuracy reaches 91.13%, the recall rate is 94.02%, and the precision rate is 86.71%. Overall, the algorithm has strong applicability and robustness. It is excellent and has well supported the commercial application of quantitative remote sensing products in the past two years.

Analysis of spatio-temporal characteristics of land subsidence on Beijing Metro Line 15 based on entropy and transition matrix

TIAN Xiuxiu, WANG Yanbing, LI Chenxia, LI Xiaojuan, ZHU Lin

2022, 0(11):  67-73.  doi:10.13474/j.cnki.11-2246.2022.0327

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The land subsidence information of Metro Line 15 is obtained based on PS-InSAR. The entropy value of the study area from 2003 to 2019 is calculated by information theory. The transformation law of land subsidence and its relationship with the change of entropy value are analyzed through the transition matrix. It is found that from 2003 to 2020, the differential subsidence of the study area is obviously affected by the geological structure, the average annual land subsidence rate is between [-100.17, 1.19] mm/a. Before 2016, the information entropy continued to increase, and the differences in land subsidence are large. After that, the information entropy gradually decreased, and the subsidence consistency is good. The value of entropy is related to the development of land subsidence, it is higher in the serious subsidence area and lower in the stable subsidence area. Entropy value increases, the subsidence type has a high transfer out rate, and the land subsidence system is unstable. Otherwise, entropy value decreases, the transfer out rate of each subsidence type is low and the subsidence system is relatively stable.

Detection of typical geographic object in maps based on deep learning

WANG Zheng, FU Xiao, DU Kaixuan, LIU Jiping, CHE Xianghong

2022, 0(11):  74-78.  doi:10.13474/j.cnki.11-2246.2022.0328

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Aiming at the problem of typical geographic target recognition in maps, this paper introduces two object detection methods based on deep learning: YOLO and RetinaNet which replaces cross entropy loss function with focal loss. Images are input into two neural network models for training and testing, and object detection results are compared and analyzed. The results show that the RetinaNet model has significantly improved the accuracy of object detection on maps, and the running speed is still up to seconds. The high accuracy and efficiency of the geographic object detection method can save a lot of manpower and time costs during map review, providing a new technical reference for intelligent understanding of map content and Internet map supervision.

Analysis of urban expansion characteristics and driving force analysis of Taiyuan city based on night light images

ZHANG Na, ZHANG Huixia, LI Aiqin

2022, 0(11):  79-83,105.  doi:10.13474/j.cnki.11-2246.2022.0329

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With the advancement of urbanization, the scope of urban built-up areas continues to expand, and many problems have emerged in this process. In order to better understand the law of urban development, DMSP/OLS data in five periods of 1992, 1997, 2002, 2007 and 2012 and NPP-VIIRS night light images as data sources in two periods of 2017 and 2019 are selected as data sources, and the scope of Taiyuan built-up areas is extracted by statistical data comparison method. Through the analysis of the temporal and spatial characteristics of the built-up area of Taiyuan, the law of urban expansion is obtained. The results show that: ① from 1992 to 2019, the area of Taiyuan built-up area increased by 249.73km², expanded by 2.6 times, and the growth of built-up area was mainly concentrated in the southeast of Taiyuan.② 2002-2012 and 2017-2019 belonged to the accelerated expansion mode, and the expansion speed was high. From 1992 to 2019, the shift distance of Taiyuan center of gravity was 5676.42m, the average migration speed was 202.73m/a, and the center of gravity generally shifted to the southeast. ③ The driving force of Taiyuan urban expansion mainly comes from the influence of economic development factors, population factors, transportation factors and policy planning factors. The research results provid theoretical basis and data support for Taiyuan urban planning and spatial structure adjustment.

Comparison and analysis of AW3D30 DEM data void repair methods under different geomorphic conditions

ZHOU Xiaoyu, ZHAO Shangmin

2022, 0(11):  84-89.  doi:10.13474/j.cnki.11-2246.2022.0330

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DEM data is widely used in many fields, but its applicability is severely restricted by the data void in production process. Therefore, it is crucial that the research on DEM data void repair. In this paper, the experimental areas of river valleys, basins, hills and mountains under four different geomorphic conditions in Taiyuan city are selected as void areas. ASTER GDEM data and direct mosaic method, inverse distance weighted interpolation method and delta surface filled method are used to reconstruct AW3D30 DEM data, and the restoration effects of different methods are compared and analyzed. The results show that: In the region of the basin, inverse distance weighted interpolation method has the best repair effect, followed by the delta surface filled method, and the direct mosaic method is weakest. However, in the valley, hill and mountain region with larger fluctuation, the delta surface filled method has better effect, and the texture features in the cavity region are obvious, and the cavity edge region is smooth, while the inverse distance weighted interpolation method is the weakest.

DEM fusion based on NASA DEM and AW3D30 DEM in Taiyuan

LIU Jiao, ZHAO Shangmin

2022, 0(11):  90-95.  doi:10.13474/j.cnki.11-2246.2022.0331

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In this paper, taking DEM data as an example, the input data and the reference data are firstly aligned to the same pixel position, then the root mean square error and standard deviation are taken as reference indicators, and the best weighting fusion coefficients are explored by the traversal process of weighting coefficients from 0 to 1 in the regions of different slope classes. To determine the fusion scheme and perform the fusion of NASA DEM and AW3D30 DEM, and finally evaluate the fusion effect quantitatively. The results show that before the alignment, the displacements of NASA DEM along x, y, and z directions are -2.65, 2.41, and 0.60m, and the displacements of AW3D30 DEM are 1.04, 7.51, and -3.33m; after the alignment, all the errors of the original data are reduced, and the systematic errors of NASA DEM disappear. Compared with the NASA DEM, the ME and RMSE of the fused DEM are reduced by 25.0% and 36.8%; for the AW3D30 DEM, the error reduction is 86.5%, and 13.2%.

The determination method of flood inundation range based on the coherence of Sentinel data

WU Yanru, LIAN Xugang, GAO Yurong

2022, 0(11):  96-100.  doi:10.13474/j.cnki.11-2246.2022.0332

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Flood disaster can cause farmland inundation, residential damage and other hazards. When the optical sensor extracts the flooded area, it can't penetrate the clouds, so it can't get effective ground information. SAR uses microwave band, which is not affected by weather conditions and can be imaged at night. Therefore, SAR has become a powerful tool for flood disaster assessment. This paper uses Sentinel-1A data of three SAR radar images on September 23, October 5 and October 17, 2021 to calculate the coherence coefficient. The threshold value is set to 0.2 to extract the water inundation range, and the expansion range and change trend are analyzed. According to the generated deformation map, the change of water level rise is analyzed. It is confirmed that the coherence coefficient threshold extraction method based on radar data is feasible in monitoring the flood inundation range. It is verified that InSAR technology can accurately extract water boundary and analyze water level rising trend.

Risk assessment of geological disaster based on information value and AHP model in mining area of Yangquan city

GUO Jia, ZHAO Zhixing, LIU Zhiqi, LI Jindong, PAN Wei, WANG Wenzhou

2022, 0(11):  101-105.  doi:10.13474/j.cnki.11-2246.2022.0333

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There are hidden dangers of geological disasters such as collapes and landslide in mining area of Yangquan city because of complex geological environment and strong hunman activity. In this paper, the risk assessment system is constructed in mining area based on the full investigation of geological disasters. Selects eight indexs such as traffic, residential, mining to carry out susceptibility zoning using the method of information value and analytic hierarchy process. On the basic of susceptibility assessment, rainfall factors are super imposed to realize the hazard assessment. Selects population, building and traffic factors to carry out vulnerability model. Based on the outcome of hazard assessment and vulnerability assessment, it establishes risk assessment modes. The research shows that medium-high risk areas are mainly distributed in the streets of Saiyu and Caiwa where there are mining activities and close to the population gathering, and the impact range is large. It is urgent to take measure to monitor and warn.

High-precision modeling of complex terrain in mining areas based on spatial variability modified ordinary Kriging method

YU Guangting, LIU Tongwen, WANG Qi, PAN Mao, LI Tao, SONG Guanhan, LIU Shanwei

2022, 0(11):  106-111.  doi:10.13474/j.cnki.11-2246.2022.0334

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The ordinary Kriging method is an effective method to construct a three-dimensional terrain model of the mining areas and reveal the dynamic changes of the surface subsidence deformation field. However, the ordinary Kriging method presents the problem of the smoothing effect, which causes the underestimation of spatial variability and fails to truly reflect the complex surface morphological characteristics of the mining areas. In this paper, a OK-SVM (spatial variability modified ordinary Kriging) method is adopted for the application experiment of high-precision modeling of the complex terrain based on the real sampling data in a mining area, and a comparative analysis is made with the existing methods in terms of modeling accuracy and spatial variability reproduction. The results show that this method can reduce the influence of the smoothing effect on modeling and provides higher modeling accuracy and spatial variability reproduction ability, which has strong applicability in the application of high-precision modeling of complex terrain in mining areas. It can be used as a reliable modeling tool to analyze the dynamic variation pattern of complex surface subsidence deformation fields in mining areas.

Evaluation of geological hazard susceptibility based on certainty factors coupling logistic regression

WANG Xuan, SHI Yun, CHEN Hao

2022, 0(11):  112-117.  doi:10.13474/j.cnki.11-2246.2022.0335

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In order to study the susceptibility of geological disasters in the Northwest region, where natural disasters frequently occur, we consider ten factors, such as elevation and slope aspect, and use the coefficient of certainty (CF) model and the coupled logistic regression (CF-LR) model to evaluate the susceptibility of geological hazards in Chenggu county. The results show that the disaster ratios of the CF model and the CF-LR model are increasing, and the density of high-extremely high disaster points are 4.75/km²and 5.97/km² respectively. In addition, in the test data set, the area under curve (AUC) of the receiver operating characteristic (ROC) of the two models are 0.812 and 0.835 respectively. In the validation dataset, the AUC of the ROC of the two models are 0.862 and 0.891 respectively. Both models can effectively evaluate the susceptibility of geological disasters in the region, and the CF-LR model has higher evaluation accuracy.

Multi-source building disaster information fusion based on spatial and semantic matching

NI Huizhu, WAN Shuhai, SI Han, FENG Siyuan, REN Xiaolei, LI Zhengqiang, LU Tao

2022, 0(11):  118-122.  doi:10.13474/j.cnki.11-2246.2022.0336

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In the national survey on natural disaster risks, there are many sources of house disaster information data, which brings great challenges to the rapid construction of the investigation base database. In order to extract and fuse multi-source house data quickly, this paper realizes the rapid and automatic fusion and reliability evaluation of multi-source house information through the operations of basic data preprocessing, spatial data extraction and automatic fusion of attribute information by using technologies such as information matching based on geospatial location and information matching based on geospatial semantics. On this basis, the natural disaster census database building system is developed to provide reliable and detailed housing construction data for natural disaster census. Practice had proved that the platform results were accurate and reliable, which could effectively improve the efficiency of natural disaster risk survey and greatly reduce labor costs.

An automatic extraction method of image control points from CORS high-precision data

LIANG Lifang, WANG Yanyun, TIAN Shiyu, ZHANG Hengcai

2022, 0(11):  123-127.  doi:10.13474/j.cnki.11-2246.2022.0337

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More and more high-precision location points haven been generated by the CORS stations, continuously. How to automatic extract image control points from these high-precision datasets become a huge challenge. It has important value for substituting traditional time-consuming and labor-intensive manual operation or measurement. In this paper, we develop an automatic extraction method of image control points form CORS high-precision data. First, it adopts Douglas-Pucker algorithm to simplify trajectory. Second, ST-DBSCAN is conducted to identify the cluster center. Then, an improved rasterization method is proposed to optimize the candidate of image control points. Finally, we develop an automatic extraction tool based on ArcPy to be deployed in production environment. The experimental results show that our proposed method greatly reduce the workload with the accuracy of 94%, and has a wide field of application with good prospects.

Fusion monitoring technology of UAV inclination photography and LiDAR

HOU Fangguo, LIU Xin, REN Xiubo

2022, 0(11):  128-131.  doi:10.13474/j.cnki.11-2246.2022.0338

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Based on the ecological restoration project of the ecological zone around Chengdu city, the fusion monitoring technology of inclination photography and LiDAR technology is realized by using the Feima D200 UAV. Through 3D model making, large-scale topographic map production, point cloud processing, grid computing, precision evaluation and other steps, it is verified that the method of inclination photography and airborne LiDAR can meet the accuracy of 1∶500 topographic map and grid measurement, and it provides a guidance for the later UAV surveying and mapping.

BIM construction and application of urban underground pipe network

WANG Kai, LIU Pengfei

2022, 0(11):  132-134.  doi:10.13474/j.cnki.11-2246.2022.0339

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With the in-depth application of surveying and mapping geographic information technology and BIM technology in urban development,the construction of urban underground pipe network BIM has become a necessary link in the construction of smart city and three-dimensional real scene in China.Combined with the application of new basic surveying and mapping in underground space surveying and mapping,this paper puts forward the deep integration technology of underground pipe network surveying and mapping data and BIM,quickly constructs the technical process and system of urban underground pipe network BIM,constructs the refined BIM model under the urban level (GIS) scene,realizes the seamless integration of surveying and mapping data and design data,and opens up the integration channel with surveying and mapping data in multi-disciplinary cooperation,Provide accurate three-dimensional spatial data base for invisible underground city construction.Based on the research results of this paper,taking a city as an application case,its data have been deeply applied in the fields of urban drainage network reconstruction project,smart water cloud platform construction,smart pipe gallery construction management and so on,which verifies the feasibility,effectiveness and application value of this research.

Application of UAV aerial photography in earthwork survey in industrial park

PENG Jintao, ZHAO Jian, XING Tingsong

2022, 0(11):  135-137.  doi:10.13474/j.cnki.11-2246.2022.0340

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In recent years, low altitude unmanned aerial vehicle(UAV) has been widely used in the field of surveying and mapping, Accurate and rapid acquisition of earthwork volume is of great significance to engineering construction. This paper mainly introduces the method of earthwork volume calculation by UAV aerial photography collecting three-dimensional point cloud data mapping. Taking the earthwork measurement during the construction of Shenjiang Industrial Park as an example, the research shows that UAV aerial mapping has obvious advantages over traditional total station and GPS mapping. The case results show that compared with the traditional UAV aerial photography method, the manual workload and labor intensity are greatly reduced. At the same time, when the accuracy index is almost the same as that of the traditional method, the amount of data per unit area is far greater than that of the latter, and the work efficiency is greatly improved.

Analysis of land subsidence variation characteristics under different means and scales:a case study of Shenzhen Dakonggang District

XIE Wenjun

2022, 0(11):  138-143.  doi:10.13474/j.cnki.11-2246.2022.0341

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In this paper, the spatio-temporal variation characteristics of land subsidence in urban reclamation areas are analyzed by using different means and different scale ground monitoring methods. Through the analysis of the land subsidence monitoring project in Shenzhen Dakonggang District, combined with precise leveling and remote sensing monitoring methods, the land subsidence monitoring at different scales is realized, and the spatio-temporal variation characteristics of land subsidence in this area are obtained. The research results show that both precision leveling method and remote sensing monitoring method have found that the settlement caused by the roads around the Convention and Exhibition Center has the same change characteristics. The precise leveling monitoring method can accurately obtain the local ground settlement, and the maximum ground settlement around the building foundation pit of Shiwei road is -303.6mm. Combined with different means and different scale monitoring methods, the deformation characteristics of the monitoring object can be obtained comprehensively.

Spatial information service of railway line 3D scene based on Cesium technology

GUO Ze, TAN Qulin, QIN Xiaochun, HE Jia, HU Jiping

2022, 0(11):  144-148.  doi:10.13474/j.cnki.11-2246.2022.0342

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With the continuous advancement of China's railway information construction,the application of 3D GIS and network GIS in the railway field is gradually deepening. Aiming at the 3D scene spatial information service of railway lines,this paper proposes a 3D scene construction and network application method for railway lines based on the 3D open source engine Cesium.The Cesium architecture and network services,the construction of the 3D geographic environment of the line,and the construction of the 3D model of the engineering components of the line and public works infrastructure have been studied. In order to integrate the spatial geographic environment information of the railway line with the railway infrastructure model in the Cesium 3D engine,the lightweight research of the BIM model under the forward design of the railway infrastructure is carried out. It has realized Cesium-based networked,cross-platform,and distributed three-dimensional spatial information and 3D scene roaming of railway lines,data sharing and functional services.

Spatio-temporal patterns of carbon emissions in Hubei province based on county level

ZHOU Xuande, DOU Wenzhang, ZHAN Qingming, Zibibula·Simayi, DENG Zutao, ZENG Yong

2022, 0(11):  149-156,161.  doi:10.13474/j.cnki.11-2246.2022.0343

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Identifying the regional heterogeneity of carbon emissions is crucial for formulating effective carbon emission reduction policies. This paper uses the linear regression model, the coefficient of variation method, the Hurst index and the spatial autocorrelation analysis method to study the evolution characteristics of the spatial pattern of carbon emissions in Hubei Province. The results show that from 1997 to 2017, the carbon emission in Hubei province showed a significant upward trend of fluctuation, with an average annual growth rate of 4.74%; there were significant regional differences in the variability of carbon emission changes in the counties, and the overall presentation is “low-to-medium fluctuations, mostly high fluctuations”. The long-term correlation characteristics of carbon emission changes in the counties are obvious, and the overall characteristics are mainly moderate and strong persistence characteristics, accounting for 70%, and the distribution is relatively wide, among which the strong persistence areas are mainly concentrated in Wuhan; The spatial distribution of carbon emissions in the county area has a significant aggregation effect, showing a circle pattern with Wuhan as the core radiating continuously to the surrounding area.

Application of 3D real scene in route selection planning of power transmission and transformation project

ZHANG Yingdong, QIAO Xin, ZHOU Shengchuan

2022, 0(11):  157-161.  doi:10.13474/j.cnki.11-2246.2022.0344

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There are many restrictive factors in the route selection of power transmission and transformation projects, which are obviously affected by the environment. The traditional 2D map selection combined with on-site survey work is not only time-consuming and labor-intensive, but also cannot fully grasp the natural conditions on the route, making it difficult to guarantee the selection effect. This paper studies the route selection planning of power transmission and transformation projects using 3D real scene technology. It provides a new idea for scientific and rational route selection by carrying out selection range constraints, line plotting and simulation in real geographic scenes, combined with spatial analysis technology to assist in the comparison of planning scheme. During the construction of Huangbuling 500kV project, practices show that the 3D real scene with its real, three-dimensional and intuitive expression advantages can not only improve the efficiency and quality of route selection, but also possible to carry out landscape visual impact analysis on special route such as crossing scenic spots to provide scientific and objective decision-making reference for scheme comparison and demonstration, which is an in-depth empowerment for digital transmission route selection.

Talent training path for surveying and mapping geographic information under the background of high-end industrial development

BAI Huayan, CHEN Yueming

2022, 0(11):  162-165.  doi:10.13474/j.cnki.11-2246.2022.0345

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Under the background of the high-end development of surveying and mapping geographic information industry, how to cultivate skilled talents in higher vocational colleges has become the focus of current research. Through investigations, it is found that enterprises pay more attention to geographic information system(GIS) technology and application (87.5%), operating unmanned aerial vehicle(UAV) information acquisition and processing (84.7%), surveying and mapping instruments use and maintenance(79.2%) skills, and students generally lack GIS software operation and application(68.1%), surveying and mapping instruments use and maintenance(65.3%), operating UAV information acquisition and processing(56.9%). This paper proposes a surveying and mapping geographic information talent training model that integrates “post-course-competition-certificate”, integrates corporate job tasks, vocational certification and skills competition requirements into the curriculum, so that students have the skills that meet the needs of future vocational positions, and adapt to the high-end development of surveying and mapping geographic information industry.

Analysis of logic and optimization path of resource and security professional group

HUANG Huaming, WANG Dan

2022, 0(11):  166-170.  doi:10.13474/j.cnki.11-2246.2022.0346

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The categories of resources, environment and safety directly serve the production of primary products, ecological environment protection and many other fields, and the status of basic guarantee is prominent. Through the statistical analysis of “double high” data, it is found that: ①The cohesion of the major categories is not strong, and the proportion of exogenous type group is as high as 63%. ② Surveying, mapping, geographic information and environmental protection majors play an outstanding role in outreach, which is manifested in the prominent position of key majors of engineering surveying technology and environmental engineering technology.③ Group logic is mainly chain and embedded type, which is manifested in the chain connection between mining majors and biology and chemical industry, energy and power and materials, and the embedded connection between surveying and mapping geographic information majors and transportation, civil engineering and construction. In order to further meet the needs of collaborative governance of resources and environment and the construction of a unified market, a group path aiming at the internal connection of asset and environment categories is constructed, including two schemes: chain group based on the information flow of the earth system and embedded group based on environmental protection and safety technology support mode.

High-precision map production technology and 3D visual expression based on multi-source data

LUO Guangfei, LIU Yunbo, WANG Zhi, LIAO Yinqi, ZHAO Ping, SUN Na, LU Wangda

2022, 0(11):  171-174.  doi:10.13474/j.cnki.11-2246.2022.0347

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With the mass production and gradual popularity of self-driving cars, the demand for high-precision maps is also increasing. Cars can realize the accurate perception of the driving environment through the high-precision map, so as to realize the safety and reliability of driving. The method of extracting the vector line drawing of high-precision map from multi-source heterogeneous data such as tilt model and vehicle mobile scanning point cloud is proposed, and analysing the different source data on the accuracy of data extraction, and discussing the spatial expression, attribute stratification and association rules of the high-precision map data model. We study the implementation of 3D visualization of high precision map, and propose feasible technical methods to provide a reference value for the production of high precision map.