Table of Content

25 January 2023, Volume 0 Issue 1

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Discussion on digital twin and metaverse in smart city construction

ZHANG Xinchang, LIAO Xi, RUAN Yongjian

2023, 0(1):  1-7,13.  doi:10.13474/j.cnki.11-2246.2023.0001

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With the in-depth integration of urban management and new technologies such as spatial big data,5G and artificial intelligence,the applications related to new smart cities have become the key concerns of the geographic information industry field and society. This paper introduces the background and concept,theory and technology of smart city,describes the relationship among digital city,smart city and digital twin city,summarizes the current situation and trend of digital twin city,and discusses the smart city in the metaverse era. The budding period of smart city relies on spatial information technology,database technology,virtual reality technology and computer network technology to build digital city,the development period integrates artificial intelligence technology,Internet of Things technology,cloud technology and spatio-temporal big data technology on the basis of digital city to build new type of smart city,and the construction period combines new type of smart city related technology and realistic 3D technology to realize digital twin. The cross-era metaverse smart city may integrate technologies or devices such as augmented reality,extended reality,brain-computer interface and somatic devices on the basis of the digital twin to realize the beautiful vision of human living in an amphibious world.

A real city 3D reconstruction method considering air-ground POS information

KANG Tingjun, XIA Yixiong, ZHANG Xinchang, ZHOU Jianfeng

2023, 0(1):  8-13.  doi:10.13474/j.cnki.11-2246.2023.0002

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Real 3D models provide a unified digital spatial base for the digital twin. In urban scenes, the parts that are obscured close to the ground as well as in the aerial view are difficult areas for 3D reconstruction. In view of the complex spatial environment of the city and the limited capability of UAV operations, This paper proposes an air-ground integrated real 3D reconstruction method that takes into account ground position and orientation system (POS) information based on the basic theory of tilt photography and air-ground integrated modelling, and is fine-grained modeled of the historical and cultural district of Foshan city based on this method. The experiments show that compared with conventional methods, the modelling of this method has the advantages of good effect and high efficiency, which is important for the production of real 3D products and multi-scale representation of spatial data, and can provide a better representation of geographical scenes for digital twin applications.

The wisdom renovation of old communities in the context of rapid construction of smart city

RUAN Yongjian, ZHANG Xinchang, JU Shengzhe, LIAO Xi, RUAN Baozhen, LIU Jiang, JING Fengrui

2023, 0(1):  14-19.  doi:10.13474/j.cnki.11-2246.2023.0003

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After decades of sustained and rapid urbanization in China, the urban system has gradually formed a large scale of old communities with the characteristics of low intelligence level. There is a contradiction between the old communities and the residents' needs for wisdom and convenient life. In this context, there is an urgent need for some reasonable solutions to enhance the old communities' wisdom to better serve community residents, and further promote the healthy construction and development of smart city. In this paper, we will take Sanyanjing community as an example to investigate the effective development path of smart transformation of old communities. Among them, key technologies for smart community transformation, such as CIM, 5G, cloud computing, and artificial intelligence are introduced, and practical construction solutions for old community transformation, including community services, smart security, smart infrastructure, public information security, and smart home care are demonstrated. It can provide valuable reference for the smart transformation of old communities under the construction of smart city.

A preliminary study on the application of digital twin technology in the management of small reservoirs

MAN Wang, LI Zongmei, NIE Qin, XU Kuan, CHEN Zhijing, LIAO Guihua

2023, 0(1):  20-25.  doi:10.13474/j.cnki.11-2246.2023.0004

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In order to solve the safety problems of small dams in our country,the digital twin dynamic supervision cloud platform of small dams is constructed based on the digital twin technology. This paper discusses the construction ideas of digital twin platform for small dams: realizing the security perception of rainwater and dam body based on IoT sensing equipment,building a unified spatio-temporal data base by constructing a fine 3D model integrating indoor and outdoor,realizing the fusion of video monitoring and 3D model,realizing intrusion detection based on AI technology,and finally building a cloud platform for dynamic supervision of small reservoirs. Digital twin technology can provide comprehensive real-time monitoring information for reservoir dams and realize real-time connection and dynamic interaction. This paper discusses the application of digital twin technology in reservoir dam management,which can provide reference for state perception and safety management of small dams.

Study on could rendering technology of intelligent mine digital twin system using unreal engine

LI Mei, JIANG Zhan, MAN Wang, CHEN Jinchuan

2023, 0(1):  26-30.  doi:10.13474/j.cnki.11-2246.2023.0005

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HTML5, WebGL, cloud rendering and other technologies provide the important technical supports for 3D rendering of various terminals such as browsers, mobile and XR terminals. After analyzing the advantages and disadvantages of the above technologies, a digital twin platform of the intelligent mine is proposed, with cloud rendering technology using unreal engine 4. The system is designed and verified by using oblique photogrammetry data, building information model, 3D roadway models and geological 3D models. The efficiency and effect of cloud rendering are analyzed, and the digital twin cloud rendering technology of intelligent mines is explored.

Integration of DMSP-OLS and NPP-VIIRS nighttime light remote sensing images

HE Liheng, Lü Meng, ZHU Tingru

2023, 0(1):  31-38.  doi:10.13474/j.cnki.11-2246.2023.0006

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DMSP-OLS nighttime light remote sensing data is terminated in 2013 and has been replaced by NPP-VIIRS nighttime light data. Therefore,in order to better serve the study of human activities with a longer time span,it is necessary to integrate the two types of nighttime light data to obtain a stable nighttime light dataset with a long time series. In this paper,two kinds of data integration methods based on resampling method are proposed to simulate NPP-VIIRS data from 2013 to 2020,and finally it establishes the 1992—2020 long time series correction-simulated DMSP-OLS NTL remote sensing data set. The evaluation shows that the integration method based on resampling method is effective (Pearson correlation coefficient ρ=0.985 2 for urban areas,RMSE=3.460 7),and the obtained integration data set is highly consistent with the relevant socio-economic reference (ρ=0.946 for the sum of image DN values and GDP,ρ=0.971 for population,Quadratic polynomial model fitting R²≈0.98,RMSE<5.55),which is superior to existing studies. So this NTL integration data set can support the study of long time series based on nighttime light images.

Forest land extraction based on Beijing No.2 and geographical national conditions data

DU Lindan, DONG Chun, ZHAO Rong, ZHANG Yu, KANG Xiaochen

2023, 0(1):  39-44.  doi:10.13474/j.cnki.11-2246.2023.0007

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The forest land in the geographic national conditions data does not include trees or single-row forests with a field area of less than 400 m². If we only use the forest land data of geographical conditions to calculate the regional forest coverage rate, there will be a large error in the statistical results of the forest land in the area with large surrounding trees. For the above problems, in order to accurately extract the forest land cover and spatial extent in the region, a forest land extraction method based on the Beijing No.2 high-resolution remote sensing image is proposed in this paper by using the geographical and national land cover data. Firstly, according to the spectral characteristics of remote sensing images, the land types are divided according to vegetation, roads, railways and construction land, and the remote sensing images are used to extract samples of each type, and the maximum likelihood classification is used to extract the vegetation coverage for the samples that have passed the separable test. Then, with the help of the geographical and national land cover data, the overlay analysis was used to eliminate the misclassification and misclassification, and obtain the regional forest land coverage rate and spatial distribution. The results show that: ① The forest land coverage rate in the study area is 20.3%, which has not yet met the needs of a new round of forest land planning in Beijing. ② The forest land area in the geographic and national conditions data accounts for 54.03% of the total extracted forest land area, indicating that the use of this method in some areas is not enough. It is necessary to supplement the geographical conditions of forest land data. The experimental result is based on the visual comparison with remote sensing images combined with the field survey results, and it is believed that the spatial distribution of the extracted forest land is basically consistent with the actual distribution. The research provides a new method for the application of geographic and national conditions. The results can assist the regional green development planning and help to construct a scientific ecological spatial pattern.

Super-resolution reconstruction of landslide image set based on enhanced generation countermeasure network

FANG Liuyang, LIU Tianyi, ZHAO Xin, WU Hao, JIA Zhiwen, ZENG Zhen

2023, 0(1):  45-51.  doi:10.13474/j.cnki.11-2246.2023.0008

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To address the problem of the lack of high-resolution training set in the use of high-resolution remote sensing images for landslide intelligent recognition. In the process of forming the high-resolution landslide training set, in order to make full use of the previous low-resolution landslide images, this paper adopts enhanced super-resolution generative adversarial networks(ESRGAN) to achieve super-resolution reconstruction of the low-resolution landslide image set. The ESRGAN model improves the feature extraction performance and stability of the generator by removing the batch normalization layer, adding multi-stage residual network and residual scaling factor based on the SRGAN model, and using the transfer learning method to conduct experimental based on the Bijie landslide image set and Yunnan Nanjing highway landslide image set. The experimental results show that the ESRGAN model based on transfer learning can achieve higher scores in peak signal-to-noise ratio (PSNR) and structural similarity (SSIM), and better results in super-resolution reconstruction. The results of this paper can provide a new technical method for acquiring high-resolution remote sensing image sets of landslides.

Optimal path-based radiometric block adjustment for unmanned aerial vehicle images

PENG Wanshan, GONG Yan, REN Jie, ZHOU Cong, YU Yajiao

2023, 0(1):  52-57,64.  doi:10.13474/j.cnki.11-2246.2023.0009

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Unmanned aerial vehicle (UAV) remote sensing can provide imagery data with high spatio-temporal resolution, and has a wide range of application prospects. Radiometric correction converts the data recorded by sensors to ground reflectance and is the prerequisite for the quantitative application of UAV data. However, UAV data is susceptible to many factors such as illumination conditions, resulting in different degrees of radiometric differences between images, which makes it difficult for the radiometric correction of multiple UAV images. Based on the information of images' overlapping area, radiometric block adjustment can obtain the global optimal correction parameters, which has great potential in reducing the radiometric differences between the images and realizing the radiometric correction of images. But a large number of unknown parameters to be solved reduces the solution efficiency of the radiometric correction model, especially when the amount of data increases sharply, this problem will become more prominent. The optimal path established based on the radiometric information of images overlapping area takes into account the radiometric conversion relationship between the images, can effectively control the error accumulation, and provide an idea for reducing the number of unknowns in the radiometric block adjustment. Therefore, this paper combines the radiometric block adjustment with the optimal path to reduce the number of unknowns, and improve the calculation efficiency of the correction model while ensuring the accuracy of radiometric correction, thereby improving the application potential of the radiometric block adjustment on large datasets.

Improved Mask R-CNN highway disease detection algorithm

SONG Weidong, BI Chunyang, ZHAO Fengshu

2023, 0(1):  58-64.  doi:10.13474/j.cnki.11-2246.2023.0010

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An improved Mask R-CNN highway disease detection algorithm (FAC-Mask R-CNN) is proposed to solve the problem of detection difficulty caused by road surface disease and low background pixel contrast. Based on ResNet101, a shallow feature expression with strong position information is added, and the adjacent feature maps are first fused as the final feature output of the backbone network. At the same time, the CBAM module is introduced to reduce the effect of low contrast between target and background pixels. Deep separable convolution and void convolution are used to replace the common convolution applied in backbone network and effective feature layer output process, respectively, which can improve the computational efficiency and mask prediction accuracy of the model. The average accuracy rate of FAC-Mask R-CNN on RDD(road disease datasets) is 89.86%, the recall rate is 88.54%, and the harmonic mean is 90%, which is 3.09% higher than that of Mask R-CNN algorithm. The results show that FAC-Mask R-CNN can effectively complete the task of fine detection and segmentation of road surface diseases.

Spatio-temporal difference analysis of carbon emissions in Chang-Zhu-Tan urban agglomeration based on multi-source remote sensing data

WANG Mengjie, WANG Yanjun, LI Shaochun, LIN Yunhao, TENG Fei, CAI Hengfan

2023, 0(1):  65-70.  doi:10.13474/j.cnki.11-2246.2023.0011

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The spatio-temporal distribution monitoring and evaluation of carbon emissions is one of the key research topics for sustainable urban development. For the analysis of the differences in the spatio-temporal distribution of carbon emissions in the Chang-Zhu-Tan urban agglomeration, this paper applies the NPP-VIIRS nighttime light images and impervious surface data, combined with county-level carbon emissions data to construct the carbon emission estimation model for the Chang-Zhu-Tan urban agglomeration, and analyzes the spatial and temporal distribution characteristics and changing trends of carbon emissions in this urban agglomeration. The results show that: ① The average and total value of nighttime lights and impervious surfaces data can better reflect the regional carbon emission level of the Chang-Zhu-Tan urban agglomeration.②From 2013 to 2017, the carbon emissions of the Chang-Zhu-Tan urban agglomeration were concentrated, mainly distributed in the middle area of the northern part. The carbon emissions areas expand year by year but the intensity weakened. ③ From 2013 to 2017, the changing trend of carbon emissions in the Chang-Zhu-Tan urban agglomeration was that the central area mainly has negative carbon emissions growth, while the peripheral areas have undertaken some carbon emissions. This study monitors the county-level carbon emissions of the Chang-Zhu-Tan urban agglomeration from 2013 to 2017 based on multi-source remote sensing data, and reveals the changes in the spatio-temporal distribution of carbon emissions, which can provide a scientific reference for carbon emission reduction and regional sustainable development.

Remote sensing diagnosis of ecological health in typical coal mining areas

CHEN Yiyu, CAO Chunxiang, XU Min, XIE Bo, ZHANG Jiutang

2023, 0(1):  71-76,94.  doi:10.13474/j.cnki.11-2246.2023.0012

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Coal resource is an important disposable energy source in China, and it is crucial to scientifically monitor and assess the ecological health of mining areas so as to maintain a balanced relationship between economic development and ecological health. In this study, three typical coal mining areas located in Shanxi province are selected. Landsat remote sensing data from 2001—2021 are used to analyze the multi-year land type evolution pattern of the open pit mining areas by visual interpretation. The greenness, humidity, dryness, and heat of the three typical mining areas are calculated, respectively. Then we construct a remote sensing ecological index(RSEI) of the mining areas based on the weight calculation method of knowledge granularity entropy, so as to complete the multi-year remote sensing diagnosis of mine ecological health. The results show that the two open-pit mines maintain reclamation while mining, and during half of the studying years their mean RSEI reach to 0.5. The underground mine area basically does not cause above-ground disturbance, and its ecological health is stable for many years. Its mean RSEI is around 0.7. In 2021, the mean RSEI values of the three mining areas are 0.53,0.48 and 0.70, respectively. This study improves the traditional remote sensing ecological index construction method, and provides scientific guidance for long time series ecological monitoring and remote sensing diagnosis of coal mining areas.

Application of UAV photogrammetry technology in emergency investigation of Aniangzhai landslide

CHEN Qiao, YUAN Feiyun, FU Xia, ZHANG Wenju, DONG Xiujun

2023, 0(1):  77-83,119.  doi:10.13474/j.cnki.11-2246.2023.0013

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UAV photogrammetry technology has the advantages of high data acquisition efficiency, fast response speed, and abundant and various results, and is gradually applied to emergency investigations of geological disasters. After the resurrection of the Aniangzhai landslide on June 18, 2020, UAV photogrammetry technology is used to conduct emergency investigations. For starters, the feasibility of the drone image-free photogrammetry technology of UAV is verified by checkpoint, and the software selection of rapid stitching and comprehensive processing of UAV image data is studied in a summary. The basic data such as 3D real model, digital surface model (DSM), orthophoto image (DOM) and dense point cloud are generated in the investigation area. Based on the processing and analysis of basic data, the rapid mapping of slide topography and the survey of landslide characteristics are completed, and the difference calculation of multi-phase high-precision UAV photogrammetry data is performed to identify areas with large landslide deformation and quantitatively characterize the landslides deformation characteristics, which provide guidance for the selection of monitoring equipment. With a maximum cumulative deformation of up to 16 m of monitoring on the landslide body,GNSS is effective to ensure the smooth implementation of disaster prevention and control projects by connecting the monitoring data of the professional monitoring equipment deployed on-site to the geological disaster real-time monitoring and early warning system.

Hyperspectral image classification based on superpixel graph convolution network

ZHANG Jiabao, XIE Fuding, JIN Cui

2023, 0(1):  84-87.  doi:10.13474/j.cnki.11-2246.2023.0014

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Hyperspectral image classification is an challenging problem in remote sensing. Hyperspectral image classification based on deep learning framework has attracted more and more attention due to its excellent classification performance. However, the common drawback of these methods is that the training of the model requires not only a lot of time, but also a large number of labeled samples. To address this issue, a superpixel graph convolution network-based hyperspectral image classification method is proposed. The method takes superpixels instead of pixels as nodes of graphs, which greatly reduces the graph size and improves the classification efficiency. The proposed superpixel merging and smoothing techniques effectively fuse spectral and spatial information and enhance the role of spatial information in classification. To validate the effectiveness of the proposed method, experiments are carried out on two real datasets, Indian Pines and Pavia University. Furthermore, the method is also compared with some advanced hyperspectral image classification methods based on deep learning framework. The results show that the proposed method is superior to other methods in classification accuracy and efficiency.

Real-time prediction of BDS-3 clock correction

LIU Duxue, HE Kaifei, YANG Jinquan, XU Xiang, LI Jiaxing

2023, 0(1):  88-94.  doi:10.13474/j.cnki.11-2246.2023.0015

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In the study of offshore precise dynamic positioning, the quality of BDS-3 correction information has a direct impact on the positioning results. This paper evaluates the quality of BDS-3 correction from the aspects of stability and accuracy. If BDS/GNSS fusion positioning mode is adopted, the communication cost of BDS-SMC is significantly higher. To solve this problem, this study proposes to use the clock correction prediction model for data compression, and analyze the structural characteristics of the clock correction, which is decomposed into the overall trend series and random fluctuation series, and then builds the prediction model respectively. The results show that DSC model is 6% higher than DLP model and 9% higher than DLP model in the 20 min prediction interval.

Noise reduction of Chan sequential adjustment combination algorithm in ultra wide band positioning

DONG Jiaqi, LIAN Zengzeng, XU Jingcheng, WEI Fengyuan

2023, 0(1):  95-100,140.  doi:10.13474/j.cnki.11-2246.2023.0016

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In the indoor environment, the distance between the receiver and the tag will be affected by random errors. Aiming at the positioning characteristics of the ultra wide band(UWB) system, combined with the advantages of the Chan algorithm and the sequential adjustmentalgorithm, a combined Chan sequential adjustment(Chan-SA) algorithm is proposed to reduce the influence of random errors in ranging. Firstly, the 3D coordinates of the label are obtained by the weighted least squares twice of the Chan algorithm, and then the coordinates are substituted into the sequential adjustment algorithm as the initial value, and the sequential adjustment algorithm is used to iterate the subsequent data to obtain the optimal solution. The calculation results of simulation data and field measurement data show that compared with the Chan algorithm, particle filter algorithm and sequential adjustment algorithm, in the static scene, the positioning accuracy of the Chan-SA algorithm is improved by 50.14%, 35.29% and 41.91%, respectively. The applicability of the proposed algorithm is also demonstrated in dynamic scenarios. Therefore, Chan-SA can improve the localization accuracy and robustness of UWB system.

Application of PS-InSAR method based on time series combination in surface deformation monitoring of Xiongxian county and its surrounding areas

TAO Wei, JIA Hongguo, KANG Miaohang, LIU Yuxin

2023, 0(1):  101-106.  doi:10.13474/j.cnki.11-2246.2023.0017

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This study proposes a PS-InSAR (TSC-PS-InSAR) monitoring method based on time series combination to extract the surface deformation information of Xiongxian county and suburb areas. Evaluation experiment results indicate that the proposed method can significantly increase the number of PS targets without prior model and the monitoring results are consistent to the deformation information extracted by StaMPS method in the settlement trend and settlement magnitud, which verify the reliability and feasibility of the proposed method. In addtion, according to monitoring results, the maximum annual subsidence rate of deformation area is -79 mm/a, which may be caused by groundwater overexploitation.

Study on forest fire simulation and collaborative fire-fighting based on parallel system

FENG Xiaogang, ZHOU Zaihui, YANG Xin, LI Meng, LI Fengxia

2023, 0(1):  107-112.  doi:10.13474/j.cnki.11-2246.2023.0018

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In order to provide scientific plan and accurate decision-making for forest fire based on spatio-temporal data. This paper proposes to simulate forest fire and its spread process by using particle system and Rothermel model based on parallel system and HLA. Based on the object class and interaction class design, the prototype system of simulation and collaborative drilling are developed, and the system is verified by taking Zhangpu county as an example. The results show that the introduction of parallel system and the coupling of spatio-temporal big data can well overcome the key disconnection between simulation and real-time scene. The introduction of measured emergency response module can provide high-precision information services for real-time fire extinguishing decision-making, which would be more applicability and generalization for the system of collaborative emergency simulation and drilling systems.

Analysis on spatio-temporal accessibility of medical services supported by real-time traffic data

XU Hao, QIAO Qinghua, LI Yanhong, CHEN Guoling, LIU Jia, GAN Lin

2023, 0(1):  113-119.  doi:10.13474/j.cnki.11-2246.2023.0019

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In view of the problem that the existing urban medical service accessibility analysis methods do not consider the medical preference,resulting in a large difference between the calculation results and the actual feelings of residents,this paper proposes a medical service spatio-temporal accessibility analysis method considering the medical time cost and distance cost preference,and takes the central urban area of Wuhan as an example. The experimental results show that research methods fully consider the impact of real traffic conditions on accessibility,and comprehensively consider the impact of traffic distance and travel time on residents' medical choice. At the same time,distance preference has a significant impact on the analysis results. When considering the actual road conditions,the accessibility shows a significant dynamic change trend in a day. On one hand,this method can reflect the difference of accessibility at different times. On the other hand,it emphasizes the preference of residents' time cost and distance cost. Compared with single time cost or distance cost,it has significant changes,and the analysis results are more in line with the reality.

High-precision sea-land surface temperature inversion over the Yellow River Delta with Sentinel-3

ZHANG Yun, LI Peng, LI Zhenhong, WANG Houjie

2023, 0(1):  120-126.  doi:10.13474/j.cnki.11-2246.2023.0020

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Land surface temperature (LST) and sea surface temperature (SST) are key parameters for understanding global change and human activities. However, the existing surface temperature products are usually discontinuous at the sea and land boundary. In this study, we use Sentinel-3 sea and land surface temperature radiometer (SLSTR) to measure continuous surface temperature product of land and sea over the Yellow River Delta (YRD) with split-window algorithms, while land surface emissivity can be estimated using NDVI threshold method. Compared with ground-truth observations and the fifth generation ECMWF reanalysis (ERA5) data, this method can obtain land and sea surface temperature inversion with high accuracy, whose RMSE is lower than 1.1 K. The results show that the accuracy of land and sea surface temperature inversion is higher than existing publicly available global products and can provide reference for global spatio-temporal continuous temperature inversion.

A method of extracting road intersections using low frequency trajectory data

CHEN Weiliang, DU Jiusheng

2023, 0(1):  127-133.  doi:10.13474/j.cnki.11-2246.2023.0021

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In order to extract urban road intersections using low-frequency trajectory data, this paper designs a precise identification method of road intersections based on data preprocessing and clustering algorithm. Firstly, combined with the characteristics of the trajectory data, a heuristic filtering algorithm is used to clean the original data and eliminate redundant points and abnormal points. Then, according to the running rules of vehicles, a step by step algorithm for extracting road intersections is proposed to calculate the characteristic points of suspected road intersections. Finally, hierarchical density clustering algorithm (HDBSCAN) is used to cluster the selected track points and extract the centroid, which is the intersection of the road. Based on the data source of taxi driving track in Chengdu, the results show that,the algorithm can extract the intersection with an accuracy of 95.33%, a recall of 82.11% and F value of 88.46%. It can effectively and accurately identify the urban road intersection information, and has a certain application value in urban administration and traffic planning.

Habitat suitability evaluation and corridor construction of budorcas taxicolor in Gaoligong mountain

FENG Hongneng, YANG Dehong, RAO Dingqi, WEI Xuan

2023, 0(1):  134-140.  doi:10.13474/j.cnki.11-2246.2023.0022

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Taking the budorcas taxicolor in Gaoligong mountain as research object, selecting eight influencing factors of the budorcas taxicolor which includes vegetation type, vegetation coverage, altitude, slope, water source, land cover, main roads and residential areas, based on GIS technology, and build resistance surface to detect the suitable habitat of budorcas taxicolor under the influence of multiple factors. The results show that the overall proportion of suitable habitats for budorcas taxicolor in the region is relatively small, and the suitable areas are mainly distributed in the central, western and southwestern regions of the study area, and are also scattered in the northern region. The migration of budorcas taxicolor is affected by human activities and road barriers, and its habitat has been destroyed to a certain extent. Combine with the distribution of budorcas taxicolor habitats and minimal cumulative resistance, build ecological corridors for budorcas taxicolor in the region, and the results show that: the corridors are mainly distributed in the southern section of Gaoligong mountain reserve, the middle section of Mabianwadi, Ziba, Eqiasadi, Mashidayaku, the northern section of Qiqi, Sikelovazu and Mudang area.

Prediction of grassland resource coverage in Jiangxi province using modified coverage slope osavi inversion method

CAO Qing'an, TU Liping, LENG Peng

2023, 0(1):  141-144.  doi:10.13474/j.cnki.11-2246.2023.0023

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The coverage of Jiangxi province's grassland resource coverage prediction based on the modified coverage slope OSAVI inversion method has a relatively direct representativeness in the grassland resource survey. At present, the coverage survey is mainly manual field survey. Aiming at the problems of large regional field survey investment and long cycle, this paper uses the coverage data of Landsat 8, ASTER GDEM images, grassland map spots in the geographical national conditions census and 134 field sample survey data as the data source.Through the extraction of slope data, the coverage survey data of 74 field sample points and the optimized soil regulated vegetation index (OSAVI), the relevant model is established, and the coverage of grassland resources in the study area is inversed to form the distribution map of the gray value of grassland coverage in the whole region. The error analysis of 60 field survey sample plots' coverage and inversion coverage shows that the inversion coverage is highly consistent with the field coverage.

Field road recognition method based on high-resolution remote sensing image

YUAN Cuixia, REN Yanmin, HAN Zhiqiang, LIU Yu, LI Shuhua

2023, 0(1):  145-148.  doi:10.13474/j.cnki.11-2246.2023.0024

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Field road is an important project for farmland construction and management,and its direction,width and accessibility directly affect the convenience of farmland cultivation.Therefore,accurate identification of field road is of great significance for evaluation of farmland construction effect.With the help of high-resolution images,this paper adopts object-oriented method to identify the road based on the idea of hierarchical classification.Then,tensor voting method,eight-neighborhood breakpoint detection and morphological algorithm are introduced to repair the breakpoints.Take Dingzhou city,Hebei province as an example,the result of field road recognition is obtained,and the integrity rate,accuracy rate and quality of field road identification are 91%,74% and 69%,respectively.

Application of indoor mobile measurement system in new basic surveying and mapping

YANG Zhen, MENG Xiangwu, TANG Shunjun, WANG Hao, GONG Yinxi

2023, 0(1):  149-153.  doi:10.13474/j.cnki.11-2246.2023.0025

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The indoor mobile measurement system plays an important role in the spatial entity construction of the new basic surveying and mapping system in Beijing. This paper proposes the technical framework of the indoor mobile measurement system in the spatial entity construction of the new basic surveying and mapping system, which includes indoor external data collection, processing procedures and methods, multi-source point cloud data splicing and fusion and integrated point cloud and panoramic image data application in all-element 3D modeling. NavVis M6 indoor mobile measurement system is used as the experimental equipment, and Huairou district is selected The area of BBMG cement plant is a pilot area for the development of Beijing's new basic surveying and mapping. The experimental results show that the operation process of the indoor mobile surveying system proposed in this paper can meet the needs of the spatial entity construction of the new basic surveying and mapping system.

A laser calibration evaluation method of high-precision map acquisition system

SUN Li

2023, 0(1):  154-157,178.  doi:10.13474/j.cnki.11-2246.2023.0026

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The commonly used laser calibration evaluation method is to use the distance error of the correspondence points in calibration field. The error in the selection process has a great impact on the evaluation result. It cannot be ignored in high-precision laser calibration. This paper designs the use of correspondence surfaces to evaluate the calibration of the laser, using the control points and the static laser construction calibration field as the true value, extracts the correspondence surfaces from the laser point cloud to be evaluated.The error between the two correspondence surfaces is used to evaluate the calibration accuracy of the laser. The laser calibration accuracy evaluation solution has been applied to the AutoNavi high-precision acquisition system, and has been put into production for more than 2 years. The relative accuracy of 98% features made from laser cloud reached 10 cm.

Uniform light and color algorithm for urban-level UAV remote sensing images

YANG Ting, WU Hao, LI Yan

2023, 0(1):  158-162.  doi:10.13474/j.cnki.11-2246.2023.0027

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Due to the influence of various factors such as sensor factors, weather factors, human factors, et al, the images obtained by UAVs have uneven distribution of brightness and hue in different degrees during acquisition. The image is processed with uniform light and color. In this study, two color-leveling algorithms are proposed, the mean algorithm and the parameter algorithm based on the camera response function. The algorithms are implemented through Python language programming, which are applied to the UAV images of the real 3D data construction area in Zhenjiang city, and the experimental results are evaluated and analyzed. Experiments show that both algorithms can better remove chromatic aberration, make the tone transition more gentle, and optimize the effect of the 3D scene in the later stage.

Research and application of intelligent verification technology for authenticity of homestead reclamation project based on deep learning

XIANG Yu, HUANG Zhi, HUA Yuanyuan, DENG Jianfeng

2023, 0(1):  163-167.  doi:10.13474/j.cnki.11-2246.2023.0028

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The review of homestead reclamation project under the background of region-wide comprehensive renovation is an effective means to ensure the legality and compliance of the reclamation project. Aiming at the low review efficiency of the current homestead reclamation project, a authenticity review method of rural homestead reclamation project was proposed based on remote sensing images. Taking the rural housing land reclamation project in Chongqing as an example, the paper establishes the authenticity review model of housing land reclamation project, and uses the improved U-Net to accurately extract buildings, and then superimpose with the reclamation red line to realize the intelligent authenticity review of the housing land reclamation project. The experimental results show that this method can quickly and accurately examine the authenticity of residential land reclamation projects, which is of great significance to optimize land structure, promote land circulation and promote rural revitalization. It can provide technical reference for the authenticity examination of residential land reclamation projects under the background of regional comprehensive renovation.

Application of oceanographic survey technology in underwater detection to convey tunnel inlet

ZHOU Xiaorong, SHEN Yongfang, CHENG Zhuo, WANG Zhaowei, ZHANG Deguan

2023, 0(1):  168-172.  doi:10.13474/j.cnki.11-2246.2023.0029

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In this paper, the underwater detection to convey tunnel inlet after blasting construction is taken as an example, comprehensive using of multiple-beam sonar, underwater robot, color image sonar and other combined acoustic and optical oceanographic survey technology, to obtain high precision, full coverage and high time efficiency measurement data of water inlet. The results show that, the multi-beam sonar scanning reaches the resolution of 1.25 cm, detecting shape and size of the tunnel, plane position, elevation and surrounding rock slope with high precision. Underwater robot could go deep into complex underwater environment, carried the color image sonar scanning could fit the shape of tunnel inlet rock plug section, lock section and slag pit. High-definition underwater video showed the lining quality of tunnel inlet body and accumulation of blocks and stones in the slag pit after blasting. This technology realizes the safe, efficient and full coverage detection of underwater tunnel in complex environment, and could be used as reference for relevant underwater engineering.

Monitoring of surface deformation characteristics in Xi'an based on SBAS-InSAR technology

WANG Runze, FEI Min, LIANG Shichuan, XUE Haowei, LOU Xiao

2023, 0(1):  173-178.  doi:10.13474/j.cnki.11-2246.2023.0030

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Land subsidence is one of the most serious geological disasters in Xi'an city.In this paper, 36 Sentinel-1A images of Xi'an city from 2018 to 2021 are processed based on SBAS-InSAR technology to obtain the latest surface deformation characteristics of Xi'an city and analyze its causes.The results show that:① the main surface deformation areas in xi'an city from 2018 to 2021 are Yuhuazhai area, electronic city area, Sanyao-Fengqiyuan area and southern part of city wall area. ② The Yuhuazhai and Yuecheng areas have been uplifted, while the southern part of the city wall has been uplifted, and the Sanyao-Fengqiyuan area still shows a downward trend. ③ The surface deformation of Xi'an city is mainly affected by confined water mining and recharge, and the distribution and trend of surface deformation are significantly affected by ground cracks, and the building load also has a certain influence on the surface deformation.

Application of laser scanning and UAV air-ground integrated measurement

DING Zhiguang, RAO Shuaixiong, WANG Tianfang, ZHU Jiongzhai

2023, 0(1):  179-183.  doi:10.13474/j.cnki.11-2246.2023.0031

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Surveying and mapping is an important part of the construction of projects, which runs through the entire life cycle of the entire project construction from planning, design, construction and completion. In recent years, engineering has begun to consider the whole process of using digital twins for project management applications.Traditional measurement methods have the defects of need long work time and single results,and it's difficult to visualize. In this paper, Trimble SX10 3D image laser scanner and UAV are used for air-ground integrated measurement, the corresponding technical methods and processes are summarized, which not only shortens the mapping cycle compared with traditional measurement methods, and the problem of night optical mapping is soved, but also the results can be digitally visualized.