Table of Content

25 December 2021, Volume 0 Issue 12

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Ground point extraction and DEM generation of traditional village landing surface points based on dense matching point cloud of UAV image: taking Dehang village in western Hunan as an example

FU Xiangxiang, DENG Yunyuan, ZHENG Wenwu, ZHOU Shaoning, ZHOU Jialu

2021, 0(12):  1-5.  doi:10.13474/j.cnki.11-2246.2021.362

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For the problems of using UAV technology to obtain ground points and DEM in mountainous area with large fluctuation and dense vegetation, a method combining cloth simulation filtering algorithm and improved local maximum algorithm is proposed.This method uses vegetation information such as tree vertices and tree heights to extract ground points, and then generates DEM for the entire area.In this paper, Dehang village, a traditional village, is taken as an example. The point cloud is divided into two parts:dense vegetation area and non-dense vegetation area by vegetation coefficient and elevation information.In non-dense vegetation area, the cloth simulation filtering algorithm and improved local maximum algorithm are used to extract ground points,tree vertices and calculate the average tree height; in dense vegetation area, the approximate ground point of the dense vegetation area is calculated from the vertex of the tree in the area, and finally perform TIN interpolation on the two parts of the ground point cloud to get the DEM of the area. The experimental results show that the root mean square error of DEM generated by this method can reach 0.037 m in non-dense vegetation areas, 1.606 m in dense vegetation areas, and the overall average error can reach 1.492 m. The overall accuracy is good, which can basically meet the needs of spatial analysis at the village scale.

Analysis of land use change in Xiong'an New Area from 2016 to 2019 based on the Sentinel-2 images

YU Miao, MA Hongbing, WANG Hongwei

2021, 0(12):  6-9,32.  doi:10.13474/j.cnki.11-2246.2021.363

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The Xiong'an New Area is another strategically important new area established at the national level. It is of great significance to grasp the details of land use in this area. In this study, the 10 m Sentinel-2 images were used to classify the land use from 2016 to 2019, and the spatio-temporal land use changes were then analyzed. This study first tested three popular classifiers including decision tree, random forest, and support vector machine to obtain the highest-accuracy land use map. Meanwhile, the importance of different features was analyzed. The results showed that in Xiong'an New Area, the land use types and areas have undergone significant changes. Among them, the area of arable land, woodland, and aquatic plants all showed a significant reduction trend, and the area of construction land has increased a lot, indicating that the Xiong'an New Area was undergoing rapid urbanization. The 10 m land use maps obtained in this study have important reference significance for the timely monitoring and planning of Xiong'an New Area.

Evolution of urban spatial pattern of GBA based on DMSP-OLS and LJ-1 nighttime light remote sensing images

HUANG Tielan, LUO Jing, GAO Zhaozhong, HUANG Feini

2021, 0(12):  10-15.  doi:10.13474/j.cnki.11-2246.2021.364

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Nighttime light remote sensing images can be effectively used to extract evolution of urban spatial pattern. In this paper, the DSMP-OLS nighttime light (NTL) images from 1992 to 2012 and the LJ-1 NTL images in 2018 are used to extract urban built-up areas of Guangdong-Hong Kong-Macao greater bay area (GBA) by applying dynamic threshold method. On this basis, in order to reveal the spatial pattern and urban expansion process of each city in GBA, a number of indicators are used, including average light brightness, growth rate of average light brightness, urban built-up area, growth rate of urban built-up area, urban center of gravity coordinates, and offset distance of urban center of gravity. Finally, we analyze the main driving factors of urban expansion in GBA combined with the national economic statistics. The results show that:① From 1992 to 2018, the urban scale of GBA increased significantly. It forms an inverted "U" shaped urban agglomeration, with Guangzhou, Shenzhen and Hong Kong as the center, expanding outward in a radial manner. ② Taking the Pearl River Estuary as the boundary, the development level of eastern cities is significantly higher than that of western cities. The development level of core cities such as Guangzhou, Shenzhen and Hong Kong were significantly higher than that of peripheral cities such as Jiangmen, Zhaoqing and Huizhou. ③ From 1992 to 2018, the expansion speed of the built-up area in GBA increases from small to large, and then decreased gradually. 2002-2007 was the fastest period of urban expansion. ④ From 1992 to 2018, there were three types of urban center of gravity migration:the center of gravity of periphery cities continued to move to the center of GBA, the center of gravity of central cities moved to the junction of neighboring cities, the center of gravity of special administrative cities is moving towards the ocean. Most cities have "vibration" in their directions of urban gravity movement.

Deep learning classification of airborne multispectral LiDAR data using sample generation method

ZHAO Peiran, GUAN Haiyan, LI Dilong, JING Zhuangwei, YU Yongtao

2021, 0(12):  16-21.  doi:10.13474/j.cnki.11-2246.2021.365

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An airborne multispectral LiDAR system, which can quickly and accurately obtain the spatial geometry and spectral information of ground objects, provides a new data source for ground coverage classification and target recognition. In recent years, a series of breakthroughs have been achieved in deep learning algorithms based on 3D point cloud. However, it is difficult to directly input irregular original point cloud data into deep learning models for point-based classification. In this paper, a sample generation method based on PFS-KNN is proposed for deep learning based classification models using airborne multispectral LiDAR data. The method first normalizes the input data, and then farthest point sampling method and k-nearest neighbor method are used to generate a series of training sample data sets with regular size from the input data. Experiments with the airborne multi-spectral LiDAR data show that the samples generated by the proposed method not only meet the input data format required by the convolutional neural network, but also ensure the complete coverage of the input scene.

Perceptual Hash integrity authentication algorithm for high-resolution remote sensing image using ULBP

LIU Mingxuan, ZHANG Liming, WANG Hao, MA Wenjun, LI Yu

2021, 0(12):  22-27.  doi:10.13474/j.cnki.11-2246.2021.366

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Aiming at the problem that feature extraction accuracy and algorithm robustness cannot be taken into account in the existing high-resolution remote sensing image perception Hash authentication algorithms, this paper proposes a high-resolution remote sensing image perception Hash integrity authentication algorithm using ULBP. Firstly, the remote sensing image was divided into grids, and the image is divided into multiple sub-blocks. ULBP algorithm is used to extract the texture features of sub-blocks. Then, the histogram distribution of texture feature in each sub-block is calculated and the perceived hash sequence of sub-block is obtained after binarization of the result and the mean value. Finally, the perceptive Hash sequence of all sub-blocks is concatenated to generate the perceptive hash value of the whole image. In image authentication, the Hash sequence of the original image and the image to be detected is first calculated, and then the average hamming distance of the perceived Hash sequence of the two is calculated, so as to complete the integrity authentication and tamper location of the high-resolution image content. Experiments show that the algorithm can identify the relatively smooth areas of ground objects in high-resolution remote sensing images, and has good robustness for the maintenance of contents such as JPEG compression, Gaussian noise and BMP format conversion, thus providing support for the integrity authentication of high-resolution remote sensing images.

Application of machine learning algorithms in estimation of above-ground biomass of forest

ZHANG Peng, MA Qingxun, Lü Jie, JI Jinliang, LI Ziwei

2021, 0(12):  28-32.  doi:10.13474/j.cnki.11-2246.2021.367

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Above-ground biomass of forests is an important evaluation index of forest productivity, and efficient monitoring of it is of great significance to maintaining global carbon balance and protecting ecosystems. The research is based on the canopy height model data, obtained the single tree canopy width boundary through the watershed segmentation algorithm, and then extracted a total of 23 LiDAR variables within the single tree canopy range,combined with 87 sets of measured data from the Penobscot experimental forest, random forest (RF) and support vector machine (SVM) are used to establish forest above-ground biomass estimation model, and the estimation results of the sample plot models are compared, and the prediction results and their accuracy are discussed. The results show that the random forest model and support vector machine model selected in this study have achieved high accuracy in estimating the above-ground biomass of forests. The random forest model has higher estimation accuracy in estimating forest above-ground biomass based on airborne radar data, stronger model generalization ability, better mapping accuracy, and better suitability.

Fusion method of UAV real-time video and 3D geographical scene

WANG Lei, ZHOU Xinxin, WU Changbin

2021, 0(12):  33-37,43.  doi:10.13474/j.cnki.11-2246.2021.368

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Aiming at the problem of the inability to obtain the spatial relationship between video elements and geographic elements of surrounding scenes when UAV video patrols, this paper proposes a method of fusion of UAV real-time video and 3D geographic scenes. This method obtains real-time UAV patrol videos by setting route stations, constructs 3D geographic scenes using high-resolution oblique photography models, projects the videos in 3D geographic scenes, and constructs video projection parameter standards and UAV data transmission models. Realize the fusion display of UAV real-time video and 3D geographic scenes. Design the application process of UAV real-scene fusion, and carry out experimental verification through specific cases. The experimental results show that the real-scene fusion of the UAV has a good expression effect, the video and the 3D geographic scene have a high degree fusion, and the video picture distortion is small. This method extends the UAV video application to 3D space, and gives a spatial reference to the video elements.

GPS-InSAR data fusion method with robust vertical variance component estimation for 3D deformation field

WU Xueyu, LI Mingfeng, DONG Sixue, WANG bin, ZHAO Zhisheng

2021, 0(12):  38-43.  doi:10.13474/j.cnki.11-2246.2021.369

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It is easily affected for the three-dimensional deformation field model of GPS-InSAR data fusion by the gross error of the observation value. The weighting method based on the Helmert variance component estimation cannot be used to resist gross errors and the calculation efficiency is low. In view of this, a method based on the GPS-InSAR fusion solution model for robust vertical variance component estimation is proposed. The variance component estimation method and the robust estimation theory are used to calculate the 3D deformation field effectively by optimizing the classification of the observed values and carrying out the weight selection iteration to allocate the weight accurately. Experimental results show that it is effectively resisted the influence of gross errors in observations by this way. The accuracy of 3D deformation field inversion and the efficiency of 3D deformation field calculated point by point is effectively improved.

RTK+PDR fusion positioning for smart phone in complex environment

XU Guoliang, LI Zhen, TAO Jun, GUO Jing, ZHAO Qile

2021, 0(12):  44-49,98.  doi:10.13474/j.cnki.11-2246.2021.370

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For the problem of low positioning accuracy and insufficient anti-jamming capability of smart phones in complex outdoor environments, real time kinematic (RTK) and pedestrian dead reckoning (PDR) algorithms are integrated to position based on raw GNSS observations and built-in IMU data from smart phone in this paper. And the GNSS data from Xiaomi8 and Huawei Mate20X mobile phone are compared and analyzed. The positioning accuracy and stability with the proposed methods are assessed under different observation conditions. The experiment results show that the RTK algorithm can reach a positioning accuracy of 1.8 m and 4.6 m in good and complex observation environment respactively, and the RTK+PDR fusion algorithm can reach a positioning accuracy of 1.2 m and 2.6 m respectively. This positioning accuracy are 50% and 76% higher than that of RTK algorithm. The positioning accuracy and stability of smart phones is improved significantly in complex outdoor environments.

Research on position interpolation of BDS-3 satellite

WANG Jianmin, LI Te

2021, 0(12):  50-53.  doi:10.13474/j.cnki.11-2246.2021.371

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In view of the problem that BeiDou precise ephemeris can only provide discrete three-dimensional coordinates and can not provide satellite position at any time, this paper proposes to use interpolation method to calculate the satellite position at any time, which includes Lagrange interpolation method, polynomial fitting method, piecewise linear interpolation method and radial basis function fitting method to interpolate the precise ephemeris of BDS-3 satellite. The experimental results show that, Lagrange interpolation method and polynomial fitting method can well interpolate the position coordinates of BDS-3. The X-direction position of the satellite carrying CZ-3A launch vehicle and the z-direction position of the satellite carrying the CZ-3C launch vehicle are solved by Lagrange interpolation method, and the other position directions are solved by polynomial fitting method.

Design of city characteristic electronic map: a case of Nanjing city

WENG Min, DOU Xiaoyue, YIN Xiangjun, DU Qingyun, SU Shiliang, KANG Mengjun, YU Bin

2021, 0(12):  54-59.  doi:10.13474/j.cnki.11-2246.2021.372

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In recent years, electronic maps have played an increasingly important role in people's daily life and tourism. As a new type of electronic map, the city characteristic electronic map is an important medium for the public to obtain urban geospatial information, understand and recognize the city, and is also an effective tool for publicizing and promoting the city. It can effectively highlight the urban structure and urban culture. However, the current research on city electronic maps is mainly focused on technology development and function realization, and there are few explorations on its visual design and artistic performance, and it is difficult to highlight the characteristics of the city. Based on theories of urban space cognition, map visual perception, color geography, etc., this research explores the design method of urban characteristic electronic map from the perspective of visual expression, and on this basis, combines the practical case of Nanjing city characteristic electronic map design. The specific methods and processes of grading content selection, symbol design and color design are explained, aiming to provide a reference for the design of city characteristic electronic maps.

Analysis on the spatial characteristics and influencing factors of Wuhan commercial center

MA Zhiyong, CHANG Yinghui, SUN Lijian, WANG Taotao

2021, 0(12):  60-65.  doi:10.13474/j.cnki.11-2246.2021.373

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Taking the main urban area of Wuhan as a case, this paper identifies the sphere of influence and hinterland of the commercial center based on the residents' travel OD data of mobile phone signaling, analyzes the spatial characteristics of the commercial center of the study area, constructs the index system that affects the scale of the hinterland, and calculates the comprehensive level of each commercial center by weighting the influence factors by entropy method. The conclusions are as follows:①Wuhan's commercial centers are characterized by multi-core distribution pattern, and the summarize sphere of influence is mainly distributed along the subway, and the Yangtze River plays a clear separation effect on them.②POI diversity has a great correlation with the scale of the commercial center hinterland (0.879 8), and the attractiveness of the commercial center depends more on its service level and traffic development degree than others.③As district-level commercial centers, Hanjie and Jiedaokou are still the first choice for consumption and recreation of nearby residents for their location and convenient transportation.

A method to improve the spatial accuracy of population grided data based on land use

GUO Zihan, CHEN Fei, LIU Xiaoli, DAI Zhaoxin

2021, 0(12):  66-70.  doi:10.13474/j.cnki.11-2246.2021.374

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The population grided data with high spatial precision has the characteristics of high spatial resolution and accurate spatial distribution of the population. It is widely used in estimation of the affected population and urban planning.There are many publicly available population grided datasets, such as WorldPop which have the disadvantages of inaccurate of population spatial distribution and low spatial resolutionon small scales. Based on land use data of Dongying, combined with land use weight and area weight to optimize the spatial accuracy of WorldPop. Produce the population grided data with 25 m resolution of Huanghe street in Dongying. Compared with the WorldPop data, the dataset processed by this method has better spatial resolution and more accurate of population distribution, in the visual comparison. The differences in the statistics of the proportion of the population in each land use reflect the spatial distribution of population is highly consistent with the distribution of land use units. This method provides a new idea for obtaining population grided data with high spatial accuracy in a small area.

Forecast of maximum water increase in typhoon storm surge based on random forest model

ZHU Peijing, LUO Nianxue, ZHAO Qiansheng

2021, 0(12):  71-74,82.  doi:10.13474/j.cnki.11-2246.2021.375

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Using 98 typhoon storm surges that landed in Guangdong, Fujian, and Zhejiang provinces from 1989 to 2018.Seven input factors of minimum central pressure, maximum wind speed, central pressure at landing, wind speed at landing, typhoon intensity at landing, landing location, and landing direction are selected, and a random forest regression model is used to predict the maximum water increase duing to typhoon storm surge, and it is verified with real data. The model is applied to the prediction of typhoon storm surges in the coming years, and the practicability of the model is illustrated by taking Typhoon Lichma in 2019 as an example. The maximum water increase at tide gauge stations simulated by Mike21 software is used to construct a prediction model for the maximum water increase at tide gauge stations, which is planned to be applied to the prediction of the maximum water increase at the port station and Beijin station in Guangdong province. The results show that it is feasible.

Fast semantic segmentation of surface engineering activity area based on multi-feature U-Net

HUANG Lei, CHEN Erdonghao

2021, 0(12):  75-78.  doi:10.13474/j.cnki.11-2246.2021.376

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In order to effectively monitor the engineering activities with filling, digging, mining and stripping behaviors, this paper proposes a remote sensing multi-feature semantic segmentation model for pixel-level surface engineering activity extraction. In this model, GF-2 optical remote sensing images are used as the data source, and U-Net is used as deep neural network. By manual labeling, the surface engineering activity image samples are constructed for model training with multi-dimensional features, so as to achieve the effect of surface engineering activity extraction. The experimental result shows that the overall extraction accuracy of this method is 87.36%, and the average accuracy is 86.78%, which is better than KNN and SVM. The proposed method provides a technical reference for the automatic supervision of engineering activities.

Study on the application of SAR images in monitoring the build paddy fields in Guangdong province

LIU Jian, WANG Dongzhi

2021, 0(12):  79-82.  doi:10.13474/j.cnki.11-2246.2021.377

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The top priority of the monitoring the build paddy fields is to cultivate rice at least once a year. In order to realize low-cost and high-efficiency monitoring, the rice recognition technology based on Sentinel-1A images with high revisit is applied in the monitoring of built paddy fields in Guangdong province, and the results are verified by field photos. The results show that the overall accuracy of the identification results of the first rice is 85.02%, and that of the second rice is 90.46%, which indicates that this method is practicable to judge the rice planting situation, and can effectively narrow the field verification scope and improve the monitoring efficiency.

Application of remote sensing technology in site selection of a station on Sichuan-Tibet Railway

YUAN Dong, REN Jinlong, ZHANG Guangze, XU Zhengxuan, FENG Tao

2021, 0(12):  83-87,93.  doi:10.13474/j.cnki.11-2246.2021.378

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The Kangding station of Sichuan-Tibet Railway is located in the alpine valley area. It is extremely difficult to locate the station because of highly different terrain and complex geological environment. Through the full application of high-resolution remote sensing technology, supplemented by thermal infrared, InSAR and other new remote sensing technologies, the major engineering geological problems such as active faults and unfavorable geology in site selection area of the station are identified in detail and analyzed comprehensively. Sandaoqiao is selected as the optimum scheme for the station site. It provides an important basis and guidance for engineering geological mapping and exploration work. The research results have reference value for similar station location work in complex and dangerous mountainous areas.

Deep learning architecture for building extraction using LiDAR point clouds

HU Chuanwen, LU Shijie, YANG Wenjing, ZHU Xiaoyong

2021, 0(12):  88-93.  doi:10.13474/j.cnki.11-2246.2021.379

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Aiming at the problem of applying deep neural network algorithm to LiDAR point cloud for large-scale building extraction, PointCNN and PointNet++ models are selected for modification and comparison in this paper. For PointCNN, the parameters are adjusted to make it more suitable for large scenes. For PointNet++, in order to add more features and speed up the training efficiency of network model in large scenes, a K-means layer is added after the sampling layer. Finally, through training and verification on the test data set, it is found that the deep learning methods can well solve the disordered characteristics of point cloud and make better use of the spatial correlation between points. The accuracy of the improved models is more than 96% and they are also better than the original models in time consumption and extraction effect.

Radiometric performance change monitoring of GF-6 pan multi-spectral sensor based on automated technology

ZHAO Shengbing, RAO Jun, XU Zhaopeng, ZHANG Xuewen, LIANG Zhihua

2021, 0(12):  94-98.  doi:10.13474/j.cnki.11-2246.2021.380

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The traditional ground-based method has a low cost-effectiveness and large uncertainty of single experiment, which can not meet the requirement of high frequency and high-precision radiation performance change monitoring of satellite payloads. A based on automated method is applied on radiometric performance change monitoring of GF-6 pan multi-spectral sensor(PMS) based on the Dunhuang radiation site (hereinafter referred to as "Dunhuang site"). The results show that decay of radiation performance is less than 5% since GF-6's launch.

Research on the correlation between land cover and climatic status based on Google Earth Engine

CHEN Wei, LIU Xiangyuan, ZENG Sheng, ZHANG Huaping, MAO Zhifang

2021, 0(12):  99-104.  doi:10.13474/j.cnki.11-2246.2021.381

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In order to explore the correlation between surface cover and climate status, this paper selects Landsat image data in 2019 and three climate indicators using temperature, precipitation and PM_2.5 concentration, by GEE platform, combined with NDVI, MNDWI and NDBI, and uses SVM, RF and cart methods to classify surface cover, so as to explore the correlation between climate indicators and surface cover type distribution. The method of using three climate indicators to construct classification features for land cover classification is proposed, and the influence of climate indicators on the accuracy of land cover classification is analyzed through ablation experiments. The results show that:① RF has good classification results, and the overall accuracy is 96.0%; ② The three climate indexes can improve the accuracy of surface cover classification, and the concentration of PM_2.5 is the best; ③ Temperature is closely related to vegetation and water body, PM_2.5 concentration is highly correlated with urban area and vegetation, precipitation is closely related to cultivated land.

High-precision map vectorization mapping based on vehicle borne laser point cloud

ZHAO Yan, CAO Yuming, HUANG He

2021, 0(12):  105-109,114.  doi:10.13474/j.cnki.11-2246.2021.382

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According to the results of feature extraction in vehicle laser point cloud, the requirement of automatic vectorization is put forward. In this paper, a method of edge detection and vectorization based on bi-directional integration is proposed. Experiments results show that:The method is feasible in dealing with practical problems. Outlier filtering is applied to the input feature point cloud to ensure the accuracy of the feature point cloud of the outsourcing box algorithm. Three-dimensional point cloud is projected to the optimal plane according to the bounding box algorithm to provide input for the subsequent integration along all directions. According to the eight neighborhood KD-tree algorithm, the mean neighborhood radius of the sample feature point cloud is calculated. The purpose is to provide the differential elements in the integration domain for the integration in all directions according to the neighborhood radius. According to the provided differential element, we integrate in all directions, and find the optimal solution of the maximum distance from the plane in the integral element. After that, the point cloud index is constructed according to the integration results, and finally the vectorized point cloud of high-precision map is obtained. The result not only ensures the basic features of the feature, but also ensures the absolute accuracy of the point cloud.

Feasibility of the vehicle laser measurement system in quality inspection

ZHANG Shaoping, ZHAI Yongcong, WANG Liuzhao, MAO Mingkai

2021, 0(12):  110-114.  doi:10.13474/j.cnki.11-2246.2021.383

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Quality inspection and acceptance of surveying and mapping results is a very important part in the whole process of surveying and mapping production projects.The existing inspection methods mainly use total station and GNSS RTK field purchasing points, which are heavy in workload and small in number.With the continuous emergence of new technologies, traditional methods can not meet the requirements of rapid update of data and continuous improvement of accuracy.Vehicle-mounted laser scanning and measurement technology, as one of the cutting-edge technologies in modern surveying and mapping field, has fast data acquisition speed, high automation degree of data processing, intuitive data results, high-precision and strong mobility, and is very suitable for quality inspection of all kinds of surveying and mapping data results.In this paper, SSW vehicle-mounted laser modeling and measurement system is used to scan and collect data from 15 sample areas. After automatic extraction and screening of feature points, data results for inspection are obtained. Compared with the data obtained by conventional methods, the feasibility of the the technology for quality inspection is verified.

Consistency quality inspection methods of geographic conditions element data

LI Hai, ZHOU Jin, YAN Qingqing, CHEN Chunxi

2021, 0(12):  115-119.  doi:10.13474/j.cnki.11-2246.2021.384

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Combined with the process quality control and quality review of national geographic national condition element data results, as well as the consistency requirements of geographic national condition element data results themselves, surface coverage classification data results, field survey verification data and special data, this paper analyzes the quality problems found in the inspection, and puts forward the quality control method of geographical national factor data results. This method provides technical reference for the quality control of national factor data results and a method basis for quality inspection.

Study on the relationship between geo-spatial factors and distribution of poverty: taking Hezhang county as an example

ZHANG Lanlan, WU Qiming, SHEN Chaoyong, LIU Fang, CHEN Yanguo

2021, 0(12):  120-123,129.  doi:10.13474/j.cnki.11-2246.2021.385

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Taking Hezhang county as an example, this paper takes the township as the research unit, constructs the evaluation index of geo-spatial factors from the aspects of topography, land resources, traffic conditions, etc. Using geodetector and weighted regression model, it scientifically reveals the influence of geographical space factors on the spatial differentiation of poverty, and reveals the spatial distribution of poverty degree and resources and environment from the perspective of space. The study provides decision-making reference for the implementation of policies to achieve targeted poverty alleviation and consolidate the achievements of poverty alleviation.

Generalization method for land polygons of the third national land survey

LIANG Lei, ZHOU Qi, REN Dongyu, WEN Xuehu

2021, 0(12):  124-129.  doi:10.13474/j.cnki.11-2246.2021.386

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Deriving multi-scale database from the third national land survey database is an important task for cartographers.In this paper, we focus on processing large number of Land polygons,study the raster generalization for land polygons to reduce broken and small land polygons, construct the semantic proximity model and the spatial geometric topology model,analyse land features map generalization based on the topology and geographical characteristics of the region, establish an automatic land generalization production process.Based on the above methods, the computer programming technology is used to develop land generalization system and generalize land features with about 230 000 land features of a county in Sichuan province to test the system.It turns out that the method proposed in this paper meets the requirements of thematic mapping and greatly improve the automatic generalization efficiency of land polygons.

Application of natural resources supervision “one-map” system in Yan'an city

HAO Qili, ZHOU Jiawei, XU Peigang, WANG Hongsen

2021, 0(12):  130-133.  doi:10.13474/j.cnki.11-2246.2021.387

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Supervision of natural resources takes an important part in natural resources managements. The supervision "one-map" system of Yan'an is taken as an example to illustrate the construction practice. The system establishes the menu of natural resources in Yan'an city, integrates thematic supervision services used in land use surveillance and water retention estimation, and provides a cloud-based information infrastructure to meet the potential demands in computation and storage. The one-map system can provide strong support for natural resources supervision and lay the foundations for profound services.

Methods and implementation of urban physical examination evaluation based on spatio-temporal data mining: a case study of Wuxi city

HUANG Yongjin, ZHANG Tao, LIAO Xinguo, SHAO Shuhua, QI Zhirui

2021, 0(12):  134-139,157.  doi:10.13474/j.cnki.11-2246.2021.388

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As one of the hotspots of current research, spatiotemporal data mining provides new ideas and technical means for urban research. In this paper we take Wuxi city as an example, and build the corresponding data mining model by using multi-source heterogeneous spatiotemporal data such as the mobile signaling, traffic jam data, POI data and urban planning achievement. Then we do some analysis of urban main characteristics such as human occupation and residence balance, regional contacting degree to build the urban evaluation system based on multi-source data mining, explore the application of spatiotemporal data mining in urban physical examination, in order to provide scientific evaluation and decision-making for urban planning, operation management.

Dynamic ship vector plotting method for large-scale real-time data

ZHANG Yingdong, GENG Zengtao, WANG Haiyin, QIAO Xin, ZHOU Shengchuan

2021, 0(12):  140-144.  doi:10.13474/j.cnki.11-2246.2021.389

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Ship visualization and analysis play an important role in the field of modern navigation management. In view of the disadvantages of the current mainstream ship symbol expression, such as distortion and difficulty in interaction. This paper proposes a vector plotting method for real-time dynamic data of ships in large space range. We implement real-time access to ship data streams for creating a continuously updated ship feature service based on spatio-temporal GIS technology. The front-end program establishes two-way communication with the service through WebSocket, obtains the latest ship positioning information with low latency, and combines multi-spatial scale expression rules and plotting algorithms for symbol redrawing to achieve accurate expression of ship position, size, and heading under different display levels. Tests have proved that this method can effectively support the dynamic visualization of ship data in a large geographic area and meet the needs of ship collision avoidance, maritime management and application analysis.

Research on centralized processing work pattern based on cloud environment

CHEN Zhao, BAI Mu, GUO Chunxi, HAN Pengfei

2021, 0(12):  145-148.  doi:10.13474/j.cnki.11-2246.2021.390

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This article analyzes the pain points of the traditional DSM, DEM, DOM image data processing production mode, after a lot of preliminary testing and research, the method based on HCI, GPU cloud computing and cloud desktop is used as the underlying system architecture of this research, builds a production resource pool for the multi-tenant model, in order to solve the shortcomings of the traditional mode. Through the test data comparison, the centralized processing method based on the cloud environment has a significant improvement in resource utilization and management methods, which can give full play to the capabilities of underlying hardware, further improve production efficiency. At the same time, it can effectively solve the problem of resource waste caused by repeated procurement and repeated deployment. The research results of this article will also be further promoted and applied in the actual project.

Design and realization of containment bulge measurement system

XU Yaming, ZHANG Yu

2021, 0(12):  149-152.  doi:10.13474/j.cnki.11-2246.2021.391

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In the nuclear power industry, the internal inspection of the containment can directly reflect its performance, which is a very important task. At this stage, the bulge measurement of the containment lining in the internal inspection is mainly carried out by manual measurement. Aiming at improving the efficiency of the traditional method, a new system for bulge measurement has been developed in this paper. This system is developed based on the Raspberry Pi platform, using laser displacement sensors and ultrasonic ranging sensors to realize automatic measurement and identification of the containment bulge, which can improve efficiency and reduce costs. In addition, the design experiment is carried out to analyze the accuracy of the system. The example shows that the measurement accuracy of the system is better than the requirements of the internal inspection, which shows that the system is practical and feasible.

Research and application on integrated service platform of the joint surveying and mapping for life-cycle of construction project

SUN Xiaowei, QIU Junwu

2021, 0(12):  153-157.  doi:10.13474/j.cnki.11-2246.2021.392

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From the standpoint of approval, management, services and supervision in the construction project field, this paper proposes to construct the platform for the full life-cycle of the construction project and then further explores the key technologies involved in multi-source data integration, the spatio-temporal data, GIS,BIM and 3D for the purpose of the management, sharing and service of these mass,multi-source and heterogeneous data for approval, management, services and supervision. At last, this paper showes the examples of the usage of these technologies to provide a reference for the others.

Comprehensive teaching reform and practice of “Geographic Information System Principle and Application” under intelligent teaching environment

CHENG Gang, YANG Jie, WANG Lei, JING Haitao, HE Shi

2021, 0(12):  158-162,167.  doi:10.13474/j.cnki.11-2246.2021.393

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Taking the new round of undergraduate education and teaching reform as an opportunity, taking the new demand of talents in the field of social economic development and surveying and geographic information industry as the guidance, taking the development of new technologies such as earth observation technology, big data, artificial intelligence, Internet plus as the driving force, taking the wisdom teaching environment as the teaching framework, and facing the curriculum teaching problems, the OBE education philosophy has been implemented in the research. The paper designs the course objectives reversely according to the graduation requirements, takes students as the center, deeply explores the teaching methods and management methods such as online and offline mixed teaching mode, story teaching method, collaborative education and whole process assessment. A number of comprehensive reforms and innovations have been carried out from the aspects of ideological and political education of course, teaching mode, teaching content, teaching methods, teaching organization and teaching management. Taking the teaching practice of "geographic information system principle and application" as an example, the relevant modes and methods have been verified, good teaching effect has been achieved, the course quality has been improved, which strongly supports the development of graduates' core competence. The relevant achievements obtained a number of teaching awards, which have been highly praised by students and recognized by peer experts.

Construction and application of UAV photogrammetry virtual simulation system for experiment teaching

ZHOU Guoqing, GUO Baoyu, WANG Haoyu, CHEN Jianjun

2021, 0(12):  163-167.  doi:10.13474/j.cnki.11-2246.2021.394

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Due to the relatively expensive equipment such as drones and their loaded cameras, LiDAR, and the high cost of experiments and maintenance of these instruments, they have become a bottleneck in improving the quality of talent training. My school has given full play to the school-enterprise cooperation platform, carried out the exploration of virtual simulation teaching, and constructed the UAV photogrammetry virtual simulation teaching system, which has solved the above problems better through virtual simulation teaching. Through virtual simulation teaching, the UAV operation ability of the students majoring in surveying and mapping in our school has been greatly improved, and they have won excellent results in the four consecutive Guangxi University UAV Competitions. This provides a certain amount of practical experience for the training of high-quality talents in surveying and mapping majors in local universities.