Table of Content

25 January 2026, Volume 0 Issue 1

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“One Map”: conceptual analysis,technological foundation and application practice

HUANG Wei, GONG Yinxi, ZHANG Hongping

2026, 0(1):  1-6.  doi:10.13474/j.cnki.11-2246.2026.0101

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In the context of modernizing national governance capabilities,“One Map” has become an important pathway for promoting cross-departmental operational synergy and innovation in digital governance models.However,its conceptual connotation,technological foundation,and development trajectory have not yet been systematically reviewed.This paper aims to provide a systematic conceptual analysis and practical review of “One Map”. The study adopts methods of literature review,conceptual discrimination,and case synthesis.It systematically traces the theoretical origins and evolutionary trajectory of “One Map”, reviews its application practices in sectors such as smart cities,water conservancy,and emergency management,and focuses on analyzing the strategic positioning,practical needs,and governance logic of “One Map” construction in the natural resources sector.The study shows that: “One Map” is not a singular technology but rather an integrated concept that fuses ideas from geographic information systems (GIS), spatial data infrastructure (SDI), “single source of truth” (SSOT), and “common operating picture” (COP), with digital twin representing its future development direction; “One Map” has become a common “spatial foundation” in multi-sectoral applications; and the natural resources sector is constructing an authoritative,unified,and conflict-free national territorial spatial digital base (the “One Map 1.0” stage) through top-level design.The study posits that the essence of “One Map” has evolved from a technical methodology into a data-driven governance model and a tool for institutional reform.The current construction of this digital base is its foundational stage,while its evolution toward more advanced forms,such as digital twins and knowledge services,presents a profound challenge for working mechanisms,demanding a shift from “operational fusion” to “governance restructuring” This transition is key to enhancing national governance capabilities in the future.

Construction ideas and application directions of low-altitude “One Map” based on real-scene 3D data

WANG Lin, WANG Guangyao, DING Qiaoqiao

2026, 0(1):  7-11.  doi:10.13474/j.cnki.11-2246.2026.0102

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The high-quality development of the low-altitude economy relies on the precise empowerment and technical support of surveying,mapping,and geographic information.It requires the establishment of a unified spatio-temporal digital foundation to provide core infrastructure support for low-altitude flight and management.Based on the achievements of the physicalized,three-dimensional,and realistic 3D real-scene project,this paper elaborates on the construction approach of a unified low-altitude natural resource map from multiple dimensions,including the establishment of spatial benchmarks,construction of spatial foundations,classification of low-altitude elements,organization of low-altitude elements,and development of support capabilities.Furthermore,it analyzes typical application directions based on the unified low-altitude natural resource map,such as delineating utilizable low-altitude airspace,empowering the planning of urban low-altitude air route networks,and facilitating the site selection of low-altitude takeoff and landing facilities.This study provides a reference for the efficient utilization of low-altitude natural resources and collaborative empowerment of low-altitude management.

Exploring a knowledge graph-driven strategy for cadastral data construction within the unified cadastral basemap of the “One Map” initiative

LI Jun, WANG Hui, LIU Yong, Lü Jiahui

2026, 0(1):  12-17.  doi:10.13474/j.cnki.11-2246.2026.0103

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Under the “One Map” initiative,historical cadastral data often contain quality defects that impede refined management.This study aims to develop an efficient and accurate method to detect these data issues.A knowledge graph and a rule-based model were constructed by analyzing the relationships among geographic base map updates,land change surveys,and cadastral operations.Using automated techniques such as high-precision spatial overlay analysis and logical consistency checks,the method systematically identifies timeliness deviations (e.g.,lack of spatial coverage,failure to deregister) and ownership conflicts (e.g.,forest-farmland disputes,unlawful occupation of cultivated land) .Empirical results show that the proposed method significantly improves the efficiency and accuracy of cadastral data issue detection.This approach offers crucial technical support for natural resources management departments to objectively assess cadastral data quality and conduct targeted supplementary surveys,thereby enhancing data reliability.

Research on ground subsidence monitoring in Xi'an using time-series InSAR and universal GNSS

LI Jingtao, ZHANG Shuangcheng, SHENG Lei, ZHANG Yi, QIANG Fei, NIE Teng, LIU Ning, WEN Fan

2026, 0(1):  18-24,46.  doi:10.13474/j.cnki.11-2246.2026.0104

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In response to the issues of traditional urban ground subsidence monitoring often relying on a single monitoring method such as InSAR/GNSS,the use of post-processing strategies for GNSS results,and the high costs of imported GNSS receivers,this paper utilizes synergistic monitoring with InSAR and universal GNSS,proposing a high-precision near-real-time calculation model based on universal GNSS.By processing Sentinel-1A data from June 2015 to June 2024 using time-series InSAR technology and universal GNSS data from June 2023 to September 2024 with near-real-time calculation technology,the study obtained average deformation results over nearly a decade for Xi'an,deformation along the subway line within a 1 km buffer zone,and a high-precision three-dimensional near-real-time deformation sequence.The three-dimensional GNSS deformation was projected to the line of sight (LOS) for comparison with InSAR results.The results show that:①The overall ground deformation in Xi'an has gradually stabilized from subsidence,mainly influenced by groundwater as revealed by wavelet analysis; ②The deformation at points along the subway line is highly consistent with the period of subway construction,suggesting that underground engineering may be an important factor affecting ground subsidence in Xi'an;③The near-real-time LOS results from four GNSS stations exhibit a maximum deviation of within 1.2 cm compared to InSAR,with average deviations of 3.1,3.61,6.62,and 3.59 mm respectively,demonstrating that near-real-time calculation with universal GNSS can meet the vast majority of conventional deformation monitoring needs.

Detection of tobacco planting areas using fused optical-radar-phenological features: a case study of Xuanwei,Yunnan

YANG Xinru, WANG Yong, CHE Xianghong, JIANG Chi, SUN Qing, LIU Jiping

2026, 0(1):  25-31.  doi:10.13474/j.cnki.11-2246.2026.0105

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Accurate tobacco planting distribution and area information is helpful for efficient allocation of tobacco resources,scientific optimization of planting management and improvement of economic benefits.While existing crop classification research has largely concentrated on major crops,the identification of tobacco cultivation areas through the fusion of multi-source remote sensing data remains under-explored.In this study,Xuanwei city,Yunnan province was taken as the research area.Based on field survey samples and existing crop datasets,tobacco/non-tobacco sample points were generated,and Sentinel-1 polarization features,Sentinel-2 spectral/index features and growth phenology features of tobacco were constructed.Then,the random forest algorithm was used for feature selection and classification to explore the optimal feature combination scheme for tobacco planting area recognition and achieve accurate identification of tobacco planting areas.The results indicate that the optimal scheme of 79 features,derived from the fusion and selection of Sentinel-1,Sentinel-2,and phenological data,achieves the highest tobacco identification accuracy.The overall accuracy (OA) reaches 94.51%,the Kappa coefficient is 0.89,and the coefficient of determination (R²) is 0.94 between the identified area and statistical data at the township scale.This study provides efficient and reliable technical support for large-scale and long-term tobacco planting monitoring,precise management and policy formulation.

A vehicle-borne and backpack cross-source point cloud registration method based on image feature matching

XU Mengbing, ZHONG Ruofei, ZHONG Xueting, YANG Ran

2026, 0(1):  32-38.  doi:10.13474/j.cnki.11-2246.2026.0106

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To address the geometric heterogeneity and discrete noise between vehicle-borne and backpack cross-source point clouds in complex environments,which result in issues such as feature matching ambiguity and high computational complexity in traditional point cloud registration methods,this study proposes a registration approach based on image feature matching.The method divides the registration process into vertical alignment and horizontal alignment.Vertical alignment utilizes ground points as primitives to correct deviations in the vertical direction.For horizontal alignment,the point clouds are converted into binary images through top-down orthographic projection.Potential correspondences are then constructed using Lowe's ratio test combined with gradient orientation constraints.An optimization framework based on iteratively reweighted least squares (IRLS) is developed by integrating the Huber robust kernel function to precisely estimate the parameters of the image affine transformation.Coarse registration is achieved by combining ground-based alignment with image feature matching parameters,followed by fine registration using the iterative closest point (ICP) algorithm.Experimental results on multiple real world datasets demonstrate that the proposed method effectively overcomes challenges such as point density variation in cross-source point clouds and achieves accurate registration.The mean rotation and translation errors are below 0.000 5 rad and 0.065 m,respectively,and the average per point error is less than 0.06 m.Furthermore,with the support of voxel downsampling,the method significantly improves the efficiency of large scale point cloud registration while maintaining high accuracy,showing strong potential for practical application.

Earthquake disaster risk assessment based on InSAR coseismic deformation

LI Pengpeng, LI Dewei, LI Xiaohong, ZHAI Xuejun

2026, 0(1):  39-46.  doi:10.13474/j.cnki.11-2246.2026.0107

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On February 6,2023,Turkey was hit by the conjugate earthquakes of Mw7.8,causing severe damage to local lives and property.To address the issue of quantifying the sensitivity of seismic coseismic deformation to risk assessment during this earthquake risk assessment process,this study proposes an integrated risk assessment methodology combining InSAR-derived deformation data and the analytic hierarchy process (AHP) .The precise coseismic deformation is retrieved byD-InSAR,corrected by GACOS and verified by using ascending and descending SAR satellite data.The AHP is used to integrate coseismic deformation with hazard potential of causative factors and vulnerability of exposed elements.Meanwhile,the Sobol indices are used to systematically quantified the sensitivity contributions of individual parameters.The results indicate that the max value of theconjugate earthquakes deformation reached 1.88 m.The high-risk zones are predominantly in the 20 km buffer zone of the fault zone where are the densely populated urban areas.The direct drivers of the seismic risk are the fault distance effect,coseismic deformation,population density,and building density.The total effect of the coseismic deformation accounted for 19.1% of the model's total variance.This study provides foundational data and a scientific basis for the post-earthquake emergency response and the reconstruction planning.

A new coastline extraction model

GUO Hairui, ZHANG Tianyu, CAO Ruixue

2026, 0(1):  47-50,71.  doi:10.13474/j.cnki.11-2246.2026.0108

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In the area at the junction of land and sea in remote sensing images,due to the complex and changeable environment,the spectra of the boundary between land and sea are not clearly distinguishable,which makes it difficult to accurately determine the location of the coastline.To solve this problem,this paper constructs a coastline extraction model (EGOM) that integrates an edge detection neural network and grey theory.The model uses a multi-scale module group SEM,which can effectively capture multi-scale features.With the help of cross-resolution local fusion and secondary fusion mechanisms,the edge prediction map is optimized.Finally,a pseudo-edge culling strategy based on grey theory is introduced.Experimental results show that the model has an average offset index of 18.89 m,a root mean square error of 21.05 m,and can effectively remove pseudo-edges.Its overall performance is better than several other coastline extraction methods.

Analysis and prediction of reservoir bank landslide deformation based on time series InSAR and BiGRU

LIU Yiliang, LI Yongyi, ZHU Qian, ZUO Qingjun, FAN Xifeng, SONG Kun, SHEN Gaowei, TANG Luosheng

2026, 0(1):  51-56.  doi:10.13474/j.cnki.11-2246.2026.0109

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Due to the influence of geological structure and reservoir storage,landslides are frequent in the Three Gorges Reservoir area.Accurate monitoring and prediction of landslide deformation is crucial to ensuring regional safety.Due to the limitations of traditional methods for monitoring large-scale,high-precision deformation,this paper uses 73 Sentinel-1A up-orbit images from January 2021 to December 2023 and the Stanford method for persistent scatterers (StaMPS) technique to analyze the Sanmendong landslide's surface deformation in the Three Gorges Reservoir area.We systematically analyze the landslide deformation characteristics by screening the highly coherent control points and introduce global navigation satellite system (GNSS) data for validation.At the same time,we combine the ARIMA model with the CNN-BiGRU-Attention model to predict the displacement of the control points in the highly deformed area.The results show that the leading edge and middle part of the Sanmendong landslide are high-deformation areas with deformation rates ranging from -108.9 to -43.9 mm/a.The combined prediction model's RMSE is 1.11 mm and its MAE is 0.97 mm.It significantly improves the prediction accuracy and provides a new technical solution for intelligent early warning of geologic hazards.

Ray tracing-assisted SAR image simulation including multiple scattering

WU Ke, JIN Guowang, HE Kuan, LIU Hui, KONG Linghui, LI Ning

2026, 0(1):  57-64.  doi:10.13474/j.cnki.11-2246.2026.0110

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In order to improve the fidelity of distributed target SAR image simulation,we propose a novel ray tracing-assisted SAR image simulation method including multiple scattering.This method utilizes the range Doppler (RD) imaging geometry and ray casting theory to discriminate the radar beam radiation area of distributed targets and simulate the electromagnetic waves transmission.The ray tracing algorithm and the physical illumination model are combined to simulate the multiple scattering of EM waves,and the multiple scattering amplitude and phase are recorded in real time.The raw echo signal of the distributed targets is processed by RD imaging algorithm,then the corresponding SAR simulated image is obtained.We select some typical distributed targets to simulate SAR images,and then compare the simulated results with the real SAR images and the simulated results of the mainstream commercial simulation software to verify the effectiveness of the proposed method.

Identification of potential landslides in complex mountainous areas using combine ALOS-2 and Sentinel-1 data

CAO Ruihan, LI Xin, ZHOU Dingjie, XI Wenfei, HUANG Guangcai, WANG Ruiting, GUO Zhen

2026, 0(1):  65-71.  doi:10.13474/j.cnki.11-2246.2026.0111

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Landslide disasters are a severe natural hazard,posing significant threats to human life,property safety,and the ecological environment.The identification of potential landslides using a single SAR dataset often fails to adequately address the trade-off between spatial resolution and temporal resolution.This study integrates the strong penetration capability of ALOS-2 data in areas with moderate vegetation cover and the high temporal resolution of Sentinel-1 data to identify potential landslide hazards.Taking a complex vegetated mountainous region in Guizhou as a case study,the SBAS-InSAR technique is applied for experimentation.The results indicate that the surface deformation rates in the study area ranged from -125.34 to 46.01 mm/a for ALOS-2 data and from -159.42 to 124.44 mm/a for Sentinel-1 data.A total of 48 new landslide hazards are identified,with the complementary strengths of the two datasets significantly enhancing the spatial coverage and applicability of landslide identification.This study provides technical support for the early detection of landslide hazards and disaster prevention and mitigation efforts.

Segmented regression model and carbon sequestration potential assessment of NPP in Dongting Lake reed wetland based on SAR-DEM collaborative inversion

CHEN Zhu, LI Chenghao, LI Xiongwen, CHEN Jizhou, DENG Jinfeng, CHEN Jiangping, GAO Li, YANG Yijun

2026, 0(1):  72-77.  doi:10.13474/j.cnki.11-2246.2026.0112

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Reed wetlands are crucial carbon sink ecosystems.Accurately assessing their carbon sequestration capacity is vital for understanding the carbon cycle and ensuring ecological security.This study,taking the Dongting Lake reed wetland as an example,proposes a net primary productivity(NPP) estimation method integrating multi-source remote sensing,and explores the driving mechanism of phenological changes on carbon sink capacity.This study employed piecewise function regression.It synergistically utilized Sentinel-1 SAR and DEM data to invert canopy height.Landsat 9 OLI and Sentinel-2 optical data were fused to construct separate NPP prediction models for the initial growth stage (April) and the senescence period (November), based on vegetation indices and canopy height.The research revealed a significant positive correlation between canopy height and NPP in April.In contrast,during the November senescence period,although height was maintained,NPP decreased significantly and showed a negative correlation.The piecewise model effectively captured carbon sink differences across distinct phenological stages.Validation with field measurements from 2023 demonstrated that the method significantly improved estimation accuracy and reliability.This study validates that integrating multi-source remote sensing with piecewise modeling enhances the precision and timeliness of dynamic carbon sink monitoring in wetlands.It provides a scientific basis for precise wetland management.

Multi-orbit InSAR discrepancy analysis of landslide hazard identification results

SU Weijiang, SUN Liucun, XIAO Wenxing, GAO Yongqiang, HE Wen, LIAO Dan, XIE Mingli

2026, 0(1):  78-84.  doi:10.13474/j.cnki.11-2246.2026.0113

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The incidence angles and directions of SAR satellites with different orbits exhibit significant variations,leading to substantial discrepancies in acquired topographic deformation data.Previous studies have predominantly focused on integrating multi-orbit InSAR for landslide hazard identification,yet few have systematically analyzed the causes of discrepancies among results from different orbits.This study selects the Jiuzhaigou county area as the test site,utilizing Sentinel-1 images from three orbits (January 2020 to June 2024) to derive surface deformation via SBAS-InSAR,interpret landslide hazards,and compare the discrepancies in hazard identification across orbits.By evaluating metrics including the number of identified landslides,deformation distribution,time-series deformation,and slope aspect deformation recovery rates,the results reveal the following.Ascending orbit 55 identified 4 landslides,ascending orbit 128 detected 3,and descending orbit 62 detected 1.The deformation zones identified by ascending orbit 55 generally exhibited larger spatial coverage,higher deformation rates,and greater cumulative deformation compared to ascending orbit 128,though their overall time-series deformation trends are broadly consistent.The average slope aspect deformation recovery rates are 72.69%for ascending orbit 55 and 68.79% for ascending orbit 128.These findings provide technical insights for optimizing multi-orbit InSAR applications in landslide hazard detection.

Motion-aware 4D Gaussian radiance field reconstruction and localization

NING Guangfang, ZHAO Xinhui

2026, 0(1):  85-90,99.  doi:10.13474/j.cnki.11-2246.2026.0114

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Achieving camera pose estimation and 4D Gaussian radiance field reconstruction in dynamic scenes serves as a critical pathway for bridging 2D image observations and real-world spatiotemporal modeling.Unlike existing methods that typically treat dynamic objects as noise to be removed,this paper proposes a motion-aware 4D reconstruction framework tailored for dynamic environments.The system incrementally tracks camera poses and constructs a time-varying Gaussian radiance field from continuous RGB-D image sequences.Specifically,motion masks are generated to provide per-pixel static or dynamic priors; 3D Gaussian primitives are then divided into static and dynamic subsets,where dynamic Gaussians are modeled via a sparse set of control points and an MLP-based deformation network to capture non-rigid temporal motions.To further enhance inter-frame motion modeling,we introduce a novel Gaussian-rendered optical flow reconstruction approach that explicitly renders motion offsets of dynamic objects between adjacent frames.These optical flow cues are integrated with conventional photometric and geometric consistency constraints to jointly optimize the 4D Gaussian field.Experimental results on the TUM RGB-D and BONN dynamic datasets demonstrate the proposed method achieves robust pose tracking and high-quality scene reconstruction,especially in complex scenes with multiple moving objects and structural variation.

Early detection and monitoring of geohazards on the mountain expressway

WEI Yuhui, LIU Xianlin, SHAO Yu, DONG Xiujun, LI Haoliang

2026, 0(1):  91-99.  doi:10.13474/j.cnki.11-2246.2026.0115

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With the gradual development of infrastructure construction in western China,the consolidation of linear projects such as mountainous highways and railways has become a top priority for regional development.However,the complex terrain structure in the southwestern mountainous areas makes manual surveying for highway construction labor-intensive and inefficient,posing challenges for comprehensive hazard identification along the routes.With the rapid advancement of multi-source remote sensing and monitoring technologies,the "space-air-ground" integrated investigation system offers a novel solution to the challenges of geological hazard surveys for mountainous highways.This paper involves: firstly,employing satellite InSAR technology for large-scale deformation zone screening along highways; then,utilizing airborne LiDAR systems and oblique photogrammetry modules for detailed investigations of key hazard-prone areas; and finally,conducting on-site surveys along with surface and slope internal monitoring to verify and assess potential geological hazards.Taking a specific expressway as the study case,this paper applies the above methodology to conduct geological hazard investigations along the route,identifying 2 deformation zones and 119 potential hazard sites.The study demonstrates that the "space-air-ground" integrated hazard investigation system provides a new approach for the early identification,warning,and prevention of geological hazards along mountainous highways,while also offering critical technical support for regional disaster prevention and mitigation.

Adaptive testing method for cross domain semantic segmentation of aerial images

LUO Huiheng, YANG Lei, WEN Fan, HU Jinyan, WANG Haiyu, LI Zhuojian, GAO Chen

2026, 0(1):  100-107.  doi:10.13474/j.cnki.11-2246.2026.0116

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To address the issue of limited availability of training data in the target domain for remote sensing images and the inability to perform complete unsupervised domain adaptation during testing,which leads to decreased model accuracy,this paper proposes a test-time adaptation technique for cross-domain semantic segmentation of aerial remote sensing images.Based on a teacher-student network framework,the method introduces spatial consistency constraints and a high-confidence pseudo-labeling mechanism,enabling real-time and continuous model optimization in the target domain without requiring source domain data or annotations.Experimental results demonstrate the superior cross-domain adaptation capability of the proposed method in cross-band scenarios of aerial remote sensing imagery.On the target domain,the model's IoU increased from 27.51% to 42.63%,significantly outperforming comparative methods.Furthermore,the method exhibits strong extensibility and can be integrated with the DRDG (depth-assisted resi-DualGAN) approach to construct a multi-stage adaptive framework,which further improves IoU by over 5%.The proposed method demonstrates excellent cross-domain adaptation capability for aerial remote sensing image semantic segmentation,along with strong extensibility,effectiveness,and robustness in complex cross-domain scenarios.

Comparative analysis of two multi-path error modeling methods in BDS baseline solution

ZHANG Qingbo, ZHU Shaolin

2026, 0(1):  108-112,139.  doi:10.13474/j.cnki.11-2246.2026.0117

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Multi-path error remains a key issue in the BDS baseline solution,as it cannot be eliminated by differential methods and significantly affects the accuracy of the solution.To mitigate the impact of multi-path error,two modeling approaches are commonly employed.In this study,we use a short baseline composed of two stations,Delta park station and Yinghe east road station,from the Fuyang subsidence monitoring project in Anhui province to conduct experiments.We collect actual BDS observation data and compare the effectiveness of the two methods in reducing multipath error for subsidence monitoring applications.The results indicate that both methods improve the baseline accuracy.The first method achieves improvement rates of 76.47%,71.95%,and 72.61%in the E,N,and U directions,respectively.The second method shows improvements of 65.73%,61.38%,and 59.60% in the E,N,and U directions,respectively.

KMCORS coordinate time series analysis and 3D velocity field construction based on BeiDou Navigation Satellite System

ZHA Wenqian, CHEN Guoping, LI Wang, XU Dongfang, WEI Baofeng

2026, 0(1):  113-121.  doi:10.13474/j.cnki.11-2246.2026.0118

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With the completion of the global networking of the BeiDou Navigation Satellite System (BDS), its regional service performance has been significantly improved,which provides an important opportunity for the application of BDS-based regional continuous operation reference station (CORS) geodesy.In this study,based on the observation data of 31 Kunming Metropolitan Comprehensive Satellite Positioning Service System (KMCORS) reference stations in Kunming and surrounding areas from 2022 to 2024,baseline resolution and coordinate leveling of the dual systems (BDS and GPS) were performed using GAMIT/GLOBK software,and a high-precision 3D velocity field model was constructed by analyzing and reconstructing the coordinate time series.The results show that: ①The positioning accuracy of BDS and GPS is comparable in the north (N) and east (E) directions,but BDS is slightly inferior to GPS in the vertical (U) direction; ②According to the Pearson correlation coefficient,BDS stations exhibit stronger spatial correlation characteristics,and the spatial filtering method based on principal component analysis significantly improves the accuracy of BDS and GPS coordinate time series; ③The common-mode error of BDS and GPS can be effectively corrected.After correction,the velocity estimates of both systems converge,with average rates of 14.92 mm/a (N), 32.87 mm/a (E), 8.05 mm/a (U) for BDS and 15.23 mm/a (N), 32.62 mm/a (E), 4.96 mm/a (U) for GPS.This study demonstrates that the BDS positioning accuracy of KMCORS is comparable to GPS and can be effectively applied in urban coordinate frame maintenance and crustal deformation monitoring.

Segmented and layered modeling method for overpasses

YING Shen, QI Xuan, LI Yu, WANG Runze, LU Yuexin, TAO Lu

2026, 0(1):  122-129.  doi:10.13474/j.cnki.11-2246.2026.0119

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The road is the core element of the urban traffic system,serving as the fundamental infrastructure that connects various regions and carries traffic flow.Overpasses,serving as key structural components within urban road networks,are essential tools for traffic diversion.Therefore,the construction of models for overpass structures is critically important in domains such as urban traffic simulation and navigation positioning.However,traditional overpass modeling methods have issues with weak semantic geometric correlation and insufficient 3D topological representation.To address these issues,this paper proposes a universal segmented and layered overpass modeling method through a deconstruction analysis of overpass structures.This method achieves 3D modeling of complex urban traffic scenes with limited height data and low data costs.The proposed method is capable of modeling overpasses with diverse and complex structures,enhancing the efficiency of overpass modeling and precisely depicting the spatial hierarchy of overpasses.It effectively supports simulation applications such as road navigation and automatic driving,offering inspirational implications for the construction of urban 3D traffic network systems and the simulation of urban virtual environments.

Changes detection of cultivated land with domestic satellite images based on SNUNet

YE Yuanyuan, CHEN Chunhui, LI Xiangyun, FANG Tingting, LI Jinchao

2026, 0(1):  130-134.  doi:10.13474/j.cnki.11-2246.2026.0120

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Aiming at the problems in change detection,such as difficultly implement of prototype algorithm and poor applicability of sample set,this paper adopts SNUNet as the prototype algorithm.A comparison is made with similar algorithms on the public data set CDD,such as FC-EF,FC-Siam,UNet++＿SOF,etc.,and the results show that the SNUNet can fully utilize the semantic information of surface coverage,and has higher and more stable change detection accuracy.In order to improve applicability of the algorithm model additionally,more than 26 000 sets of change detection sample datasets are produced by using domestic multi-source satellite remote sensing images in Anhui province for localized training and optimization of the algorithm,and the accuracy reaches 84.3%.An application of cultivated land change detection is conducted in the experimental area.The algorithm and sample sets have good application prospects in the protection of cultivated land in Anhui province,and provide sufficient technical support for change detection in other places and different fields.

Efficient visualization and query analysis method for massive InSAR point cloud data for Web applications

LUO Xiaoliang, LIU Lingjia, LUO Jin, WANG Lüchun, YU Wei, LUO Gan, GAO Hua

2026, 0(1):  135-139.  doi:10.13474/j.cnki.11-2246.2026.0121

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Interferometric synthetic aperture radar (InSAR) is widely used in geological hazard monitoring and urban subsidence analysis as a technology that can obtain large-scale and high-precision surface deformation data.However,the existing WebGIS platform has obvious deficiencies in the efficient display,query and interpretation of tens of millions of InSAR point cloud data and deformation time series data,which restricts the promotion and application of InSAR technology.Therefore,in order to solve the key technical problems such as data preprocessing,storage,browsing and query of InSAR point clouds,this paper proposes a set of efficient visualization and query methods for massive InSAR point clouds in the Web environment,and develops a prototype system based on Cesium.By testing the performance of the system in six typical application scenarios,the results show that the developed system can smoothly realize the display of 3D deformation sequences of tens of millions of InSAR point clouds.The prototype system not only realizes the convenient distribution of InSAR deformation data and users can view it online,but also realizes the practical functions of deformation rate profile query,multi-period deformation profile query,single-point time series query and early warning analysis,which provides technical support for surface settlement analysis.

Tidal data-aided SAR image-based coastline extraction for islands

LIU Liansheng, LI Jingjing, LU Jiangtao, LIAO Jielin, WANG Changwei, YUE Wen

2026, 0(1):  140-143.  doi:10.13474/j.cnki.11-2246.2026.0122

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The coastline of an island serves as the baseline for analyzing the mechanisms of island evolution.Accurately extracting island coastlines has become a critical challenge urgently needing to be addressed in island research.This study focuses on Nan'ao Island as the research area.By spatio-temporally matching hourly tidal station water level observation data with Sentinel-1A synthetic aperture radar (SAR) satellite overpass times,four SAR images captured during high-tide periods from September 2023 to August 2024 were selected.An active contour model (Chan-Vese,CV model) was employed to extract instantaneous waterlines under different high-tide conditions,and a mean coastline was generated using the Euclidean distance metric method.Comparative analysis between this mean coastline and the latest government-approved coastline data of Guangdong province (2022) revealed an extraction accuracy of 16.28 m.The research demonstrates that the SAR image-based island coastline extraction method assisted by tidal information can effectively mitigate errors caused by traditional single-period image tidal corrections.This approach provides a novel solution for coastline extraction and dynamic monitoring in cloudy and rainy island environments,offering significant application value for enhancing refined island management capabilities.

Extraction of rock pile block size in mining based on 3D laser point cloud

HU Tianming, WANG Xingbang, HUANG Junyu, LI Kegong, WANG Haiyuan, LI Zhiming, LI Tao, ZHAO Weishan, NIAN Yanyun

2026, 0(1):  144-150.  doi:10.13474/j.cnki.11-2246.2026.0123

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Blast size is a key indicator for evaluating blast quality.Appropriate size not only enhances the efficiency of crushers but also significantly reduces energy consumption.This research utilizes the volume connected clustering segmentation(VCCS) algorithm and the local characteristic point cloud processing(LCCP) algorithm from the Point Cloud Library (PCL) to extract and analyze the block size in four classic blast pile areas of the Xiaozhashan limestone mine in Gansu province.The results show that as the block size of the ore increases,the accuracy of ore identification using the VCCS+LCCP algorithm significantly improves.Among the four blast piles,only the large block rate of pile 3 reached 14.59%,exceeding industry standards,thus necessitating secondary blasting or manual intervention to reduce its size.The large block rates of the other three piles were within a reasonable range,meeting the requirements for subsequent processing.In conclusion,this study confirms the effectiveness of three-dimensional laser point cloud technology in mining block size analysis,demonstrating its broad application prospects in enhancing the automation and accuracy of analysis.

Canopy gap information extraction method based on improved PSPNet network

LIU Danying, XIA Jisheng

2026, 0(1):  151-155,171.  doi:10.13474/j.cnki.11-2246.2026.0124

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Understanding the spatial distribution of canopy gaps holds significant importance for the conservation and sustenance of forest ecosystems.In the task of extracting canopy gap information based on GF-2 remote sensing imagery,given the extensive and complex distribution of cannopy gaps within forest systems,traditional remote sensing interpretation methods are inefficient and prone to misclassification and omission.Therefore,an improved canopy gap information extraction model based on PSPNet is proposed.This model replaces the backbone network to lighten its load,incorporates the CBAM attention mechanism,and refines the loss function,thereby enhancing the model's ability to learn forest gap information and addressing the issue of inaccurate identification of canopy gap edge details caused by an imbalance between positive and negative samples.Compared to the original PSPNet model,the improved PSPNet model exhibits an increase in the average intersection over union (IoU) by 3.12 percentage point,an improvement in average pixel accuracy by 3.6 percentage point,and a 65.43% increase in detection speed.This demonstrates the effectiveness of the proposed method for canopy gap information recognition.

Integration of 3D laser scanning and BIM models for construction quality inspection of large-span steel structures: a case study of the China-aided national football stadium project in Belarus

WANG Yong, SHA Yi, SUN Xiaoqiang, WANG Xiaojing, LIN Xiaofeng, ZHU Feifei, REN Changjiang, WANG Tiegang

2026, 0(1):  156-159,186.  doi:10.13474/j.cnki.11-2246.2026.0125

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The installation and construction of large-span steel structures face the disadvantages such as high construction precision requirements,significant influence of temperature on steel components,and difficulty in controlling overall deformation.In traditional installation and construction of large-span steel structures,the total station is mainly used to measure and control the key nodes of the steel structure.This method has fewer measuring points,and the understanding of the overall deformation of the steel structure is not comprehensive enough.As a result,after installation,the steel structure often has a high degree of coincidence with the original design model at several main components,but there are large installation errors between the positions without measuring point control and the design model.Such large installation errors often affect the service life of the entire steel structure.In order to obtain the deviation between the construction quality of the steel structure and the design more accurately,this paper proposes a comparative analysis method based on 3D laser scanning and BIM to detect the construction quality of the steel structure model.Firstly,the 3D point cloud data of the overall steel structure after construction is obtained through 3D laser scanning,and the point cloud of the steel structure is denoised (separated from the background point cloud).Then,the BIM model is compared and analyzed with the point cloud of the separated steel structure,and the deviation values of the steel structure members can be quickly obtained.Taking the steel structure construction project of the Belarus national football stadium as an example,this paper quickly obtains the deviation between the steel structure and the designed BIM model through the proposed method,and calculates the deviation amount between the point cloud of the steel structure after construction and the designed BIM model.The results show that this method can effectively check whether the steel structure construction meets the design requirements,effectively guarantee the construction of the steel structure,and provide a new solution for the quality inspection of steel structure construction.

Emergency rapid mapping technology based on multi-scale database products

LIU Bin

2026, 0(1):  160-164.  doi:10.13474/j.cnki.11-2246.2026.0126

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To meet the demand for efficient handling of urban emergency incidents,this paper explores the construction of an emergency rapid mapping system to realize the application of efficient emergency mapping technology.By analyzing the application scenarios of emergency maps,this paper deconstructs their core characteristics and sorts out the map resource database system.On this basis,it designs the technical process of emergency rapid mapping and elaborates on key links in the process,such as data construction,map matching,and rapid output.Combining with the practical case of Ningbo,this paper introduces in depth the on-site construction and application of this mapping system.Practice shows that the emergency rapid mapping process constructed by this technical system has played a key supporting role in actual emergency handling and significantly improved the efficiency of emergency response and decision-making.

Water-soil resource coordination and driving mechanisms in the Zhuanglang River basin based on the MGWR-coupled coordination model

ZENG Zhaorong, LI Chourong, LI Xia, WEI Wei, YANG Shilong

2026, 0(1):  165-171.  doi:10.13474/j.cnki.11-2246.2026.0127

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As a vital component of natural resources,water is essential for sustaining life,while soil forms the foundation of survival.Investigating the coupling and coordination between water and soil resources is crucial for ecological conservation and the sustainable development of river basins.Based on water and land use data from 2009 to 2021,this study constructs coupling coordination degree model and multiscale geographically weighted regression model to examine the spatio-temporal evolution and key influencing factors of water-soil resource coupling in the Zhuanglang River basin.The results show that: ①From 2009 to 2021,the overall coupling coordination degree exhibited a downward trend.High coupling degrees were observed between water resources and cultivated land,forest,grassland,and wetland; similarly,high coordination degrees were found between water resources and cultivated land,grassland,and wetland.②Spatially,the distribution patterns of coupling and coordination degrees were largely consistent,with high-value areas primarily located in the northern ecological protection zone and low-value areas concentrated in the central transitional zone.③Precipitation (0.705), slope (-0.723), land use type area (0.432), and water resource utilization efficiency (0.686) were identified as the most significant influencing factors,contributing substantially to the spatial differentiation of the coupling coordination degree.Moving forward,it is imperative to enhance the rational allocation of water and soil resources,strengthen integrated planning and management,and promote the coordinated development of multiple natural resources within the basin.

Supervision mechanism for environmental protection rectification in the Yellow River basin of Shaanxi province

MA Yuanzheng, MA Xinbo, YUAN Xinmiao, XUE Guiqin

2026, 0(1):  172-176,186.  doi:10.13474/j.cnki.11-2246.2026.0128

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To depth ecological protection and high-quality development efforts in the Yellow River basin,this work studies on environmental supervision and rectification mechanisms to improve the level of high-quality development in the Yellow River basin.Upon reviewing the current situation of the Yellow River basin in Shaanxi province,comprehensive data governance method for the rectification and supervision of environmental protection supervision issues in the Yellow River basin was designed.A supervision and supervision mechanism integrating “supervision and monitoring-supervision information management-remote sensing monitoring”was proposed,and successfully implemented its application in Shaanxi province.The designed mechanism clarifies the information flow and business interactions across various stages of supervision and monitoring,facilitates smooth transmission of supervisory information,and supports the generation of reliable analytical reports.Leveraging this mechanism,the development and reform department of Shaanxi province is able to effectively track and address rectification issues identified during environmental inspections,thereby significantly improving administrative efficiency and providing strong technical support for the establishment of a coordinated rectification supervision mechanism across the nine provinces of the Yellow River basin.

A dual adaptive filtering-based method for BDS+INS positioning and attitude determinatio

HU Wei, LI Junlei, LIU Weidong, SHEN Jian, LI Zhidong, FANG Yueyue

2026, 0(1):  177-181.  doi:10.13474/j.cnki.11-2246.2026.0129

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Subject to severe satellite signal occlusion in environments such as urban canyons and mountainous areas,the positioning accuracy and reliability of UAV power inspection systems face significant challenges.To address the degradation in filtering precision caused by observation gross error interference and inaccurate modeling of noise statistical characteristics within the BDS (BeiDou Navigation Satellite System) +INS(inertial navigation system) integrated navigation system,a dual adaptive filtering-based integrated navigation method is proposed,building upon the traditional loosely-coupled BDS+INS integration algorithm.By integrating the IGGⅢ robust estimation technique with the Sage-Husa adaptive filtering algorithm,this approach effectively suppresses pose errors caused by observation anomalies resulting from multipath effects and signal blockage.Experimental results demonstrate that the proposed method improves BDS standalone positioning accuracy by approximately 77%.Regarding BDS+INS integrated navigation performance,positioning accuracy and attitude estimation accuracy are improved by approximately 55%and 54%,respectively,compared to traditional algorithms.

Application of the “4M1E” quality control model in large-scale surveying and mapping projects:a case study of the 3D reality modeling project in Jiaxing city

CAO Qitong, WEN Yubin, HUANG Guodong, LI Zhaofeng, SHEN Yuzhen

2026, 0(1):  182-186.  doi:10.13474/j.cnki.11-2246.2026.0130

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With the continuous development of digital china and the digital economy,the number of large-scale surveying and mapping projects has increased significantly.The traditional “two-level inspection and one-level acceptance” approach is no longer sufficient to meet the high-quality development requirements of modern large-scale surveying projects.This paper takes the Jiaxing city 3D engineering construction project as a case study and introduces the “4M1E” quality control model,which is widely used in manufacturing and other fields.By restructuring the relationships between the man,material,machine,method,and environment within the surveying context,this approach enables comprehensive quality management throughout the entire process and all elements of large-scale surveying projects.The results indicate that in this project,the quality pass rates of terrain-level geographic scene data,3D model data,and land-use entity data all exceeded 98%,with all phase tasks completed on schedule,effectively reducing the overall project cost.The study demonstrates that the restructured “4M1E” model can meet the quality management needs of modern large-scale surveying projects,effectively improving project efficiency and quality.