Table of Content

25 May 2021, Volume 0 Issue 5

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Study on classification of spatio-temporal big data

TIAN Lizheng, LI Chengming, LIU Xiaoli, YIN Jie

2021, 0(5):  1-4.  doi:10.13474/j.cnki.11-2246.2021.0131

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“Unified exercise of the responsibility of the owner of all natural resources assets owned by the whole people, unified exercise of the responsibility of all land and space use control and ecological protection and restoration” is a new demand for the organization and classification of spatio-temporal big data after the establishment of the Ministry of Natural Resources. On the basis of summarizing the evolution characteristics of domestic big data classification system and analyzing the existing problems of China’s current spatio-temporal big data classification system, combined with the demand of the Ministry of natural resources for big data classification, and through historical inheritance, merger and addition, a set of spatio-temporal big data classification system that can serve both the “two unifications” responsibilities of the Ministry of Natural Resources and the whole society is proposed. The classification system of spatio-temporal big data established in this study is a three-level classification with six types, which can be divided into seventeen first-level types, sixty-eight second-level types and twenty-four third-level types. Compared with the previous classification, the most obvious change of this classification is to separate the natural resource data into a large category, which is of great significance for the organization and management of big data.

Study on attribute joining and extension approach between spatio-temporal data for new surveying and mapping

WANG Yuhong, LIU Kangchen

2021, 0(5):  5-9.  doi:10.13474/j.cnki.11-2246.2021.0132

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Attribute joining is an important operation and method to integrate multi-source attribute data from new surveying and mapping, enrich entity information and promote knowledge mining and service. The limitations of ArcMap in join predicate, join type, join cardinality and other aspects are analyzed and explained base on the summary of the concept and type of join. Aiming to these limitations, the popular AO addin technology at present is chosen to design and implement an extended attribute join toolbar, named eJoin. Its interface component elements and function implementation strategies are discussed in detail. Many experiments for testing it have been done using various datasets. The results show that the extended toolbar can efficiently carry out many kinds of join operation between data tables such as general join, self join, m∶n join, projection join, etc., and supplies more practical, convenient, flexible tool supports for attribute joining between spatio-temporal data from new surveying and mapping.

Surface classification information mining based on multi-source spatio-temporal data

DU Meng, ZHAO Ping, ZHANG Hao, ZHU Mingfei, QIAN Mengru

2021, 0(5):  10-14.  doi:10.13474/j.cnki.11-2246.2021.0133

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With the development of territorial space, the demand for surface classification information in natural resource management and territorial space planning is increasing day by day. How to obtain the surface classification information efficiently and accurately by using the data mining method has become an important research direction. Based on the analysis of multi-source data, referring to the classification scheme of the third national land survey, taking multi-source spatiao-temporal data as the data source, multi-dimensional surface classification, semantic rules mapping, spatial comprehensive mapping, multi-scene feature judgment, classification weight judgment, spatial aggregation analysis and other methods are used to mine the surface classification information. the paper proposes a method of surface classification information mining with the advantages of gathering multi-source data. It is of great significance to enrich the product types and information dimensions of surface classification data.

Fine-grained clustering based on spatio-temporal big data of shared bikes

ZHANG Qiang, BAI Zhengdong, XIN Haohao, CHENG Yuhang, GUO Jinping

2021, 0(5):  15-19,29.  doi:10.13474/j.cnki.11-2246.2021.0134

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Aiming at the problem that the clustering results obtained by the traditional methods such as K-means and DBSCAN alone when clustering the location data of shared bikes are inconsistent with the real clustering structure, a fine-grained clustering method(FGCM) based on spatio-temporal big data of shared bikes is proposed. This method uses DBSCAN to perform initial clustering, and on this basis, uses GMM-EM algorithm to perform detailed clustering to extract fine-grained hotspots. Experiments show that this method can eliminate noise and outliers based on the density threshold, has no need to specify the number of detailed clusters, and the shape and size of the clusters are more flexible. In the case of clustering the location features of the big data of shared bikes, compared with traditional methods that use K-means or DBSCAN alone, FGCM has a higher degree of refinement, and can fully demonstrate the actual characteristics of shared bikes, which can be used to plan facilities such as electronic fences and helps to regulate the parking of shared bikes without reducing the commuting efficiency.

Application of spatio-temporal fusion technology in time series classification of regional land cover

GU Chunxia, LI Dacheng

2021, 0(5):  20-24.  doi:10.13474/j.cnki.11-2246.2021.0135

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Due to the low time series of medium and high-resolution remote sensing image data, the time series characteristics of ground objects cannot be accurately recorded during the classification process. In order to increase the temporal change characteristics of ground features, the study uses the spatio-temporal fusion model to reconstruct high-sequence and high-resolution remote sensing images, and analyzes the influence of adding temporal features on the classification results. Taking the central area of Shijiazhuang City, Hebei Province as an example, the study uses three spatiotemporal fusion models to reconstruct high-time sequence 30-meter resolution remote sensing images to add time series classification features. This study uses random forests to classify annual reconstructed time series images, and analyzed the impact of different number of reconstructed images and different time spans on the classification results. Experiments show that the accuracy of image classification by reconstructing annual time series is better than that of single image. The classification accuracy increases with the number of time series images, when the number of images is selected as 12 scenes (one scene per month), the classification accuracy tends to be stable. And different time periods have different influence on classification results. With the introduction of imagery during vegetation change, the classification accuracy is the highest.

Analysis of spatio-temporal changes of land cover and landscape pattern in Guangdong-Hong Kong-Macao Greater Bay Area

GAO Zhaozhong, WEI Haixia, HUANG Tielan

2021, 0(5):  25-29.  doi:10.13474/j.cnki.11-2246.2021.0136

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Guangdong-Hong Kong-Macao Greater Bay Area is a mega-city cluster with the goal of becoming a world-class city cluster. Multiple periods of remote sensing data and the landscape pattern index are used to find the development law of the Greater Bay Area from 2000 to 2020 in this paper. The results show that: ①The main land cover types in the Greater Bay Area are forest land, arable land, and residential and construction land. The total proportion of the three types of land is more than 80% for many years. ②The residential and construction land in the Greater Bay Area is increased by 115.21% in 20 years with the area growing to 9 183.47 km², which is the land type with the largest area growth and the fastest rate of change in the Greater Bay Area. ③The fragmentation and patch density of the landscape pattern in the Greater Bay Area is decreasing continuously. The degree of landscape aggregation and landscape abundance is increasing. The distribution of regional landscape patterns is becoming increasingly rational.

Summary of the establishment and development of marine stereoscopic observation network

LI Linyang, CHAI Hongzhou, LI Shanshan, QIAO Shubo, KUANG Yingcai, Lü Zhiping

2021, 0(5):  30-37,95.  doi:10.13474/j.cnki.11-2246.2021.0137

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The high-accuracy global marine stereoscopic observation network is a critical segment of the integrated outer-space, spatial, terrestrial and marine observation network, and it is also an important extension of the terrestrial observation network and spatial observation network to the ocean. The composition of marine stereoscopic observation network including the marine space-time frame network and marine environment monitoring and sensing network is systematically introduced in this paper. And such core equipment as underwater navigation and positioning, marine geophysical environment detection, polar navigation and positioning and big data center is studied and reviewed in detail. Facing up our strategy of managing the ocean and building a maritime power, the trend of marine stereoscopic observation network should be followed and its construction should be speed up.

Vertical deformation caused by glacial isostatic adjustment in Canada based on GAMIT/GLOBK and GPS measurements

ZHANG Hanwei, CHEN Wei, LI Jiancheng

2021, 0(5):  38-42.  doi:10.13474/j.cnki.11-2246.2021.0138

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Based on the GAMIT/GLOBK software, this paper processes the original GPS observation data, with a time span of 2000—2018, from 31 IGS stations in Canada, and obtains the time series of the station vertical velocities under the ITRF2014 reference frame. With jumps corrected and outliers eliminated, this paper removes contributions from elastic deformations caused by the recent melting of glaciers, and estimates the uplift rate of GPS stations caused by glacial isostatic adjustment (GIA) from the GPS time series. The differences between the results and the previous results are within 2 mm/a, and the difference between the results and the predicted value of the ICE6G series GIA model is within 3 mm/a, which verify the correctness and reliability of the results. This study has laid a solid foundation for constraining and improving the GIA model by using observation data from global GPS stations.

Influence of Nepal Mw7.8 earthquake on glacier deformation and velocity in the Everest region

HE Zhengfeng, ZHANG Jixian, HUANG Guoman, SHENG Huijun

2021, 0(5):  43-48,101.  doi:10.13474/j.cnki.11-2246.2021.0139

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Based on the L-band ALOS PALSAR-2 data, this paper uses time series InSAR technology to dynamically monitor the Tibetan Plateau from September 2014 to August 2019 and combines the offset tracking method to obtain the difference of the results of the glacier flow velocity distribution in the distance, azimuth and horizontal directions some glaciers before and after the Nepal earthquake. It is found that during the monitoring period, there is a general phenomenon of subsidence in the study area, only a small range of uplift occurs in a few years, and the maximum annual average deformation rate can be achieved -203.1 mm/a during the monitoring period. it is believed that the earthquake has a special impact on the fluctuation of the time series observation results in the study area; during the study period, the velocity of some glaciers increased during a long period of time after the earthquake, and the maximum velocity can reach 2.645 m/d, it is believed that earthquake is the cause of the rapid increase in glacier velocity.

Analysis of the variation of NPP and its responses with climate changes of global tropical forests

YANG Ruifang, YIN Siyang

2021, 0(5):  49-53,110.  doi:10.13474/j.cnki.11-2246.2021.0140

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Based on MODIS data,using mask analysis to extract NNP data of the study area, and combined with meteorological factor data,we compare the NPP variation and its climate response among three main tropical forests in the world from 2001 to 2013 through geographical information technology and statistical methods. Results show that the total NPP of the whole study area has a decreasing tendency. Comparing the correlations between NPP and temperature, precipitation as well as photosynthetically active radiation (PAR), we find that the NPP of Amazon basin and Congo basin sub-study areas are more sensitive to the change of temperature, while Southeast Asia sub-study area is more sensitive to the change of precipitation. Among the three sub-study areas, Southeast Asia sub-study area has a relative close relationship between NPP and climatic factors, Congo basin sub-study areatake second place, and Amazon basin sub-study area at the end. This study has a certain reference value for further understanding the relationship between global tropical forest change and climate.

Automatic intrinsic and extrinsic calibration for a monocular camera-odometry system

YUAN Debao, CAI Liangli, WANG Cheng

2021, 0(5):  54-58.  doi:10.13474/j.cnki.11-2246.2021.0141

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In this paper, we provide a novel intrinsic and extrinsic calibration method for a monocular camera and odometry system automatically. Unlike previous methods aiming at only alternative intrinsic or extrinsic parameters, this method efficiently calibrates both intrinsic and extrinsic parameters using one platform in a unified way. Our platform contains four chessboards with three of them assembled in an optimized way for intrinsic calibration, and the fourth chessboard for the extrinsic calibration. Based on this platform, the camera-odometry system only need to take one shot image of the three chessboards for intrinsic calibration, and then move with a planar z-path seeing the fourth chessboard for the extrinsic calibration. Testing on the real dataset collected from clear robot, we show that our method can accurately estimate the intrinsic parameters with a measurement to evaluate the calibration quality automatically, and it’s effficient and outperform the previous methods.

Spatialization of population in Guangzhou supported by nighttime light data

WU Xianwen, SU Yunzhong, SUN Zhaohui

2021, 0(5):  59-62.  doi:10.13474/j.cnki.11-2246.2021.0142

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Understanding the spatial distribution of population can provide data to support urban management and urban planning, which is of great practical significance for improving urban development. Therefore, this study uses the nighttime light (NTL) image of LJ-1 01 as the basic data, Guangzhou as the study area, and combines the population estimation model and other methods to carry out a study of population spatialization based on NTL data. The results show that the LJ-1 01 NTL data can be effectively applied to the study of population spatialization. After population spatialization, the population distribution in Guangzhou has a distinctive feature of “one main center, multiple cores”, and the differences in population distribution within each area can be clearly shown and distinguished. The results of this study can be of some value in supporting urban planning and urban management.

UAV elevation route planning and modeling analysis for complex mountain landslides in Dongchuan

BI Rui, GAN Shu, YUAN Xiping, LI Raobo, HU Lin, GAO Sha

2021, 0(5):  63-67.  doi:10.13474/j.cnki.11-2246.2021.0143

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Using single-lens four-rotor small UAV as experimental equipment, for single and high-drop landslides in complex mountain areas, the use of landslide-oriented elevation route planning is proposed in this paper, combined with traditional single-level routes and cross-cutting route planning to construct three-dimensional under different routes model. The methods of constructing three-dimensional (3D) models under different routes are evaluated and analyzed through three aspects: the degree of overlap, the integrity of the 3D model, and the accuracy of the 3D model analysis by placing ground targets. Experiments show that the use of elevation routes can achieve 98.72% heading overlap and 88.82% sideways overlap; the model texture details, color information and ground information richness obtained by using elevation routes are all better than that of the traditional two routes obtained; for target measurement error calculation, the accuracy of the model obtained by using the elevation route is higher.

Non-urban surface deformation monitoring based on improved PS-InSAR

ZHAO Zhongshu, ZHANG Hongfeng

2021, 0(5):  68-72.  doi:10.13474/j.cnki.11-2246.2021.0144

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To solve the problem of large monitoring errors caused by insufficient distribution of permanent scatterers (PS), when PS-InSAR is applied for non-urban ground deformation monitoring, an improved PS-InSAR algorithm based on partial time scatterers is proposed. Based on the analysis of a large number of partial time scatterers in non-urban areas, the partial time scatterers are extracted through the combination of dual threshold and credible probability after the image is denoised by improved EMD algorithm. And then, the deformation rate is calculated through the iterative estimation of the different parameters and the phase separation of the partial time scatterer, obtaining the surface deformation of the monitoring area. Experimental results show that the extracted partial time scatterers basically cove the PS points extracted by the traditional PS-InSAR algorithm and maintains their spatial distribution characteristics and the timing change trend. The spatial distribution density required for surface deformation monitoring in non-urban areas is greatly improved. Improved the accuracy of non-urban surface deformation monitoring, which verifies the effectiveness of the algorithm.

GMDH model inversion of Cr content in cultivated soil under spectral unmixing

GUO Yunkai, ZHANG Qiong, ZHANG Siai, XIE Xiaofeng

2021, 0(5):  73-76.  doi:10.13474/j.cnki.11-2246.2021.0145

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Aiming at the problems of weak spectral response between remote sensing image reflectivity and heavy metal elements, and low accuracy of soil heavy metal classical inversion models.In this study, Sentinel-2 remote sensing image is used as the data source, and the dimidiate pixel model is used for image spectral unmixing. The characteristic spectra with high correlation are selected as spectral parameters. PLS model and GMDH model of soil reflectance and heavy metal Cr content under different spectral transformations and pixel linear unmixing are constructed.The results show that there is a significant correlation between the spectra and the content of Cr, and the number of bands is increased and the correlation is enhanced.The GMDH model constructed based on the unmixed soil spectrum and the heavy metal Cr content has better model stability, stronger predictive ability and better accuracy.This research method expands the traditional method of remote sensing image inversion, and can provide a useful reference for monitoring soil heavy metal pollution in a large scale.

An EMD method to suppress boundary effect and its application in landslide monitoring

SUN Haoran, YUE Jianping

2021, 0(5):  77-80,90.  doi:10.13474/j.cnki.11-2246.2021.0146

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The correct decomposition of landslide displacement sequence has important influence on landslide prediction and early warning.Empirical mode decomposition (EMD) is a commonly used time series decomposition method, but it has endpoint effect in the decomposition process.Therefore, this paper improves the classical EMD method and proposes an EMD method to suppress endpoint effect.The improved method is analyzed and verified by using the data of Baige landslide in Jinsha River. The experiment results show that the improved method has good endpoint effect suppression effect and the prediction accuracy is also improved compared with the classical method.

Usability evaluation of road map schematic representation

GONG Chengyin, TI Peng, WU Hao, LAN Tian

2021, 0(5):  81-85.  doi:10.13474/j.cnki.11-2246.2021.0147

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The current schematic map representation is mainly for public transportation networks, and there is a lack of research on the usability evaluation of road map schematic representation. This study selects two typical road scenes: scenic spots and streets, and uses the latest automatic schematic method to generate schematic maps, and uses subjective questionnaire surveys combined with objective eye-tracking experiments to evaluate the usability of schematic representations of road maps. The experimental results indicate: ①The schematic representation can improve the simplification, clarity and user satisfaction of the road map, especially for the situation where the original road shape is more complicated. ②The shape simplification of roads may result in the changes of perceived lengths of different routes so as to influence the human decision-making for route planning. ③If the path schematic result increases the density of road network, the cognitive efficiency of schematic map is reduced. This study can be helpful for the improvements of design rules of automated schematization for road maps and enhances the practicability of schematic representations of maps.

Caculation of traffic congestion index based on betweenness centrality

YE Yexing, YANG Fei

2021, 0(5):  86-90.  doi:10.13474/j.cnki.11-2246.2021.0148

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Traditional betweenness centrality of road network mainly evaluates the theoretical road accessibility based on the proportion of the shortest paths in each section. Based on the traditional network betweenness centrality, this study proposes dynamic betweenness, as a new urban traffic congestion index, to evaluate the actual congestion of each section in the city from the perspective of the proportion of traffic volume. This paper calculates the betweenness of urban road network to reflect the accessibility of urban road sections, and calculates the dynamic betweenness and traffic trajectory with taxi GPS fixed-point data. The comparison of the two betweennesses can objectively and comprehensively reflect the traffic congestion, improves the reference value of the traffic congestion index, and provides a basis for decision-making for urban construction planning and road reconstruction, which contributes to alleviating the situation of urban road traffic congestion.

POS-assisted and nuclear line-constrained oblique image matching method

WANG Ting, CHEN Chaoran, PENG Mengyuan, HUANG Ershuang, HUANG Xia

2021, 0(5):  91-95.  doi:10.13474/j.cnki.11-2246.2021.0149

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In order to solve the problem of low efficiency and reliability of UAV oblique image matching based on SIFT feature points due to a large amount of redundant data, large image geometric deformation and repeated texture, a novel image matching method based on POS information and epipolar constraint is proposed. In this method, firstly, the image POS data obtained by the airborne GNSS/IMU device is used to calculate the object overlap area between the images, and then the object overlap area is projected to the image side, and then a highly reliable image pairs are selected according to the image overlap ratio of the two images. Secondly, after using the SIFT-GPU algorithm to extract feature points from the image, the antipolar relationship between the image pairs is estimated based on the POS data. Thirdly, the Euclidean distance between descriptors is a similarity measure, which can achieve efficient and robust matching of feature points. Finally, RANSAC algorithm is used to eliminate mismatches. The reliability of the proposed method is verified by the matching experiment of oblique image.

Photovoltaic land extraction from high-resolution remote sensing images based on deep learning method

WU Yongjing, WU Jinchao, LIN Chao, DOU Baocheng, LI Ke

2021, 0(5):  96-101.  doi:10.13474/j.cnki.11-2246.2021.0150

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In recent years, the rapid development of China’s photovoltaic industry has caused a lot of land use problems. Extracting photovoltaic land through remote sensing technology and monitoring the distribution and status of photovoltaic land are of great significance for the healthy development of the photovoltaic industry. This research proposes a set of automatic photovoltaic land extraction methods for high-resolution remote sensing images. Satellite images such as GF-1 and Google Earth images are used to construct photovoltaic land samples. A deep learning semantic segmentation algorithm based on the ResNeSt-50 and DeepLab V3+model is proposed. The deep learning results are post-processed with computer graphic methods and the general-purpose and high-precision automatic extraction of photovoltaic land for high-resolution remote sensing images are achieved. The proposed deep learning model has a verification accuracy of mIoU of 0.899 2, and the extraction results have good edge accuracy. The method has wide applicability, and supports images such as GF-1, ZY-3, GF-6, GF-2, and Google Earth images.

Research and accuracy analysis of image control point arrangement schemes for UAV oblique photography

WANG Zhaohui, WU Hao, MENG Jiang

2021, 0(5):  102-105,110.  doi:10.13474/j.cnki.11-2246.2021.0151

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With the rapid development of UAV equipment and computer-based digital image processing technology, UAV is more and more widely used in surveying and mapping industry. Especially in the current new form of natural resources development, the demand for three-dimensional “one map” is more and more urgent. UAV oblique photogrammetry technology has developed rapidly because of its convenience, flexibility and simple operation. But the UAV data generally has the problem of low elevation accuracy, and a large number of control points are needed to improve the accuracy. However, the existing specifications for field work of low-altitude digital aerophotogrammetry can not meet the requirements of UAV operation. Therefore, on the basis of considering the efficiency and the accuracy of the results, this paper discusses the influence of different image control layout schemes on the three dimensional accuracy of the UAV oblique photography remote sensing system and the results of the three-dimensional real scene model, and conducts relevant tests and accuracy analysis.

Construction of refined 3D model based on DP-Modeler

YANG Yanmei, WANG Ying, SHI Lei, TAO Sirong, LI Hong

2021, 0(5):  106-110.  doi:10.13474/j.cnki.11-2246.2021.0152

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The technology of automatic production of real 3D model by tilt photogrammetry has been developed and mature gradually, and it has the characteristics of high efficiency, low cost, good accuracy and simple operation. In order to make the real 3D model more refined and available, this paper firstly analyzes the automatic construction methods and processes of the 3D model, including preprocessing, aerial triangulation and 3D model generation. Then, the fine processing of 3D model is studied, including model modification and monomer model construction, the former mainly includes suspension deletion, road leveling, water surface mending and elevation texture modification. The latter mainly uses DP modeler professional software to reconstruct the monomer model. Finally, the specific application of the fine 3D model in planning, cultural relic protection and real estate registration is discussed.

UAV terrain following technology application in the mining subsidence monitoring research

YANG Xuting, YAO Wanqiang, ZHENG Junliang, MA Bolin, MA Xiaohui

2021, 0(5):  111-115.  doi:10.13474/j.cnki.11-2246.2021.0153

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This study aims at the problem that the monitoring accuracy of the same aerial survey aircraft varies greatly due to the topographic relief when the traditional UAV conducts subsidence monitoring in mining area. In this paper, the influence of terrain change on the resolution, photo overlap and monitoring accuracy of the shooting image was analyzed. The TOF sensor was installed on the UAV, and the PID controller was coded to maintain the same height and stable flight relative to the ground, thus realizing the UAV terrain following monitoring. The results show that the terrain fluctuation will reduce the monitoring accuracy of the traditional UAV, but the method proposed in this paper can improve its accuracy, so that the UAV can follow the aerial survey and ensure the monitoring accuracy. Meanwhile, in mining areas with complex terrain, the average precision of traditional UAV for subsidence monitoring is 65.73 mm, making the average precision of UAV with terrain following technology for subsidence monitoring reach 46.59 mm, and greatly improving the detection accuracy of UAV. Compared with the observation line data in the field, the results can predict the subsidence trend accurately, but can not accurately capture the subtle changes of the surface. Thus, the obtained subsidence scope can comprehensively and extensively reflect the area affected by the subsidence which caused by the advance of the working face. Therefore, the research results can provide reference for mining subsidence monitoring.

Analysis on regional spatial difference of railway transportation service: a case study of Jiangsu Provina

WU Qinshu, ZHU Yuexia, ZHAO Zhuowen, ZHANG Shizhi

2021, 0(5):  116-119.  doi:10.13474/j.cnki.11-2246.2021.0154

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Railway transportation plays an important role in regional economic and social development. Affected by macro-economy, industrial structure, population scale, natural conditions and other factors, regional railway transportation development level has obvious differences. It is of far-reaching significance to study the development degree of regional railway transportation service and analyze regional differences for further improving the layout of regional railway network and realizing the integration of transportation infrastructure supply. Based on the monitoring data of geographical conditions, this paper designs a method to analyze the spatial differences of regional railway transportation services. Taking Jiangsu Province in the Yangtze River Delta as an example, this paper studies the development degree of regional railway transportation service and analyzes the differences of railway transportation service in different regions. It provides reference for railway construction planning and regional transportation integration development.

Automatic matching method of land map in inspection area

LI Xiao, LI Yongzhi, SUN Xiyong, ZHAO Zheng, LI Yiqiao, ZHANG Gaoqiang

2021, 0(5):  120-123,144.  doi:10.13474/j.cnki.11-2246.2021.0155

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In the natural resources inspection work, in order to determine whether there is an illegal land use in the target area, ArcGIS software needs to be used to perform spatial calculations and summary statistics on the target area and land pattern data to provide data support for the implementation of the inspection work. At present, manual integration has problems such as the high production cost, the large workload, low accuracy, and inconsistent data naming and storage formats. For those reasons, this article realizes the automatic matching method of the ground pattern based on Python. This method can automatically complete the spatial calculation of the target area and the ground pattern, field calculation, Excel export and generation of pivot tables, etc. It greatly reduces the workload of the technical staff, effectively shortens the data preparation time of the inspection work, and has practical significance for improving the efficiency of the natural resource inspection work.

Recognition and early warning of deformation information in GNSS coordinate series based on the LWR-Pettitt method

DUAN Wei, WANG Min, WU Hao, LIU Chao

2021, 0(5):  124-128,154.  doi:10.13474/j.cnki.11-2246.2021.0156

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GNSS deformation monitoring data usually has no specific distribution characteristics, which is not conducive to the establishment of universal statistics. As a non-parametric test method, the Pettitt test is introduced to establish statistics of GNSS deformation monitoring data, and then the deformation information identification and early warning are carried out. However, the statistics constructed by the Pettitt test always have large fluctuation, and can only be used to identify the single deformation information. Therefore, a new method named LWR (Locally Weighted Regression)-Pettitt is proposed to optimize the statistics and threshold judgment method in the Pettitt test, and is used for GNSS deformation information identification and early warning in this paper. The experimental results show that the proposed method can identify the location of deformation information effectively, especially for trend-type deformation information, but for the abrupt-type deformation information, it can only identify the continuous deformation information more than two-fold standard deviation equivalent deformation.

Construction and application of modern surveying and mapping datum system in Zhuhai City

HUANG Jieyun

2021, 0(5):  129-131.  doi:10.13474/j.cnki.11-2246.2021.0157

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Fundamental surveying and mapping is the premise and foundation of economic construction and social sustainable development, as well as long-term and arduous public welfare establishments.Surveying and mapping datum is the cornerstone of fundamental surveying and mapping work and one of the key factors to ensure its development successfully.With the continuous progress of science and technology, in order to guarantee the construction and development of cities, many cities urgently need to establish the local modern surveying and mapping datum system.Taking Zhuhai City as an example, this paper expounds the construction of modern city surveying and mapping datum system, introduces the historical situation and existing problems of urban surveying and mapping datum, and focuses on the concrete construction of modern urban surveying and mapping datum, which mainly includes technical route and method, construction content and application of achievements.

Fusion application of the new surveying and mapping technology in the construction of new urban infrastructure model

XU Huajian, XIANG Yu, HUANG Zhi, HUA Yuanyuan

2021, 0(5):  132-136,166.  doi:10.13474/j.cnki.11-2246.2021.0158

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The construction of spatial information infrastructure is an important part of new infrastructure construction. With the rapid development of surveying and mapping technology, new surveying and mapping equipments such as remote sensing satellites, unmanned aerial vehicles and mobile survey vehicles are becoming more and more popular, Internet of Things technology is also widely used under the tide of new infrastructure construction. Based on this, this paper introduces how to use the ground moving measurement and oblique photography technology together to construct the 3D fine model, and introduces IoT data and BIM data into the model to realize the construction of new urban infrastructure construction model. On this basis, the application of new urban infrastructure construction model in bridge deformation monitoring is realized, which can be used for references in smart city construction.

Implementation and accuracy assessment of water level control in the Daya Bay waters

HE Zhimin, XU Jun

2021, 0(5):  137-139.  doi:10.13474/j.cnki.11-2246.2021.0159

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Coupled with the basic measurement examples of sea charts, the implementation steps and technical details of water level data preprocessing, datum surface determination, and water level accuracy evaluation are summarized in this paper. The residual water level synchronization curve and the accuracy evaluation result can directly and rigorously determin the residual water level strong correlation tide station. After careful argumentation, the water level correction method based on the residual water level monitoring and tidal model can be applied in the water of Daya Bay to meet the accuracy of water depth measurement and meet the requirements of relevant specifications. It can replace traditional water level correction methods, optimize the layout of tide gauge stations, and reduce the amount of tide stations.

Study on fine detection methods of non-excavation pipelines

HUANG Pengfei

2021, 0(5):  140-144.  doi:10.13474/j.cnki.11-2246.2021.0160

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Fine detection of underground pipelines refers to the use of special instruments and methods for key pipelines, difficult pipelines and special pipelines in key areas of engineering construction on the basis of conventional underground pipeline detection, and provides more accurate and more detailed results for design and construction through high-quality, high-density or high-precision detection. The fine detection of non-excavation pipelines is the most important one, and has always been a difficult problem in the industry, as conventional material detection equipment for such pipeline detection seems powerless. Through the application example in this essay, the accuracy and reliability of Ritchie SR-20 combined with micro tracer probe and inertial gyroscope positioning technology in the fine detection of non-excavation pipelines are verified, and the fine detection of non-excavation pipelines is able to be achieved depending on the site conditions and pipeline depths.

Application of open source systems in GIS programming course

KANG Mengjun, REN Fu, CAI Zhongliang, WENG Min, SU Shiliang, WANG Mingjun

2021, 0(5):  145-150.  doi:10.13474/j.cnki.11-2246.2021.0161

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The application of commercial GIS software in GIS teaching has weakened students’ understanding and exploration abilities of principles and algorithms. It is necessary to use an open source GIS solution instead. According to the teaching objectives and knowledge points of the GIS software development courses, this paper classifies the open source GIS software systems. At the same time, from the aspects of license agreement and development mode, a set of GIS software development, desktop development, and WebGIS development and open source solutions for mobile GIS development are proposed. Practices in teaching prove that the open source solution proposed in this paper can significantly improve students’ GIS software development skills.

Ideological and political education in “spatial analysis” course

LIU Qiliang, DENG Min, HOU Zhaoyi, HUAN Weihua

2021, 0(5):  151-154.  doi:10.13474/j.cnki.11-2246.2021.0162

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Ideological and political education is vital for cultivating people with morality. Although ideological and political education has been valued in university teaching, ideological and political education in Science and Technology courses is still in the exploratory stage. In this study, we firstly analyzes the connotation and characteristics of the ideological and political construction of Science and Technology courses. Then, we take the core course of geographic information science “spatial analysis” as an example to discuss some explorations and practices of integrating ideological and political education with Science and Technology majors. The curriculum construction experience introduced in this study may provide some references for promoting the teaching reform of geographic information science.

Analysis of steel structure deformation based on 3D laser point cloud

ZHAO Yabo, WANG Zhi

2021, 0(5):  155-158.  doi:10.13474/j.cnki.11-2246.2021.0163

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The deformation of steel structure is a common problem in engineering and industrial fields. If the deformation exceeds the allowable value of design, it will affect the normal implementation of engineering and the normal operation of industry. Traditional methods such as total station are used to detect the deformation of steel structure.But it is not only inefficient, but also difficult to fully and accurately reflect the overall deformation of steel structure. Taking the deformation of steel structure of a offshore drilling platform as an example, this paper introduces the method of detecting and analyzing the deformation of steel structure by using 3D laser scanner, filters and divides the point cloud collected in the field, and fits the 3D point cloud based on the steel structure design model.According to the collision analysis of the measured 3D point cloud and the fitting model, the spatial deformation of the steel structure can be obtained.

Research on measurement of case involved forest stump diameter based on 3D laser scanning

ZHANG Minxia, LI Jin, WANG Hengyue, MA Yuanfei

2021, 0(5):  159-161.  doi:10.13474/j.cnki.11-2246.2021.0164

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Use 3D laser scanning to obtain the point cloud data of the tree stump, and use the rich point cloud data processing function provided by Trimble Realworks software to measure the stump diameter and calculate the volume of the tree. Comparing the calculated results with those measured by traditional methods, it is shown that the volume obtained by measuring the diameter of the tree stump by the three-dimensional laser scanner meets the accuracy requirements of volume measurement, and the measurement efficiency is much nigher than that of traditional measurement methods, and the site can be fixed and restored. The indoor measurement was completed, which provided technical support for quickly and efficiently measuring the timber volume of the forest involved.

Application of refined modelling in maintenance and detection for extra large bridge

CUI Qinghong

2021, 0(5):  162-166.  doi:10.13474/j.cnki.11-2246.2021.0165

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In this paper, we use a variety of types of rotor UAVs and mounts by taking oblique photography, close photography, and other methods to obtain high-precision multi-angle images of the main bodies and the surrounding environments of the super railway bridges in steep terrain. Based on the images, we built the bridges’high-precision realtime three-dimensional model using a realscene modeling system and cloud servers. Such model results can provide effective data support for the daily maintenance and inspection of super railway bridges. The proposed method can make up for the deficiencies of existing methods, improve inspection efficiency, and reduce personnel risks. In this paper, we applied the proposed method to inspect the Nanpanjiang Bridge on the Yunnan-Guizhou railway, and also discussed the disadvantages and developments of the method.