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Geo-Agent: a framework for intelligent geographic information systems with natural language interaction LIANG Hailei, WANG Yong, DU Kaixuan, ZHOU Weixiang Bulletin of Surveying and Mapping    2025, 0 (10): 114-118,126.   DOI: 10.13474/j.cnki.11-2246.2025.1019 Abstract （544）      PDF（pc） （3350KB）（127）       Knowledge map    Save Traditional geographic information systems (GIS)often encounter multiple challenges in the human-computer interaction process, such as cumbersome operation procedures and limited intelligence.With the rapid development of general artificial intelligence technology, new engines centered on generative AI are driving the geographic information industry to accelerate its evolution from digitalization to intelligence.Typical practices include innovative research such as Autonomous GIS, MapGPT, and LLM-Find.Existing studies have confirmed the huge potential of large language models (LLMs)in tasks such as GIS knowledge Q&A and map-making.However, current research still has the following limitations: on the one hand, the models lack the ability to autonomously understand geographic information data and perform complex spatial task analysis; on the other hand, they highly rely on the task parsing and code generation capabilities of the large models themselves.In addition, the API calling mode may lead to the risk of privacy and sensitive geographic data leakage.To address these challenges, this paper innovatively proposes a geographic information intelligent agent, Geo-Agent, based on an open-source architecture.This framework proposes a multi-level instruction parsing strategy based on spatial thinking chains and a data retrieval strategy oriented to graph structures, effectively solving the problems of geographic semantic understanding deviation and spatial logic disconnection.Experimental verification shows that Geo-Agent can understand, manage, and deeply analyze geographic information data, and can complete complex spatial analysis tasks through natural language interaction, providing an innovative path for realizing fully autonomous and intelligent next-generation geographic information systems. Reference | Related Articles | Metrics

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Real-scene 3D data acquisition and fusion technologies inside and outside caves:take Yixing Shanjuan Cave for an example GUO Zhendong, WU Hao, GU Zhengdong, HUANG Liang Bulletin of Surveying and Mapping    2025, 0 (8): 149-152.   DOI: 10.13474/j.cnki.11-2246.2025.0824 Abstract （530）      PDF（pc） （3762KB）（136）       Knowledge map    Save Aiming at the insufficient research on modeling complex indoor and underground spaces in real-scene 3D construction,this paper proposes a 3D modeling method that integrates 3D point clouds and video imagery.Firstly,high-precision laser point cloud data inside the cave is acquired using SLAM technology,while multi-angle video imagery is collected via close-range photogrammetry.Then,the SFM algorithm is employed to generate dense matching point clouds,and the ICP algorithm is applied to achieve precise registration of heterogeneous data,constructing a 3D cave model with both structural features and texture information.Finally,the indoor model is fused with an outdoor terrain-level real-scene 3D model obtained from UAV oblique photogrammetry,forming a unified digital twin platform.The results demonstrate that this method achieves high-precision reconstruction and virtual-real integration of indoor and outdoor scenes,providing a reliable technical reference for modeling complex underground spaces. Reference | Related Articles | Metrics

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Application of BIM reverse modeling based on multi-source data fusion in the preservation of historic and cultural blocks XING Wang, FANG Zheng, XU Yi, ZHANG Canghao, SUN Lianzeng, WANG Zhaoze Bulletin of Surveying and Mapping    2025, 0 (8): 159-163,178.   DOI: 10.13474/j.cnki.11-2246.2025.0826 Abstract （515）      PDF（pc） （3507KB）（186）       Knowledge map    Save Addressing the issues of low model completeness and unstable data accuracy in traditional modeling of existing buildings in historical and cultural districts,a technical system of “comprehensive acquisition-data fusion-intelligent reconstruction” is proposed.By utilizing 3D laser scanning and multi-view photogrammetry technologies,millimeter-level geometric frameworks and high-resolution texture information of buildings are obtained respectively.An improved SICP algorithm is employed to achieve precise fusion of multi-source point clouds.Finally,using BIM reverse modeling to construct a realistic 3D model containing building information.The results indicate that this method achieves millimeter-level geometric accuracy and over 98%completeness of the model,supporting multi-dimensional spatio-temporal information overlay analysis.It provides a full lifecycle solution for preventive conservation,virtual restoration,and revitalization of the district. Reference | Related Articles | Metrics

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Ground deformation monitoring and influence factors analysis of the Gaizi valley near the Karakoram highway based on SBAS-InSAR technology MO Dandan, HUO Jiuyuan Bulletin of Surveying and Mapping    2025, 0 (8): 32-42.   DOI: 10.13474/j.cnki.11-2246.2025.0806 Abstract （499）   HTML （19）    PDF（pc） （14386KB）（115）       Knowledge map    Save The Karakoram highway (KKH) in China and Pakistan has complex geological conditions, peculiar and variable climate, and landslide hazards are frequent along the route, so the investigation and monitoring study of landslide hazards in this region is of great importance for disaster prevention and mitigation. In this study, the small baseline subsets InSAR (SBAS-InSAR) technique is used in combination with optical remote sensing images to monitor the surface deformation and analyze the time-series deformation characteristics of the Gaizi valley section of the China-Pakistan highway.Based on 64 scenes of Sentinel-1 image data covering the study area, the SBAS-InSAR technique is used to obtain deformation distribution maps and time-series deformation features of the study area over the time span. The deformation rate values of the radar line of sight (LOS) in the study area from March 2017 to August 2022 ranged from -33.5 to 11.6 mm/a, with a maximum cumulative deformation of 179.4 mm. On this foundation, the accuracy of the deformation detection results is verified by combining the optical remote sensing images of four typical landslide areas in the region and previous research results, demonstrating that SBAS-InSAR technology is an effective tool for deformation monitoring of landslide hazards. The time series deformation curves are analyzed by using monthly average precipitation, monthly average temperature, monthly maximum temperature, monthly minimum temperature, surface soil moisture data, glacier distribution data, earthquake catalogue, IGBP land cover data and so on. Furthermore, the influence of different factors on the surface deformation of landslides in the study area is explored to provide a scientific basis for early identification and prevention of disasters. Reference | Related Articles | Metrics

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UAV-based object recognition dataset for coastal sewage outfalls YIN Junjie, GUAN Daiwanjing, LI Hao, ZHANG Xiaoyang, MA Yujie, XING Hanfa Bulletin of Surveying and Mapping    2025, 0 (8): 112-117.   DOI: 10.13474/j.cnki.11-2246.2025.0818 Abstract （446）   HTML （11）    PDF（pc） （3975KB）（67）       Knowledge map    Save The identification of coastal sewage outfalls is a crucial aspect of marine supervision,providing essential safeguards for the ecological and resource security of marine areas.Addressing the current challenges of insufficient specialized datasets and the lack of precision in target recognition algorithms for coastal sewage outfall detection using unmanned aerial vehicle (UAV)imagery,this study constructs a high-quality dataset of coastal sewage outfalls and proposes an enhanced detection method based on the improved YOLOv8n model.Initially,focusing on the coastal region of Yangjiang city,Guangdong province,the study employs UAVs to capture images at various altitudes,establishing a comprehensive dataset that encompasses diverse characteristics of sewage outfalls.Subsequently,the YOLOv8n model is augmented with the SimAM parameter-free attention mechanism to refine feature extraction and fusion,alongside the integration of NWD and CIoU loss functions to address issues of boundary ambiguity and target overlap.Experimental results demonstrate that the enhanced model surpasses the original in terms of precision,recall rate,and mAP,achieving an mAP of 98.27%.This research offers an intelligent solution for monitoring coastal sewage outfalls,contributing technological support for marine supervision and pollution control. Reference | Related Articles | Metrics

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Precision analysis and positioning evaluation of satellite-based precise point positioning service in the Antarctic region LIU Yang, CHAI Hongzhou, WANG Min, ZHOU Yingdong, SUN Shuang, ZHANG Qiankun Bulletin of Surveying and Mapping    2025, 0 (8): 1-6.   DOI: 10.13474/j.cnki.11-2246.2025.0801 Abstract （428）   HTML （18）    PDF（pc） （3117KB）（194）       Knowledge map    Save Satellite-based precise point positioning service offers high-precision positioning in the environment where terrestrial networks are hard to cover,yet there are few applications in polar regions.Based on the measured HAS data of China's 40th Antarctic Expedition and the real-time precision orbit and clock deviation products of MADOCA and CNES broadcast on the network.This paper assesses the availability,accuracy and PPP performance of different products' orbit and clock correction of GPS and Galileo in the Antarctic region.The results demonstrate that GPS and Galileo correction products provided by HAS,MADOCA and CNES are highly accurate and can satisfy the requirement of centimeter-level positioning accuracy,reflecting the applicability of these real-time products in the Antarctic region.Both HAS and MADOCA can provide stable and reliable PPP services,with a horizontal positioning accuracy of less than 0.2 m and a vertical positioning accuracy of less than 0.4 m,conforming to the service standards.This provides a theoretical and practical basis for the application of satellite-based precision single-point positioning technology in polar regions and other high latitudes. Reference | Related Articles | Metrics

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Forest aboveground biomass mapping in the Greater Mekong Subregion using multi-source remote sensing data fusion YUAN Lili, YANG Xinwei, LI Menghua, CHEN Yuquan, TANG Bohui Bulletin of Surveying and Mapping    2025, 0 (8): 43-47.   DOI: 10.13474/j.cnki.11-2246.2025.0807 Abstract （414）      PDF（pc） （6381KB）（132）       Knowledge map    Save Accurate estimation of forest aboveground biomass density is crucial for advancing sustainable forest management.This study focuses on the Greater Mekong Subregion (GMS)and utilizes spaceborne global ecosystem dynamics investigation(GEDI),Sentinel-1,Sentinel-2,and auxiliary datasets to extract 52 feature variables.By applying the LightGBM machine learning model,a 1 km resolution forest aboveground biomass density map of the GMS is generated.The results indicate that the LightGBM model achieved R 2=0.65,RMSE=38.11 Mg/hm 2,and EA=72.03%.Across the study area,biomass density ranged from 15.16 to 423.87 Mg/hm 2.The derived biomass product demonstrated strong correlation with the GEDI L4B product ( R 2=0.52,RMSE=61.91 Mg/hm 2).In conclusion,open-access earth observation (EO)data exhibits significant potential for estimating forest aboveground biomass. Reference | Related Articles | Metrics

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Intelligent collaborative DOM production technology based on remote sensing image production platform WANG Yingmou, LI Lei Bulletin of Surveying and Mapping    2025, 0 (8): 142-148.   DOI: 10.13474/j.cnki.11-2246.2025.0823 Abstract （414）      PDF（pc） （9843KB）（104）       Knowledge map    Save This paper investigates the intelligent collaborative DOM production technology based on a remote sensing image production platform.This technology effectively addresses the issues of low efficiency,insufficient accuracy,and cumbersome processes associated with traditional DOM production by constructing a control point database and a multi-software intelligent collaborative platform.The establishment of the control point database enables the integration and efficient utilization of historical control point data,significantly reducing fieldwork and production costs.The multi-software intelligent collaborative platform combines the functional advantages of software such as INPHO,Tian Gong 2D integrated software,and DPGrid,achieving full-process optimization from aerial triangulation to DOM production.This effectively improves the geometric accuracy and visual effects of DOM while significantly increasing production efficiency.The experimental results show that this technology can effectively improve the efficiency and quality of DOM production,reduce fieldwork and costs,which has considerable value for promotion and application. Reference | Related Articles | Metrics

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Ground target localization method combining unmanned aerial vehicle pose information LUO Qingli, ZHANG Shubin, JIANG Xintao, WEI Jujie, GAN Jun Bulletin of Surveying and Mapping    2025, 0 (8): 19-25.   DOI: 10.13474/j.cnki.11-2246.2025.0804 Abstract （382）   HTML （16）    PDF（pc） （10468KB）（142）       Knowledge map    Save Traditional methods for ground target localization using single-frame drone images typically require at least four prior control point information.However,acquiring control points becomes increasingly challenging as their quantity increases,presenting an arithmetic growth problem.This paper proposes a ground target localization method that integrates unmanned aerial vehicle(UAV)pose information.The method combines UAV pose information with three ground control points to establish a geometric optical model.This model enables the mapping relationship between ground target points and UAV image pixels,facilitating the determination of latitude and longitude coordinates for each ground target point.Consequently,precise ground target localization based on a single-frame drone image is achieved,reducing the required number of control points and enhancing localization accuracy.The experimental results indicate that the average positioning accuracy of this method reaches 1.45 pixels,which is 4.61 pixels higher than that of the traditional PnP four-point target positioning method. Reference | Related Articles | Metrics

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Real-scene 3D data supported UAV low-altitude route planning for complex urban environments YU Zhonghai, YANG Na, WANG Lu, LI Xin, ZHOU Changjiang, DUAN Longmei Bulletin of Surveying and Mapping    2025, 0 (10): 127-132.   DOI: 10.13474/j.cnki.11-2246.2025.1021 Abstract （365）      PDF（pc） （4588KB）（130）       Knowledge map    Save Low-altitude route planning and infrastructure constitute important research directions in the low-altitude economy.To further enhance the application of real-scene 3D modeling in urban digital transformation and provide a sustainable 3D digital foundation for low-altitude economic growth, this paper proposes a low-altitude route planning algorithm based on RRT+Floyd, supported by real-scene 3D data, tailored for complex urban environments.Experiments are conducted in the eastern high-tech zone and northern built-up area of Jinan city, evaluating route planning at four altitudes (30, 80, 120, and 300 m).Five metrics(route length, node count, smoothness, average turning angle, and maximum turning angle)are compared with the traditional RRT algorithm.Results show that the proposed algorithm significantly improves planning efficiency and speed in low-altitude airspace, particularly in class W airspace. Reference | Related Articles | Metrics

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The method of smoke and flame target extraction facing UAV and remote sensing images LIU Xiaodong, ZHAO Chenmeng, REN Yinghua, YANG Liping, ZHAO Like, ZHANG Ka Bulletin of Surveying and Mapping    2025, 0 (12): 7-14.   DOI: 10.13474/j.cnki.11-2246.2025.1202 Abstract （356）      PDF（pc） （9810KB）（206）       Knowledge map    Save Addressing the bottlenecks in UAV and remote sensing-based smoke/flame detection task,such as insufficient multi-scale feature capture,complex background interference,and blurred edges,a method of smoke and flame target extraction based on the improved YOLOv12 model is proposed in this paper.The proposed method enhances multi-scale feature fusion through a mixed local-channel attention (MLCA)mechanism,improves detail retention in low-resolution images via an adaptive downsampling (ADown)module,and refines boundary regression accuracy with a customized adaptive loss function.Furthermore,by integrating the fine-tuned SAM2.1 model,the paper's method can realize pixel-level segmentation of targets within detection boxes.Experiments on the FASDD＿UAV,FASDD＿RS,and S-Firedata datasets shows that the proposed method achieves mAP50 scores of 93.1%,78.5%,and 68.2%,outperforming the baseline model YOLOv12 by 1.3%,1.5%,and 1.2%,respectively.The proposed method demonstrates significant advantages in detecting small targets,handling occluded scenarios and complex lighting conditions.Additionally,ablation experiments have confirmed the feature enhancement effects of the MLCA and Adown modules,as well as the optimization effect of Focaler-PIoU on model performance through dynamic gradient allocation. Reference | Related Articles | Metrics

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GAMIT multi-system GNSS data processing to determine Guangzhou CORS coordinate datum CHEN Jiaqi, CHENG Xiangbing, HU Yaofeng, LI Wenyi Bulletin of Surveying and Mapping    2025, 0 (8): 179-184.   DOI: 10.13474/j.cnki.11-2246.2025.0830 Abstract （341）      PDF（pc） （5221KB）（64）       Knowledge map    Save To unit of Guangzhou CORS reference station network and BeiDou ground-based monitoring station network coordinate datum,and explore the feasibility of using the BeiDou system to maintain the surveying datum of regional CORS station network,we carry out GAMIT high-precision baseline solution and 3D constrained adjustment for 6 sets of dual-frequency data from 27 stations in the Greater Bay Area.The results show that normalized root mean square error(NRMSE) of the baseline solutions is better than 0.25,and the ambiguity resolution success rate of GPS,GLONASS,and Galileo baseline solutions exceeds 90%.The plane direction of baseline repeatability is better than the elevation direction,the fixed error of linear fitting is in the order of millimeter,and the scale error is better than the GNSS Class B 10 -8 accuracy requirements.The baseline adjustment accuracy of the four systems is the highest,and average RMSE of the single system adjustment coordinate difference is 1.1 mm in the north direction and 1.5 mm in the east direction.There is inconsistency in the elevation direction,and the maximum difference in the elevation of Galileo and GLONASS adjustment coordinates is more than 20 mm.This paper verifies the feasibility of GAMIT processing BDS data to independently maintain regional CORS coordinate datum.On the whole,the accuracy of BDS new signal frequency B1C/B2a and B1C/B3I is equivalent to that of GPS L1/L2 dual-frequency combination,and superior to BDS B1I/B3I and Galileo E1/E5a dual-frequency combination.The accuracy of various indicators of the GLONASS G1/G2 dual-frequency combination is relatively low. Reference | Related Articles | Metrics

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Analysis and application of BDS-3 new frequency PPP continuity in East Antarctica MAO Wenbin, YAN Hao, XU Junming, LIU Shiji Bulletin of Surveying and Mapping    2025, 0 (8): 13-18.   DOI: 10.13474/j.cnki.11-2246.2025.0803 Abstract （330）      PDF（pc） （2239KB）（64）       Knowledge map    Save Addressing the polar positioning performance of the BDS-3 new frequency,this paper analyzes the B1C/B2a dual-frequency combined precise point position(PPP)accuracy of the BDS-3 system and the coordinate time series variation trend for each tracking station,based on multi-year (2021—2025)measured data from four tracking stations in the East Antarctica region.Experimental results show that BDS-3 offers good satellite availability in East Antarctica,with an average of 9 satellites available and PDOP values below 3.The static PPP performance is excellent,with horizontal positioning accuracy better than 1 cm and vertical positioning accuracy better than 1.5 cm.Each tracking station's coordinates exhibit a significant shift trend,with a maximum annual shift rate reaching the centimeter level,mainly influenced by local ice flow speed and mass changes.Similarly,the study's results can be used to infer ice flow speed and mass changes,providing new references and continuous support for the practical application of BDS-3 new frequency in polar regions. Reference | Related Articles | Metrics

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Construction of multimodal population spatialization model via IVYA-SIAM joint optimization and its driving effect analysis WANG Lizhi, XIAO Dongsheng Bulletin of Surveying and Mapping    2025, 0 (8): 95-99,106.   DOI: 10.13474/j.cnki.11-2246.2025.0815 Abstract （326）      PDF（pc） （9550KB）（43）       Knowledge map    Save Aiming at the precision bottleneck and insufficient spatial heterogeneity analysis in existing models due to single-algorithm dependence,this study proposes a three-tier “multimodal ensemble-parameter adaptation-feature enhancement” optimization framework.First,multi-source data (such as nighttime lighting,building outlines)are integrated to construct a secondary model (N-MLP)via stacking random forest,XGBoost,and MLP.Then,the IVY algorithm (IVYA)is introduced for dynamic hyperparameter optimization,and a spatial interaction-augmented attention mechanism (SIAM)is designed to enhance geographical spatial dependence analysis through parallel attention architectures.Finally,a dual-scale validation system (400 m grid and township/street levels)is established in Chengdu,and the driving effect of population distribution on drone logistics demand is analyzed via a low-altitude economy demand elasticity model.Results show that the optimized SIAM-IVYA-N-MLP model achieves an R2 of 0.947 9 at the grid scale,with MAE and RMSE reduced by 14.67%and 3.38%,respectively.At the township/street scale,the R2 reaches 0.971 6.A 1%increase in main urban population density drives a 1.19%growth in drone logistics demand.This study provides an operational technical pathway for high-precision population spatialization and low-altitude economic infrastructure planning. Reference | Related Articles | Metrics

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Integration of multi-view images and deep learning for automated restoration and application of realistic textures in 3D building models LIU Yawen, TIAN Qin, GUO bingxuan, LI Demin Bulletin of Surveying and Mapping    2025, 0 (12): 15-19.   DOI: 10.13474/j.cnki.11-2246.2025.1203 Abstract （318）      PDF（pc） （4233KB）（196）       Knowledge map    Save 3D building models with both geometric accuracy and realistic textures have become an important component of the national new infrastructure construction.Due to constraints such as UAV flight conditions and building layout,a large number of real texture occlusion problems occur in the texture mapping of 3D building models,which affect their visualization effects and the functions of applications such as query and measurement.Existing methods are based on a single texture image for repair and treat the occluded area as an unknown random variable,leading to possible deviations of texture repair from the real facade features of buildings.Based on the characteristic that the occlusion range of the same facade of a building varies in images from different perspectives,this paper proposes an automatic facade texture occlusion repair algorithm combining multi-view images and deep learning networks.The algorithm extracts the occluded area by using the structural similarity of multi-view textures after texture alignment,automatically synthesizes the real facade texture through the graph-cut method,and uses the DeepFill model to repair and optimize the synthesized texture.Experiments show that this method can repair the real texture of more than 40% of the occluded area,and the SSIM and PSNR values of the repaired facade texture are improved compared with existing methods. Reference | Related Articles | Metrics

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Monitoring of TLS point cloud deformation in large underground caverns WANG Haofan, LI Biao, LI Tao, XIAO Peiwei, QIAN Hongjian, XU Nuwen Bulletin of Surveying and Mapping    2025, 0 (8): 76-82.   DOI: 10.13474/j.cnki.11-2246.2025.0812 Abstract （308）      PDF（pc） （5218KB）（68）       Knowledge map    Save Deformation control in large underground caverns may pose a serious threat to personnel safety and engineering progress.Deformation monitoring of underground cavern is of great significance to prevent engineering disasters.To solve the problem of low deformation monitoring efficiency and incomplete information in large-scale underground cavern engineering,a deformation observation technology based on TLS point cloud is proposed in this paper.This technology includes semi-automatic point cloud noise reduction combining RANSAC Shape Detection algorithm and surface variation,and calculation of caverns surface deformation based on M3C2 algorithm,which can realize comprehensive and efficient monitoring of large-scale underground caverns deformation.This technique is applied to monitor the support deformation in a typical area of the main building of Xulong Power station,and it is found that there are obvious deformation bands in the downstream side arch of Yc0+140 to Yc0+170 during the frequent construction stage,and the results are consistent with the traditional deformation monitoring results on site.The observation results provide more comprehensive three-dimensional deformation information for deformation control of large underground caverns and improve the efficiency of deformation monitoring. Reference | Related Articles | Metrics

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Urban multi-dimensional sensing infrastructure: architectural innovations and monitoring applications HU Yaofeng, CHENG Xiangbing, CHEN Jiaqi Bulletin of Surveying and Mapping    2025, 0 (8): 174-178.   DOI: 10.13474/j.cnki.11-2246.2025.0829 Abstract （305）      PDF（pc） （2252KB）（84）       Knowledge map    Save Historical and cultural blocks are core areas where urban historical and cultural heritage is centrally preserved,serving as a critical component and essential focus in the protection of historical and cultural cities.This paper addresses persistent issues in China's historical and cultural blocks,including lagging supervision and management,recurring damage to traditional architectural features,and outdated dynamic monitoring methods.We propose the concept of establishing an urban multi-dimensional sensing network,investigate its key technologies,and validate the significant effectiveness of the sensing network implementation through a pilot application in Guangzhou's historical and cultural blocks. Reference | Related Articles | Metrics

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GNSS-assisted UAV aerial photography technology for obtaining data for quality inspection of new surveying and mapping products ZHANG Yongli, ZHU Wenchao, FAN Yewen, QU Zhi Bulletin of Surveying and Mapping    2025, 0 (8): 153-158.   DOI: 10.13474/j.cnki.11-2246.2025.0825 Abstract （302）      PDF（pc） （2165KB）（67）       Knowledge map    Save The development of new basic surveying and mapping has driven the innovation of quality inspection technologies.This paper aims to study the technology of acquiring quality inspection data for new surveying and mapping products without ground control points based on a new-type surveying and mapping equipment-the unmanned aerial vehicle (UAV)aerial photography system.Based on the relevant research achievements of the UAV aerial photography system and the standards related to aerial photography,this paper discusses the quantitative relationship between aerial photography flight parameters and the data accuracy of surveying and mapping products,and presents the corresponding mathematical model.At the same time,it analyzes three modes of GNSS-aided UAV aerial photography,and designs a ground control point-free UAV aerial photogrammetry scheme for acquiring data used in quality inspection of large-scale surveying and mapping products.The feasibility of the scheme combining the flight parameters designed by the mathematical model with GNSS-aided UAV aerial photography has been verified through the experiment in Luoding,Guangdong,which can obtain high-precision quality inspection data corresponding to the scale. Reference | Related Articles | Metrics

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Hyperspectral and multi-spectral data fusion method combined with deep spatio-spectral-temporal features PAN Chen, WANG Xiaochu, WANG Zhiwei Bulletin of Surveying and Mapping    2025, 0 (8): 118-122.   DOI: 10.13474/j.cnki.11-2246.2025.0819 Abstract （301）      PDF（pc） （5480KB）（63）       Knowledge map    Save To address the limited spatial resolution of hyperspectral satellite imagery,this study proposes a data fusion method driven by deep spatio-spectral-temporal features.The method integrates the rich spectral information of hyperspectral images with the fine spatial details of multi-spectral data,aiming to generate fused imagery with both high spectral and spatial resolution.The fusion network is built upon a generative adversarial network (GAN)architecture,with an optimized feature fusion strategy that significantly enhances the network's capability in handling multi-resolution data.Experiments conducted on a comprehensive dataset,comprising both spaceborne and airborne hyperspectral imagery,demonstrate that the proposed method notably improves image quality,outperforming conventional approaches in terms of spatial detail preservation and spectral consistency.Quantitative evaluation using multiple metrics further confirms the robustness and effectiveness of the method.This study provides essential technical support for the enhancement and application of hyperspectral remote sensing imagery,offering important theoretical and practical value. Reference | Related Articles | Metrics

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Comparative analysis of undifferenced and uncombined precise point positioning performance for BDS-3 dual-frequency data ZHOU Mingduan, CUI Likun, MENG Mingzhi, XIE Qianlong, LI Yueyao, SONG Qiao, YU Runxin Bulletin of Surveying and Mapping    2025, 0 (8): 48-54,61.   DOI: 10.13474/j.cnki.11-2246.2025.0808 Abstract （300）      PDF（pc） （1737KB）（80）       Knowledge map    Save In view of the fact that BDS-3 broadcasting B1I/B3I/B1C/B2a signals and the comparative analysis of PPP positioning performance for the current B1I+B3I and B1C+B2a data is still relatively scarce.In this paper,based on the establishment of the BDS-3 undifferenced and uncombined PPP positioning model,an implementation flowchart of integer ambiguity fixed algorithm for BDS-3 undifferenced and uncombined PPP is decuced in detail.The BDS-3 undifferenced and uncombined PPP positioning analysis software (short as UDUC_PPP)using C/C++programming language based on Visual Studio 2022 development platform is designed and developed applied to compare and analyze the positioning performance of BDS-3 undifferenced and uncombined PPP for B1I+B3I and B1C+B2a data.Supported by BDS-3 B1I/B3I/B1C/B2a signals from fourteen representative stations with globally distributed in the MGEX experimental network for 060 d for 24 hours consecutive observation data in 2024 are selected for the positioning performance analysis,the results show that the convergence time and the positioning accuracy of BDS-3 undifferenced and uncombined PPP fixed resolution are better than the float resolution positioning for not only B1I+B3I data but also B1C+B2a data,in which the integer ambiguity resolution success rate is 92.5%above after the positioning convergence for BDS-3 undifferenced and uncombined PPP for both of B1I+B3I and B1C+B2a data,meanwhile the positioning accuracy of BDS-3 undifferenced and uncombined PPP fixed resolution is better than 0.9 cm in the horizontal-RMSE and 2.3 cm in the point-RMSE respectively.For both float resolution and fixed resolution,BDS-3 undifferenced and uncombined PPP positioning in terms of convergence time for B1C+B2a data is better than for B1I+B3I data,which the positioning accuracy is basically comparable. Reference | Related Articles | Metrics