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Integration of InSAR and airborne LiDAR technologies for early landslide identification and analysis ZHENG Wei, ZUO Xiaoqing, LI Yongfa, LI Zhenghui, WANG Zhihong, LI Debin Bulletin of Surveying and Mapping    2024, 0 (5): 1-6.   DOI: 10.13474/j.cnki.11-2246.2024.0501 Abstract （67）   HTML （13）    PDF（pc） （12677KB）（84）       Knowledge map    Save The insufficiency in the accuracy and dependability of early landslide identification in densely vegetated complex mountainous areas is tackled in this paper. A method for early landslide identification analysis is suggested, which combines the micro-topographic features from LiDAR data and the deformation characteristics from InSAR technology. Initially, the SBAS-InSAR technique is used to extract the temporal deformation information of the region, confirming the abnormal distribution range of deformation rates. Subsequently,leveraging the advantages of airborne radar in high-precision terrain and landform data, seven potential landslides within the main area are identified, and landslide maps along with the boundaries of potential landslides are delineated. Finally, the identification results are validated through optical image remote sensing and geometric distortion principles. The results demonstrate that the combination of InSAR and airborne LiDAR technologies can enhance the accuracy and detection capabilities of landslide identification. The developmental characteristics of landslides and the identification results provide theoretical support and a basis for the prevention of geological disasters and the cataloging of landslides in the Wenshan region. Reference | Related Articles | Metrics

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A combined method of PCA and IR-MAD for detecting rainfall landslide ZHAO Qiong, ZHANG Jinshui, ZHENG Wenwu Bulletin of Surveying and Mapping    2024, 0 (5): 7-11,18.   DOI: 10.13474/j.cnki.11-2246.2024.0502 Abstract （33）      PDF（pc） （28368KB）（56）       Knowledge map    Save Seasonal patterns of torrential rainfall is one of the primary triggering agents which predisposes to catastrophic landslides, especially in the complex terrain medium-elevation mountains and hilly of China. The geographic scene resulted in landslide occurrence is very complex. Therefore, exploring the landslide detection methods in complex situations has important significance for damage assessment and post-disaster emergency investigation. In this paper, we propose a landslide detection method combining PCA and IR-MAD to realize the accurate extraction of nascent landslide.The research results show that compared with the existing methods, the proposed method effectively inhibits the disturbance of landslide detection caused by seasonal factors such as crop seeding and harvest, flood season caused by heavy rainfall, and other similar remote sensing features of bare land and tidal flat. The accuracy rate of landslide detection and the stability of landslide identification model have been improved to a certain extent. Reference | Related Articles | Metrics

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A fine extraction method for tidal channels with fully polarized SAR and optical remote sensing LI Shu, LI Peng, LI Zhenhong, WANG Houjie Bulletin of Surveying and Mapping    2024, 0 (5): 29-34,40.   DOI: 10.13474/j.cnki.11-2246.2024.0506 Abstract （38）   HTML （2）    PDF（pc） （7645KB）（54）       Knowledge map    Save The tidal channel system is the most active geomorphic unit in the chalky-silt tidal flats. Due to the influence of periodic tidal erosion, human activities, and sea level rise, it is challenging to monitor tidal channel in a large scale. In this study, a method of tidal channel detection and extraction based on C-band GF-3 fully polarized synthetic aperture radar (SAR) and PlanetScope multispectral remote sensing data is proposed. Through the fusion of spectral, index, polarization, texture and other features, the optimal feature set was constructed, and the maximum likelihood method, support vector machine and random forest algorithm were combined to carry out synergetic classification, and the fine distribution information of the tidal channel at the Yellow River estuary with 3m resolution was obtained. The results show that the overall accuracy of the method is 99%, F1 value is 0.98, and the extraction result is better than that of a single data source. This study is expected to provide a cost-effective alternative for the tidal channel mapping in estuarine and coastal areas, and help to quantitatively describe the morphological evolution, stability and driving factors. Reference | Related Articles | Metrics

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Study on sample unbalance in landslide recognition algorithm based on depth learning WANG Lixia, XI Wenfei, SHI Zhengtao, ZHAO Zilong, QIAN Tanghui, ZHAO Lei, MA Yijie Bulletin of Surveying and Mapping    2024, 0 (5): 12-18.   DOI: 10.13474/j.cnki.11-2246.2024.0503 Abstract （30）      PDF（pc） （6696KB）（46）       Knowledge map    Save Landslides are a common geological disaster that can cause significant property losses and casualties to natural ecosystems and humans once they occur. How to quickly and accurately obtain landslide information is crucial to disaster prevention and mitigation. Traditional deep learning methods depend heavily on the quality of landslide samples, but the quality of existing samples is uneven, and the impact of landslide sample imbalance on the performance of deep learning models is rarely considered. Aiming at the problem of how to improve model accuracy by improving sample quality, this paper proposes a Faster R-CNN landslide target detection method based on multi-source unbalanced samples starting from sample quality. By conducting integrated training on a variety of imbalanced samples, the impact of different samples on the comprehensive performance of the model is studied. The results show that:①The accuracy rate of the model is 85.16%, F1 score of 0.69, precision of 56.96%, recall of 86.58%, and the missed detection rate is 0.33 under the imbalance of difficult samples. After strengthening the sample quality, the accuracy rate increases by 2.04%. The precision increased by 4.29%, the recall rate increased by 1.71%, and the missed detection rate decreased by 0.04. ②Under the imbalance of positive and negative samples, the accuracy rate of the model is 96.03%, F1 score of 0.78, precision of 64.50%, recall of 97.15%, and the missed detection rate is 0.09. After adding difficult samples to participate in the training, the accuracy rate drops by 8.45%. The rate dropped by 6.93%, the recall rate dropped by 7.25%, and the missed detection rate increased by 0.18. Difficult samples have a greater impact on the overall performance of the model. By improving the quality of these samples, the model detection accuracy can be improved. Therefore, the method proposed in this article provides a reference for solving the problem of landslide data sample imbalance in deep learning. Reference | Related Articles | Metrics

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Bathymetric inversion model for fusion of heterogeneous satellite remote sensing data GUO Songtao, XING Shuai, ZHANG Guoping, KONG Ruiyao, CHEN Li Bulletin of Surveying and Mapping    2024, 0 (5): 19-23.   DOI: 10.13474/j.cnki.11-2246.2024.0504 Abstract （43）   HTML （4）    PDF（pc） （4157KB）（43）       Knowledge map    Save To investigate the impact of image resolution and bathymetry models on the fusion of heterogeneous satellite data for depth inversion, this study integrates ICESat-2 laser altimetry data with multi-temporal Landsat 8, Sentinel-2, and WorldView-3 satellite data. Depth inversion is performed using logarithmic ratio model, multi-band model, BP neural network, support vector machine, random forest, and extreme gradient boosting. Experimental results show that the spatial resolution of the images has an insignificant effect on the accuracy of depth inversion. Considering both the accuracy and resolution of the inversion results, Sentinel-2 satellite data performs the best. Moreover, the XGBoost model outperforms other models in terms of inversion performance, achieving an optimal RMSE of 0.51 meters in the Dongsha Atoll experimental area. These results provide valuable reference for coastal depth measurement based on the fusion of heterogeneous remote sensing satellite data. Reference | Related Articles | Metrics

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Progress and perspectives of urban functional region identification CHENG Penggen, QI Guangyu, ZHONG Yanfei Bulletin of Surveying and Mapping    2024, 0 (5): 90-95.   DOI: 10.13474/j.cnki.11-2246.2024.0516 Abstract （28）      PDF（pc） （2305KB）（37）       Knowledge map    Save With the rapid development of the economy and society, the urban development boundary has rapidly spread from the center to the outside. Identifying urban functional areas can provide reference basis for urban construction and planning, and it is of great significance for the rational allocation and utilization of urban space and resources. Based on the literature review of urban functional area division and identification at home and abroad, this article summarizes the research status of urban functional area identification. Firstly, various data sources used for urban functional area identification are introduced, and their advantages and disadvantages are analyzed and compared. Secondly, it summarizes four types of method for urban functional area identification, focuses on analyzing the application of deep learning methods in urban functional area identification, and conducts case analysis and comparison to illustrate the effectiveness of different data sources and methods for urban functional area identification. Finally, the problems and research trends in the field of urban functional area division and identification are pointed out. Reference | Related Articles | Metrics

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Exploration and practice of reforming innovation education for geographic information science specialty in the big data era SHI Yan, DENG Min, LIU Baoju, CHEN Bingrong Bulletin of Surveying and Mapping    2024, 0 (4): 179-182.   DOI: 10.13474/j.cnki.11-2246.2024.0431 Abstract （51）      PDF（pc） （1444KB）（62）       Knowledge map    Save Big data brings new opportunities and challenges for college professional innovation education in the new era. Taking the geographic information science specialty as an example, this paper systematically analyzed and summarized the current situation of college innovation education in our country and the main challenges it is facing. We made an exploration and practice for the reform of innovation education for geographic information science specialty in the big data era, and proposed new reform measures based on the permeation of innovation idea, the raising of innovation awareness, the training of innovation thinking and the evaluation of innovation ability. These measures can provide references for the comprehensive construction of college innovation education system. Reference | Related Articles | Metrics

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High-precision 3D modeling technology of urban real scene based on NeRF SUN Jianhua, LI Wei, YUAN Weizhe, WANG Feng, GU Jiaming Bulletin of Surveying and Mapping    2024, 0 (4): 129-134.   DOI: 10.13474/j.cnki.11-2246.2024.0422 Abstract （99）      PDF（pc） （6094KB）（91）       Knowledge map    Save In order to better apply NeRF high-precision 3D modeling in the 3D digital reconstruction of urban real scenes,this paper divides the large scene into sub-NeRF based on NeRF technology,and initializes the polygon mesh by constructing multiple octahedral bodies in the scene. And the vertices of the polygon faces are continuously optimized during the training process. After the training is completed,the weights of the encoder-decoder network are obtained,and different levels of polygon mesh refinement are performed on each independent block through vertex optimization. From satellite-level images that capture city overviews to ground-level images that show complex details of buildings,multi-scale data for urban detail and spatial coverage are constructed through progressive learning. The neural network voxel rendering model uses a multilayer perceptron (MLP) to realize the parameterization of volume density and color,and uses a hierarchical sampling method to realize the sorting distance vector of rays between the near plane and the far plane of a predefined viewing angle,so as to realize real-time interactive rendering of large-scale scenes. Then,GIS and NeRF are fused to provide a new solution for tasks such as multi-data fusion,query,analysis,measurement,annotation and sharing,so as to achieve instant and smooth dragging,zooming and 360° browsing and viewing of scenes without dead ends. This fusion makes it easy to integrate various data sources for spatial analysis in 3D scenarios such as urban planning,land management and environmental monitoring. Reference | Related Articles | Metrics

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Analysis of the effects of UAV-borne LiDAR point cloud density on DEM accuracy XIAO Jie Bulletin of Surveying and Mapping    2024, 0 (4): 35-40.   DOI: 10.13474/j.cnki.11-2246.2024.0407 Abstract （100）      PDF（pc） （5613KB）（146）       Knowledge map    Save UAV-borne LiDAR point cloud data is an important data source for producing DEM. In order to further improve DEM production efficiency,selecting flat terrain and mountainous terrain as test areas,the ground point cloud,which is processed by filtering method,is thinned and simplified according to the a lgorithm based on TIN with seven different the ground point cloud retention rate of 80%,60%,40%,and so on,and the corresponding DEM is generated and its accuracy is evaluated by mean error (ME),standard deviation (SD),and root mean square error (RMSE). The results show that: ①The accuracy of the produced 0.5 m grid-spacing DEM could exceed 0.05 m when the ground point cloud density reached 2 points/m 2 for flat terrain and 9 points/m 2 for mountainous terrain. ②As the density of ground point cloud increases,the DEM accuracy level gradually stabilizes,and the DEM accuracy would decrease rapidly when the ground point cloud density is thinned to 1 point/m 2. For the DEM production tasks in large regions using UAV-borne LiDAR point cloud data,the conclusions of this research have a certain guiding and reference significance in reducing data acquisition costs and improving DEM production efficiency. Reference | Related Articles | Metrics

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Application experiment and analysis of high-precision engineering surveying network for BDS-3+BDS-2 dual-frequency data ZHOU Mingduan, BAI Yansong, JI Xu, XU Xiang, CUI Likun, XIE Qianlong Bulletin of Surveying and Mapping    2024, 0 (5): 60-65.   DOI: 10.13474/j.cnki.11-2246.2024.0511 Abstract （35）      PDF（pc） （1321KB）（33）       Knowledge map    Save Aiming at the current stage of BeiDou system in BDS-3+BDS-2 hybrid service, this paper analyzes the data processing model of BDS network, and establishes a kind of high-precision engineering surveying network based on BDS-3+BDS-2 dual-frequency data for the application test. Four CORS stations that simultaneously support BDS-3+BDS-2 and GPS dual-frequency data are selected to lay high-precision engineering surveying network for data processing, and comparative analysis and evaluation are carried out in terms of the accuracy of phase observation values, standardized root-mean-square error after checking, quality of baseline vectors, repeatability of the baseline, and results of the net adjustment point coordinates. The experimental results show that: using the B1I and B3I dual-frequency data of BDS-3+BDS-2 to establish a high-precision engineering surveying network, the results of the obtained point coordinates are millimeter lever in horizontal direction and millimeter to decimeter level in vertical direction different from the corresponding results of the L1 and L2 dual-frequency data of GPS, which is effective to be applied to the high-precision engineering surveying network. Reference | Related Articles | Metrics

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Road extraction of UAV remote sensing image based on deep learning ZHANG Wei, ZHANG Chaolong, WANG Benlin, CAI Anning Bulletin of Surveying and Mapping    2024, 0 (6): 77-81.   DOI: 10.13474/j.cnki.11-2246.2024.0614 Abstract （33）      PDF（pc） （1821KB）（33）       Knowledge map    Save Aiming at the problems of high-resolution remote sensing images and road image datasets in the target scene in terms of difficulty in acquiring, high cost, etc., we explore the optimal image resolution of the network models to perform the extraction task at different scales, evaluate the applicability and reliability of each model on road extraction, and provide methodological reference and case study for the road recognition project. In this paper, three classical network models in the field of image segmentation are introduced, the models are trained using public datasets, and the unmanned aerial images of Chuzhou city, Anhui province are used as the test data to perform the road extraction work at different scales, to find out the optimal resolution and model applicability of each model in the new scene, and to evaluate the reliability. The experimental results show that the applicability of the D-LinkNet network model is more prominent in the road extraction task at different scales, the reliability of the DeepLabV3+ network model is poorer, and the optimal resolutions of the road extraction input images for the U-Net and D-LinkNet network models are 1.0 and 0.5 m, respectively. Reference | Related Articles | Metrics

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LiDAR point cloud registration with improved ICP algorithm XU Zhe, DONG Linxiao, WU Jiayue Bulletin of Surveying and Mapping    2024, 0 (4): 1-5.   DOI: 10.13474/j.cnki.11-2246.2024.0401 Abstract （199）      PDF（pc） （3266KB）（192）       Knowledge map    Save The traditional ICP algorithm has long matching time and is affected by initial values in LiDAR target point cloud matching, which leads to low positioning accuracy and poor robustness when applied to unmanned vehicle SLAM technology. Proposes an NDT-ICP algorithm that combines the KD-tree algorithm. Firstly, voxel grid filtering is used to preprocess the point cloud data obtained from LiDAR, and the method of plane fitting parameters is used to remove point cloud of ground. Secondly, use NDT algorithm for point cloud coarse matching to shorten the distance between the target point cloud and the point cloud to be matched. Finally, the KD-tree proximity search method is used to improve the speed of corresponding point search, and the precise matching of the ICP algorithm is completed by optimizing the convergence threshold. Through experiments, it has been shown that the improved algorithm proposed in this article has significantly improved speed and accuracy in point cloud matching compared to NDT and ICP algorithms, and has better accuracy and robustness in map construction. Reference | Related Articles | Metrics

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Comparison of handheld LiDAR point cloud filtering methods for complex mountain microtopography XU Yajing, YUAN Xiping, GAN Shu, LI Raobo, YE Junmin Bulletin of Surveying and Mapping    2024, 0 (5): 24-28.   DOI: 10.13474/j.cnki.11-2246.2024.0505 Abstract （34）      PDF（pc） （4229KB）（31）       Knowledge map    Save In this paper,a typical use case of hand-held laser point cloud data for measuring soil erosion and surface erosion in complex mountainous areas is presented,the performance of delta filter algorithm,slope filter algorithm and cloth simulation filter algorithm in point cloud classification of ground-based LiDAR is compared and analyzed. In order to obtain the highest performance,the parameters corresponding to three kinds of filters are used to test the test data set,and the optimal filtering of each algorithm is obtained through comparative analysis,the experimental results show that for smooth bare landform filtering,cloth simulation filtering is the best,progressive densification triangle filtering is the second,and slope filtering algorithm is the worst,the progressive encrypted triangle filter algorithm has the best filtering effect,the cloth simulation filter is the second,and the slope filter algorithm has the worst filtering effect. The experimental results provide valuable information for optimizing the parameters of the filtering algorithm to improve its performance in detecting micro-terrain changes,and verify the effectiveness of the progressive encrypted triangle filter in complex areas. Reference | Related Articles | Metrics

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Remote sensing monitoring and influencing factors analysis of grassland degradation in Xinjiang from 2001 to 2020 MA Lisha, ZHENG Jianghua, PENG Jian, LI Gangyong, HAN Wanqiang, LIU Liang Bulletin of Surveying and Mapping    2024, 0 (6): 1-7.   DOI: 10.13474/j.cnki.11-2246.2024.0601 Abstract （38）   HTML （5）    PDF（pc） （8662KB）（31）       Knowledge map    Save Due to climate change, overgrazing and overcultivation, grassland degradation and other ecological problems in Xinjiang have attracted increasing attention. In this study, MODIS NDVI remote sensing data products are used to monitor and analyze the grassland status in Xinjiang from 2001 to 2020. The pixel binary model, grassland degradation index based on coverage change, cold/hot spot analysis and other methods are used to obtain the temporal and spatial characteristics of grassland degradation in Xinjiang according to the national standard of grassland degradation grade classification, and then the influencing factors are analyzed. The results show that:①the coverage of grassland in Xinjiang is increasing with a main variation degree of stability (55.4%), and the distribution shows a gradually decreasing trend from north to south.②In the past 20 years, the degradation level of grassland coverage in Xinjiang was in a state of moderate to mild degradation, with the north mainly in an undegraded or mildly degraded state, while the east and south were mainly in a state of mild to moderate degradation, and the grassland was in a recovering trend during different study periods.③The grassland degradation index in Xinjiang shows an overall downward trend, increasing first and then decreasing in northern Xinjiang, decreasing continuously in eastern Xinjiang, and slightly increasing in southern Xinjiang. The cold/hot pattern shows that the cold spot increases and the hot spot decreases. It means, grassland degradation has weakened and is gradually recovering.④The grassland type caused by human activities is mainly transformed into bare land and farmland, and the grassland area decreases by 1.676 million hm 2. The temperature shows a mean temperature inhibition, a high-temperature promotion, and a low-temperature inhibition effect on the grass coverage.Precipitation has a promoting effect on grassland coverage.The results of this study can provide targeted guidance for the degradation of grassland in Xinjiang at the regional scale and provide a decision-making basis for the protection and restoration of the ecological environment. Reference | Related Articles | Metrics

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A method for constructing true 3D models of complex scenes based on multi-source spatial data ZHOU Baoxing, WANG Bing, ZHANG Hangfan, MA Dengyue, LIU Xizhu Bulletin of Surveying and Mapping    2024, 0 (4): 13-17.   DOI: 10.13474/j.cnki.11-2246.2024.0403 Abstract （99）      PDF（pc） （11003KB）（156）       Knowledge map    Save The 3D models of cities have been widely applied in various fields such as urban construction and social services. In order to rapidly and accurately construct 3D city models to meet the needs of urban detailed planning and management,this article focuses on the main theme of fast,reasonable,and precise construction of true 3D models,with city terrain and urban features as the research objects. It proposes a fast construction solution for city 3D models,starting from terrain to features,and from rough to precise. It realizes the rapid modeling of urban basic terrain,buildings,and other 3D scenes. The proposed modeling approach is specifically implemented using the Skyline platform,forming a complete operating process. Reference | Related Articles | Metrics

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An approach for extracting BIM component instance information integrating IFC semantic data and geometric similarity HE Biao, TANG Aowei, KUAI Xi, XU Hai, XIAO Jiadong Bulletin of Surveying and Mapping    2024, 0 (5): 96-102.   DOI: 10.13474/j.cnki.11-2246.2024.0517 Abstract （30）   HTML （2）    PDF（pc） （2736KB）（29）       Knowledge map    Save Building information modeling (BIM) accurately captures architectural structures,component compositions,and semantic attributes. It plays a crucial role in the digital management of smart cities' spatiotemporal frameworks and the entire building lifecycle,including planning,construction,maintenance,and operation. However,the massive data scale,complex reference relationships,and hierarchical structures of BIM models present challenges in extracting component instance information,hindering lightweight data transmission,seamless visualization,and BIM analysis within current city information modeling (CIM) platforms.To address this issue,we introduce an innovative approach that combines IFC semantics with geometric similarity. Utilizing ICP and the Hausdorff distance metric,we attain a high level of precision in extracting BIM component instances. Furthermore,we present a specialized method tailored to the extraction of common extruded components. Our comprehensive evaluation,encompassing five diverse BIM disciplines,demonstrates exceptional results,including a 29.79% reduction in file sizes,a 79.41% component instantiation rate,and a 22.47% solid compression rate. Impressively,each instantiated component encompasses an average of 49.24 sub-components. Our method excels in extracting IFC-based BIM component instances,facilitating the efficient transformation of extensive models. Reference | Related Articles | Metrics

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Research on groundwater storage and surface subsidence in Huangshui Valley based on GRACE and Sentinel-1A HU Xiangxiang, KE Fuyang, SHI Yaya, WU Tao, LIU Baokang, PANG Dongdong, ZHANG Lili, SONG Bao Bulletin of Surveying and Mapping    2024, 0 (6): 46-52.   DOI: 10.13474/j.cnki.11-2246.2024.0609 Abstract （34）      PDF（pc） （8288KB）（28）       Knowledge map    Save GRACE/GRACE-FO and GLDAS data are used to invert the groundwater changes in 2019—2022 in Huangshuang Valley area. And SBAS-InSAR technology is used to obtain the simultaneous rate of surface subsidence in the region, which is combined with the precipitation data to study the correlation between surface subsidence and groundwater changes in Huangshuang Valley area. The results show that: ① The overall direction of groundwater loss in Huangshui Valley is from northwest to southeast. ②Groundwater changes have a greater impact on the more serious surface deformation in the region. ③The greater the surface deformation (uplift), the more groundwater reserves are lost. The upper reaches of the Yellow River have the greatest uplift, and the loss of groundwater reserves is the greatest. ④ The surface deformation in the northern part of the Huanghe Valley is not sensitive to changes in groundwater reserves, while the surface deformation in the southern part is more sensitive to changes in groundwater reserves. The conclusions of this paper can provide important scientific reference for local geological disaster warning, sustainable utilization of water resources, ecological protection and high-quality green development. Reference | Related Articles | Metrics

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Assessment of cultivated land use change in Guilin using the GeoSOS-FLUS model NI Chunyu, HE Wen, YAO Yuefeng Bulletin of Surveying and Mapping    2024, 0 (5): 35-40.   DOI: 10.13474/j.cnki.11-2246.2024.0507 Abstract （32）      PDF（pc） （2465KB）（27）       Knowledge map    Save Information of spatiotemporal change in cultivated land and its future trends is an essential component for effective land use management. Here, we explore the spatiotemporal change pattern of cultivated land in Guilin with multi-temporal Landsat remote sensing images based on the Google Earth Engine (GEE) cloud platform. Firstly, we comprehensively evaluate five classification methods for their suitability in classifying land use in Guilin. Secondly, we analyze the land use changes, especially the spatiotemporal change pattern of cultivated land from 2000 to 2020. Furthermore, we simulate and predict change in cultivated land under different scenarios in 2030 using the GeoSOS-FLUS model. The results show that the random forest (RF) algorithm demonstrate the highest overall accuracy and Kappa coefficient for land use classification in Guilin. There was a continuous decrease in cultivated land area during 2000 to 2020, with the most pronounced decline observed between 2010 and 2015. Cultivated land was mainly converted to construction land and forests.The Grain for Green Program, the rapid expansion of tourism, and an increase in construction land are the key factors that impact the spatiotemporal change patterns of cultivated land.Under the natural development scenario, it is anticipated that the cultivated land will continue to decrease significantly, while construction land will expanse in 2030. This will have adverse impacts on the ecological environment.Under both the cultivated land protection and ecological control scenarios, an increase in cultivated land area is anticipated. Increase in cultivated land and optimization other land use types will have significant importance for safeguarding food security, promoting the sustainable development of tourism, and ensuring ecosystem stability in Guilin. Reference | Related Articles | Metrics

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Key technologies of point cloud processing for light and small airborne LiDAR HUANG Jiangxiong, CAO Qian, HU Xiang, CHEN Xiaojun Bulletin of Surveying and Mapping    2024, 0 (5): 115-120.   DOI: 10.13474/j.cnki.11-2246.2024.0520 Abstract （35）      PDF（pc） （3602KB）（27）       Knowledge map    Save Aiming at the problem that the elevation accuracy of light and small airborne LiDAR point cloud data is difficult to meet the production requirements of 1∶500 large-scale topographic maps, this paper adopts a new hierarchical multi-model combined filtering method to classify and extract ground points. This paper systematically introduces the measurement principle of airborne LiDAR, the collection and processing methods of point cloud data, and focuses on the classification and extraction methods of ground points according to the characteristics of light and small LiDAR, such as large thickness of point cloud data and few ground points in dense vegetation areas. The new combination of multiple filtering models can effectively improve the elevation accuracy of ground points after classification. After resampling the ground points, the elevation points are extracted and used to draw contour lines of topographic maps. This method perfectly takes into account the accuracy and aesthetics of contour lines. Reference | Related Articles | Metrics

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Monitoring of early identification and ground deformation characteristics of coal mining subsidence area based on multi-data source:taking Daliuta Town of Shenmu city as an example ZENG Guang, ZHANG Pengfei, WANG Haiheng, WANG Yao Bulletin of Surveying and Mapping    2024, 0 (5): 121-126.   DOI: 10.13474/j.cnki.11-2246.2024.0521 Abstract （44）      PDF（pc） （7722KB）（27）       Knowledge map    Save The ecological environment problems in coal mining areas have been paid more and more attention by the society. How to realize the accurate, efficient and economical early identification and dynamic monitoring of coal mining subsidence areas is particularly urgent. Based on the data collection and analysis, this paper uses the DEM data of 5 periods from 2000 to 2022 for differential decomposition calculation, and uses 164 long-term series Sentinel-1 data from June 15,2015 to July 15,2023 to dynamically monitor the land subsidence in the coal mining area. The current distribution and land subsidence characteristics of the coal mining subsidence area in Daliuta town, Shenmu city are identified, and a set of early identification methods of coal mining subsidence area based on multi-data sources is formed. The results show that:①The distribution area of coal mining subsidence area in Daliuta town is 252.70km 2, including two types of ground collapse and goaf suspended roof. The coal mining subsidence problems in Shigetai, Halagou, Daliuta and Huojitu mining areas of Shenhua company are serious.②The DEM data with a resolution of 2m is resampled to 5m and then the difference operation is performed. The error is 0.01m, and the accuracy is high and the calculation is efficient. ③DEM difference decomposition and SBAS-InSAR technology can accurately identify the range of ground collapse with high matching degree, and each method complements and confirms each other. Reference | Related Articles | Metrics

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Development for the content of the engineering surveying under new engineering and technical disciplines:take the lofting and line measurement as examples LI Haojun, HUANG Liangke Bulletin of Surveying and Mapping    2024, 0 (5): 178-181.   DOI: 10.13474/j.cnki.11-2246.2024.0532 Abstract （31）      PDF（pc） （1673KB）（27）       Knowledge map    Save Building upon the foundation of summarizing the development of the new engineering disciplines, this study combines the content of the engineering surveying course within the surveying and mapping major as well as the comprehensive applications of this course and the accumulation of corresponding foundational knowledge within the discipline. Under new engineering and technical disciplines, engineering surveying has great significance to expand new application thinking based on traditional content. The article discusses the teaching content expansion of engineering surveying taking the lofting and line measurement as examples under new engineering and technical disciplines. Reference | Related Articles | Metrics

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A slope anomaly monitoring technology based on deep learning and image local feature extraction LIN Bokun, DING Yong, LI Denghua Bulletin of Surveying and Mapping    2024, 0 (4): 23-28.   DOI: 10.13474/j.cnki.11-2246.2024.0405 Abstract （91）      PDF（pc） （5137KB）（118）       Knowledge map    Save In order to improve the monitoring ability of slope hazards,this paper proposes a slope anomaly monitoring technology based on deep learning and image local feature extraction. By extracting the two-dimensional coordinates of natural features of the slope,this technology constructs the triangular target network. As the slope danger range is defined by the changing area of the triangular network,feature points with the same name are extracted within the change range,while the displacement of those feature points describes the slope change. The first step is to take images before and after the slope occurs,followed by identifying the natural features of the slope with the target detection model YOLOv5. In the semantic segmentation model DeepLabV3+,the extracted natural features are semantically segmented to obtain their binarized areas,and their two-dimensional coordinates are determined by determining the centre of the binarized area. As a next step,the triangular target network will be constructed by combining the two-dimensional coordinate lattices of all natural features,and the slope change range is delineated as the triangular network changes. After analyzing the image,the feature points with the same names within the change range are extracted using the image feature extraction technology,and their displacement distance and direction are used to evaluate the slope change. According to the test results,this technology is effective at monitoring slope changes,and it is a feasible tool for slope monitoring engineers. Reference | Related Articles | Metrics

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Remote sensing information extraction of sargassum from the in-shore shallow sea in Daya Bay LI Jun, HE Yingqing, DENG Ruru, XIONG Longhai, ZHANG Ruihao Bulletin of Surveying and Mapping    2024, 0 (5): 108-114.   DOI: 10.13474/j.cnki.11-2246.2024.0519 Abstract （32）      PDF（pc） （7202KB）（26）       Knowledge map    Save Sargassum plays an important role in healthy coastal ecosystems. Remote sensing monitoring mostly studies of floating sargassum in the open sea, and less research on shallow seabed sargassum; technical methods are mostly based on empirical models and rely on a large amount of measured data. This paper establishes a sargassum remote sensing information extraction model based on the radiation transfer process of water bodies. The results of three experimental areas in Daya Bay show that:①The sargassum abundance distribution is essentially consistent with the field survey data. ②Sargassum in Daya Bay grows better and has a higher abundance when the water is highly open, the water exchange conditions are good, the water is affected by wind and waves, the bottom is sand-covered rocks or reefs, and the water depth is less than 1.6m.③Water depth and waves are important environmental factors that affect the growth and distribution of sargassum. The method in this paper has positive significance for the protection of sargassum resources and the construction of coastal biodiversity. Reference | Related Articles | Metrics

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Real estate registration key technology based on 3D model WANG Zhaoze Bulletin of Surveying and Mapping    2024, 0 (5): 151-154,159.   DOI: 10.13474/j.cnki.11-2246.2024.0527 Abstract （46）      PDF（pc） （2508KB）（26）       Knowledge map    Save Three-dimensional real estate registration can effectively reduce registration errors, improve the accuracy of real estate registration, enhance the intuitiveness of real estate registration information, and solve problems such as spatial information confusion in real estate registration. Based on the in-depth research of key technologies such as real 3D models and BIM involved in 3D real estate registration, this article achieves rapid query and accurate positioning of 3D real estate units through spatial matching and data association of attribute data and model data, provids more accurate and comprehensive data support for 3D real estate registration. It provides feasible reference and reference for the future development of 3D real estate registration technology. Reference | Related Articles | Metrics

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A method for extracting complex and difficult road networks based on deep learning models ZHANG Nan, ZHANG Yunling Bulletin of Surveying and Mapping    2024, 0 (5): 155-159.   DOI: 10.13474/j.cnki.11-2246.2024.0528 Abstract （38）      PDF（pc） （1632KB）（26）       Knowledge map    Save With the wide spread application of high-resolution satellite image remote sensing technology, it also plays a huge driving role in transportation. There are technical difficulties in extracting rural road networks, such as data acquisition difficulties, inconsistent road features, natural environment interference, and frequent road changes. This study mainly uses high-resolution satellites as the main data source, and based on deep learning algorithms, learns the spectral, texture, and separable feature sets of different types of rural roads to identify rural roads with low grades and poor road conditions, which provides accurate data guarantee for the identification and discrimination of rural road networks, timely obtaining objective, accurate, and comprehensive basic data of rural roads solves the problem of insufficient road network information in complex and difficult areas. This study can serve scientific decision-making basis for the planning and construction of road networks in complex and difficult areas, and facilitates travel and traffic guidance. Reference | Related Articles | Metrics

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InSAR observations constrained coseismic slip distribution and Coulomb stress variation of Mw 6.7 Menyuan earthquake in 2022 WANG Xin, LI Shuiping, KANG Jing Bulletin of Surveying and Mapping    2023, 0 (7): 32-38.   DOI: 10.13474/j.cnki.11-2246.2023.0197 Abstract （188）            Knowledge map    Save In this paper, the line-of-sight (LOS) co-seismic deformation field of the Mw 6.7 Menyuan earthquake in Qinghai province on January 8, 2022 is obtained by using synthetic aperture radar differential interferometry (DInSAR) technology based on the Sentinel-1A satellite ascending and descending data. The non-negative least squares principle is used to retrieve the geometric parameters and co-seismic slip distribution of seismogenic faults. Finally, the Coulomb stress variation is calculated based on the fault slip distribution parameters and Coulomb fracture criterion. The results show that the Menyuan earthquake caused significant surface deformation, the coseismic deformation area is about 33 km×22 km, and the maximum LOS shape variables of ascending and descending data are -60 and 85 cm, respectively. Co-seismic sliding model display, the Menyuan earthquake is a left-lateral strike-slip event with a little thrust, and caused a co-seismic rupture about 36 km long (24 km for the main fault and 12 km for the branch fault) on the surface. The main rupture area is concentrated in 0～15 km depth, and the maximum slip of the main fault is 2.94 m, corresponding to 1.5 km depth.The maximum slip of the branch fault is 1.43 m, corresponding to 4.5 km depth. The seismic moment releases by inversion is 1.37×10 19 N·m, which is equivalent to a Mw 6.73 earthquake. Based on the results of field investigation and fault inversion, it is preliminarily determined that the co-seismogenic fault is the west end of Lenglongling fault and ruptures to the east end of Tuoleshan fault. The results of coseismic Coulomb stress variation and aftershock distribution show that the Coulomb stress at the east end of Lenglongling fault and the west end of Tuoleshan fault are obviously under loading condition, and the risk of strong earthquakes in the future is high. Reference | Related Articles | Metrics

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Application of comprehensive method of BeiDou/GNSS and precision leveling in old goaf collapse area surface deformation monitoring YANG Chunyu, YIN Hang, GUO Shuang, LUO Zhenhua, MA Fengfu Bulletin of Surveying and Mapping    2024, 0 (5): 142-146.   DOI: 10.13474/j.cnki.11-2246.2024.0525 Abstract （29）      PDF（pc） （9920KB）（25）       Knowledge map    Save Based on the on-site situation in the research area, this article fully utilizes the advantages and complementarity of BeiDou/GNSS and traditional precision leveling, and conducts comprehensive measurement analysis, achieving the organic unity and combination of BeiDou/GNSS and traditional precision leveling in monitoring complex landforms and underground space areas with complex features. Firstly, the basic working techniques and methods of BeiDou/GNSS surface deformation monitoring and precision leveling are introduced. Then, taking the surface deformation monitoring project in the old goaf collapse area of the Muchengjian coal mine in western Beijing as an example, the surface deformation monitoring data of the research area in the past year are analyzed, and the deformation status and trend are predicted and evaluated. This article can provide reference for the monitoring and research of surface deformation in the old goaf collapse area. Reference | Related Articles | Metrics

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An updating method of the HD map confidence ZHAO Mingshu Bulletin of Surveying and Mapping    2024, 0 (5): 166-171,177.   DOI: 10.13474/j.cnki.11-2246.2024.0530 Abstract （43）      PDF（pc） （1387KB）（25）       Knowledge map    Save The requirements by autonomous driving to HD maps, including high-precision, high-quality, and vast-coverage, which is less likely to be fully addressed with current technology. This paper proposes a method to convert low-precision observations into confidence of high-precision map elements, for they are different in spatial but very similar at feature level. It improves the strategy of HD map reliability without shorten its update cycle. The process starts with narrowing down matching scope and measuring matching rate, twice filtering using rectangular neighbor and a measuring model are employed to figure out the target from HD map. Followed by feature level analysis, status assessment and confidence score calculate, confidence of HD map elements get updated afterwards. Applying this method to our experiments with HD map includes 17 provinces, confidence of traffic sign gets updated via dash cam images. Moreover, two ways that could trigger out confidence update are verified, i.e. new observation and new map inputs. The results show redundant observations and confidence level are in positive correlation. When observation redundancy reaches 15, more than 80% of the target elements can maintain high confidence for 60 days, and the accuracy rate exceeds 96%. This study provides a solution to the conflict between high-precision map freshness and reliability, which can further promote the deepening of strategies of high-precision map applications. Reference | Related Articles | Metrics

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The Reform and Practice for Surveying Instrument Curriculum in Surveying and Mapping Department of College YU Teng, HU Wusheng, ZHOU Li, JIAO Minglian, SUN Xiaorong 测绘通报    2017, 0 (5): 147-151.   DOI: 10.13474/j.cnki.11-2246.2017.0176 Abstract （543）   HTML    PDF（pc） （6000KB）（698）       Knowledge map    Save In view of the actual situation of the continuous development and innovation of the surveying instrument,the effect and social evaluation of the curriculum of surveying instrument in the past five years is summarized. Surveying instrument has entered the era of electronic intelligence, the reform of teaching content according to the theory and practice are put forward, the improvement and innovative teaching methods are found, in turn, the curriculum also seeks to a reasonable assessment methods, and puts forward reasonable suggestions to form a complete set of curriculum related condition, finally, after the reform of curriculum, the teaching effect is discussed and analyzed. Reference | Related Articles | Metrics

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An assessment of BDS/GNSS positioning accuracy based on RTS backward smoothing methods WANG Yifan, ZHAI Wei, MA Yi Bulletin of Surveying and Mapping    2024, 0 (5): 66-70,84.   DOI: 10.13474/j.cnki.11-2246.2024.0512 Abstract （38）      PDF（pc） （3426KB）（24）       Knowledge map    Save To mitigate the issue of poor accuracy during the convergence phase of precise point positioning (PPP),we investigates the improvement of positioning accuracy using the RTS (Rauch-Tung-Striebel) backward smoothing algorithm. The evaluation of static PPP using the forward Kalman filter indicates that BDS can achieve an accuracy of 2.6mm,2.0mm,7.8mm in N、E、U direction. The GPS+Galileo combined PPP can achieve the best accuracy,which is 1.7mm,2.1mm,3.4mm in the N、E、U direction. The kinematic PPP using the RTS smoothing method indicate that an accuracy of 3.3mm,3.4mm,9.0mm can be achieved for the BDS PPP in the N、E、U direction. Introducing the GPS,GLONASS,or Galileo observations can improve the accuracy of BDS PPP by more than 50%. The analysis of on-vehicle dynamic testing further indicates that utilizing the reverse RTS smoothing algorithm for PPP calculations can achieve positioning accuracies of 0.028meters in the north direction (N),0.015 meters in the east direction (E),and 0.033 meters in the up direction (U). Reference | Related Articles | Metrics