Most Down Articles

    Published in last 1 year| In last 2 years| In last 3 years| All| Most Downloaded in Recent Month | Most Downloaded in Recent Year|

    Published in last 1 year
    Please wait a minute...
    For Selected: Toggle Thumbnails
    Large language model-driven GIS analysis: methods, applications, and prospects
    Huayi WU, Zhangxiao SHEN, Shuyang HOU, Jianyuan LIANG, Anqi ZHAO, Haoyue JIAO, Zhipeng GUI, Xuefeng GUAN
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 621-635.   DOI: 10.11947/j.AGCS.2025.20240468
    Abstract1405)   HTML471)    PDF(pc) (3633KB)(1620)       Save

    The rapid development of large language models (LLMs) provide a new approach for GIS analysis, leading to the large language model-driven GIS analysis technical architecture (LLM4GIS). Based on the latest research up to October 2024, this paper reviews the evolution of GIS analysis and summarizes the LLM4GIS technical architecture from 3 aspects: application modes, datasets and evaluation methods. It also summarizes the research progress of LLM in GIS analysis tasks such as knowledge question-answering, knowledge extraction, spatiotemporal reasoning, and analyzing and modeling. Finally, the paper prospects the future research directions of GIS4LLM in 5 aspects: collaborative understanding of multimodal spatio-temporal data, balancing generalization with depth, enhancing interpretability and credibility, transitioning to embodied intelligence and edge intelligence, and the development of intelligent and universal GIS analysis. This paper provides inspiration for achieving mutual empowerment between LLM4GIS and GIS4LLM.

    Table and Figures | Reference | Related Articles | Metrics
    A survey on cloud removal in optical remote sensing images: progress, challenges, and future works
    Xinchang ZHANG, Ji QI, Chao TAO, Siyang FU, Mingning GUO, Yongjian RUAN
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 603-620.   DOI: 10.11947/j.AGCS.2025.20230137
    Abstract715)   HTML530)    PDF(pc) (1847KB)(1213)       Save

    Optical remote sensing images (RSIs), which are widely used in various Earth observation tasks due to its rich geoinformation, are often significantly affected by varying degrees of cloud contamination, leading to a significant reduction in data quality and usability. Although extensive research has been conducted on cloud removal from optical RSIs, there is still a lack of systematic review and analysis in this field. To address this gap, this paper first employs bibliometric analysis to investigate the publication trends of relevant literature both domestically and internationally, revealing the long-term development dynamics of cloud removal research in RSIs. Subsequently, the paper then provides a comprehensive and systematic review of research on the removal of thin and thick clouds, thoroughly analyzing the core challenges, underlying assumptions, approaches, and fundamental principles of different cloud removal methods, while evaluating their strengths and weaknesses. Finally, this paper summarizes and discusses the common key challenges and future trends in current optical remote sensing cloud removal research. This paper not only offers crucial insights for readers to fully understand the research progress in optical remote sensing cloud removal over the past three decades but also serves as a valuable reference for grasping the development patterns and trends in this field.

    Table and Figures | Reference | Related Articles | Metrics
    Singular value decomposition normalization prediction method for non-steady landslide displacement
    Wei QU, Rongtang XU, Jiuyuan LI, Xingyou TANG, Peinan CHEN
    Acta Geodaetica et Cartographica Sinica    2025, 54 (9): 1647-1663.   DOI: 10.11947/j.AGCS.2025.20240463
    Abstract469)   HTML708)    PDF(pc) (4666KB)(1108)       Save

    The reasonable establishment of high-precision landslide displacement prediction model has important reference value for landslide disaster prevention and early warning. In this study, a simple normalization method based on singular value decomposition is developed for the current data-driven landslide displacement prediction model, which has a strong dependence on the amount of data and limitations in dealing with the distributional drift characteristics of non-stationary landslide displacement monitoring data. This method can effectively solve the distribution drift problem of non-stationary landslide displacement data by segmentally normalizing the landslide displacement monitoring data and then combining the statistical characteristics of the extrapolation model for the inverse normalization process, and does not need to rely on large-scale data training, which can significantly improve the prediction ability of the prediction model for non-stationary landslide displacement. Tests with measured data of Heifangtai landslide in Gansu, a typical landslide domain in China, show that compared with the traditional z-score normalization method and no normalization, the method developed in this study can significantly improve the prediction accuracy of multi-class models, such as (multi-layer perceptron MLP), (long short-term memory LSTM), (gated recurrent unit GRU), and (temporal convolutional network TCN), and the average enhancement rate of (root mean square error RMSE) and (mean absolute error MAE) is more than 50%. The method in this study can significantly improve the stability of the model training process, effectively predict the sudden change of landslide displacement, and has a high value of practical popularization and application.

    Table and Figures | Reference | Related Articles | Metrics
    Satellite gravity technology oriented towards data-scenario-model driven approach: developments, challenges and outlook
    Jiancheng LI, Yunlong WU, Yibing YAO, Zhicai LUO
    Acta Geodaetica et Cartographica Sinica    2025, 54 (9): 1537-1560.   DOI: 10.11947/j.AGCS.2025.20250274
    Abstract991)   HTML139)    PDF(pc) (6221KB)(866)       Save

    Satellite gravimetry, as a major breakthrough in modern geodesy, has demonstrated strong capabilities in capturing mass variations in the Earth's surface and subsurface layers. It has been widely applied in critical fields such as geodetic surveying, hydrological cycle monitoring, glacier mass balance, sea level change, and tectonic deformation. This study systematically reviews the evolution of gravity satellite missions from CHAMP and GRACE to GRACE-FO and Chinese gravity satellite programs, with a particular focus on next-generation satellite gravimetry missions and emerging trends in quantum-based gravity satellite concepts. Based on this, the study comprehensively summarizes the data processing pipeline from Level-0 to Level-3, key inversion methodologies, and science product development. Application cases are presented across hydrology, cryosphere, oceanography, seismology, and geoid refinement. Furthermore, major challenges in China's current gravimetry application system are identified, including data quality limitations, multi-source signal separation, lack of interpretability in AI-based models, and barriers to interdisciplinary integration. Finally, the study calls for synergistic innovation driven by “data-scenario-model” integration to support multi-satellite networks and high-precision modeling in service of national strategic needs and global sustainable development.

    Table and Figures | Reference | Related Articles | Metrics
    Deep learning methods for remote sensing intelligent change detection: evolution and development
    Jixian ZHANG, Haiyan GU, Huan NI, Haitao LI, Yi YANG, Shaopeng DING, Songman SUI
    Acta Geodaetica et Cartographica Sinica    2025, 54 (8): 1347-1370.   DOI: 10.11947/j.AGCS.2025.20240417
    Abstract606)   HTML76)    PDF(pc) (9549KB)(587)       Save

    The rapid development of multimodal remote sensing and deep learning technologies has expanded the data and method dimensions of remote sensing change detection, laying the foundation for more automated, refined, and intelligent change detection. This article focuses on change detection based on deep learning, addressing two fundamental scientific issues: change feature expression and network learning strategies, and detailing the evolution of change detection research. In terms of change feature expression, there are four research trends: from local to global and spatiotemporal integration, from single modality to multimodality, from lightweight models to large models, and from binary to multi-category semantic feature expression. In terms of network learning, there is a development trend from fully supervised to weak/semi-supervised to unsupervised change detection. Based on this, the article discusses the current challenges faced by deep learning-based change detection and, in conjunction with the development trends of artificial intelligence technology, points out three development directions: text-image fusion, generative, and human-computer collaborative modes. This aims to provide direction and ideas for theoretical methods and application research, and to enhance the intelligence and application level of remote sensing change detection.

    Table and Figures | Reference | Related Articles | Metrics
    On the development of surveying and mapping in the era of artificial intelligence
    Deren LI, Mi WANG, Wenbin SHEN, Qingyun DU, Shuo WANG
    Acta Geodaetica et Cartographica Sinica    2025, 54 (12): 2107-2115.   DOI: 10.11947/j.AGCS.2025.20250438
    Abstract468)   HTML83)    PDF(pc) (4381KB)(519)       Save

    Against the backdrop of rapid advances in artificial intelligence and the surging demand for spatio-temporal information applications, spatio-temporal intelligence, a new discipline integrating surveying, navigation, remote sensing, and artificial intelligence (AI) has emerged. Leveraging intelligent sensors for communication, navigation, and remote sensing, cloud computing, and AI technologies, it enables intelligent perception, cognition, and decision support for natural and human activities, with a focus on promoting sustainable development. Surveying and mapping plays a core supporting role, requiring the construction of a four-dimensional spatio-temporal reference frame to ensure the accuracy of spatio-temporal information, the development of “fast, accurate, and agile” intelligent processing technologies to address massive data challenges, and the enhancement of spatio-temporal information comprehension efficiency through multi-dimensional dynamic visualization. The “National One Map” project serves as a typical paradigm for the practical implementation of spatio-temporal intelligence theory. Relying on the Oriental Smart Eye constellation and Tianditu (national geospatial information public service platform), it promotes the unified application of spatio-temporal information in government affairs, public services, and commercial sectors, achieving dynamic updates and intelligent analysis. In the future, spatio-temporal intelligence will deepen its theoretical system, improve the theories of spatio-temporal reference frame construction and data processing, integrate cutting-edge AI technologies, facilitate global spatio-temporal information sharing, provide more precise decision support for urban governance, environmental protection, and other fields, and contribute to the construction of a community with a shared future for mankind.

    Table and Figures | Reference | Related Articles | Metrics
    The design and implementation of the open geospatial engine (OGE)
    Jianya GONG, Peng YUE, Longgang XIANG, Haoru WU, Kaixuan WANG, Ruixiang LIU, Baoxin TENG
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 587-602.   DOI: 10.11947/j.AGCS.2025.20250051
    Abstract701)   HTML93)    PDF(pc) (14201KB)(504)       Save

    The construction of new spatiotemporal information infrastructure relies on innovative software middleware and geographic information service models. Driven by cloud computing, artificial intelligence, and big data, traditional spatiotemporal data infrastructure is evolving from data services to intelligent computing services. This paper focuses on a spatiotemporal intelligent computing service platform, aiming to develop a Digital Earth Cube-ready service. It explores key technologies in organizing, computing, and reasoning with geospatial big data, and develops the open geospatial engine (OGE) system, which deeply integrates computing power, data, and algorithms while promoting openness and sharing. The system provides a data-ready, analysis-ready, and decision-ready geospatial data-information-knowledge service framework, forming an open geospatial engine (OGE) and establishing a new type of spatiotemporal information infrastructure based on spatiotemporal cube management and geospatial big data analysis. Based on this foundation, an OGE prototype system has been developed, integrating various types of Earth observation data accumulated by Wuhan University and related institutions. A series of typical spatiotemporal analysis experiments covering raster, vector, and thematic data were conducted, validating OGE's capabilities in managing and analyzing geospatial big data.

    Table and Figures | Reference | Related Articles | Metrics
    Prospects for the development of deep space navigation technologies
    Gang LI, Fang XIE, Yifan WU, Jun LU, Shuren GUO, Yingchun LIU, Chengeng SU, Xiaoheng YANG
    Acta Geodaetica et Cartographica Sinica    2025, 54 (3): 397-409.   DOI: 10.11947/j.AGCS.2025.20230493
    Abstract637)   HTML77)    PDF(pc) (2825KB)(489)       Save

    Deep space navigation is a fundamental element ensuring the efficient implementation of all kinds of deep space missions. With the substantial increase in the number of cislunar and Mars missions, as well as the great extension in distance of interplanetary missions, the entire process of spacecraft cruise, flyby, orbiting, descent landing, and surface activities pose increasingly higher demands for navigation. The traditional methods, such as deep space network, are hard to fulfill the requirements for multi-task, real-time and autonomous navigation. The main characteristics of deep space missions are analyzed, such as increasing in number, focusing on Moon and Mars, transforming from exploration to development and extending in distance. The paper summarizes three typical navigation requirements for cislunar transfer space, the outer space and surface of planets (like Moon and Mars), and ultra-far deep space. Then the paper studies the characteristics and trends of currently in-use, available and potential technologies. Moreover, the suggestions for the development of deep space navigation technology are proposed, including continuously improving the performance of in-use technologies, actively promoting the experimental deployment of available technologies, and strengthening the fundamental research of potential technologies. This study can provide reference for the technical development in the field of deep space navigation.

    Table and Figures | Reference | Related Articles | Metrics
    Intelligent methods for 3D terrain reconstruction of the Moon and near-Earth planets: a review of current advances and future perspectives
    Xiaohua TONG, Rong HUANG, Jiarui CAO, Chen LIU, Rong WANG, Yusheng XU, Zhen YE, Yanmin JIN, Shijie LIU, Sicong LIU, Yongjiu FENG, Huan XIE
    Acta Geodaetica et Cartographica Sinica    2025, 54 (11): 1917-1933.   DOI: 10.11947/j.AGCS.2025.20250337
    Abstract525)   HTML78)    PDF(pc) (3680KB)(473)       Save

    3D terrain reconstruction of extraterrestrial bodies is a core element of deep space exploration, providing essential spatial information for landing site selection, rover navigation, and resource exploration. Traditional techniques—such as photogrammetry, photoclinometry, and laser altimetry interpolation—have been extensively applied to the Moon, Mars, and asteroids, achieving significant progress in building high-precision terrain models, interpreting geomorphological features, and supporting resource prospecting. However, these methods remain constrained by limited imaging conditions, the absence of reliable control references, and the complexity of terrain and illumination, often resulting in issues such as low data quality, difficult feature matching, missing observations, and limited automation. In recent years, artificial intelligence (AI) techniques—including convolutional neural networks (CNNs), generative adversarial networks (GANs), attention-based models (Transformers), and neural radiance fields (NeRF)—have shown growing potential in extraterrestrial 3D reconstruction. This review synthesizes three major AI-driven approaches: ①Feature extraction and image matching. ②Depth estimation from single-view images. ③Radiance field modeling from multi-view observations. We further compare their underlying mechanisms, representative applications, applicable scenarios, and performance characteristics. Finally, we outline key technical challenges and discuss future directions in multi-source data fusion, self- and weakly supervised learning, foundation models, and real-time processing, aiming to foster broader applications of AI in extraterrestrial 3D terrain reconstruction.

    Table and Figures | Reference | Related Articles | Metrics
    China's National 3D Mapping Program (3DRGLM): overall architecture and key technological issues
    Jun CHEN, Haibo TIAN, Yin GAO, Yuanjie ZHANG, Wanzeng LIU, Hao WU, Hongwei ZHANG, Wei HUANG, Jianjun LIU
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 636-649.   DOI: 10.11947/j.AGCS.2025.20240115
    Abstract616)   HTML40)    PDF(pc) (1853KB)(442)       Save

    China has launched recently its national 3D mapping program to build 3D realistic geospatial landscape model (3DRGLM), and has been considered as an important step towards establishing Digital China and transforming our geospatial industry. It is a huge spatio-temporal information engineering with many complex technical and management factors, and is becoming a challenging task for governmental agencies and academy societies. The paper has introduced the motivation and fundamental concepts of the 3DRGLM, i.e., moving from traditional 2~2.5D cartographic products to 3D realistic geospatial landscape products, from simple data supply to spatio-temporal empowerment, from digital to intelligentized mapping. The overall architecture of national 3DRGLM was then proposed and it has a number of key components, such as the data product system for generating geospatial entities, geospatial scenes and realistic geospatial scenes, the service system designed to support spatio-temporal connection, computing, and intelligence, as well as its digital-intelligentized hybrid technological support system. The 3DRGLM has some special key technological issues, including geospatial entity modeling, stereo reconstruction of muti-dimensional real space, realistic description and geospatial temporal knowledge service. Finally, this paper discussed five typical application scenarios of 3DRGLM, including application of 3DRGLM in digital economy, digital governance, digital living, digital culture, and digital ecological civilization. In order to achieve a successful establishment and an in-depth application of national 3DRGLM, it is necessary to carry out strategic planning, enhance scientific and technological innovation and promote cross-border and multi-disciplinary collaboration.

    Table and Figures | Reference | Related Articles | Metrics
    The development and key technologies of quantum PNT
    Yuanxi YANG, Xia REN, Qiang ZHANG, Mingqiang HOU, Dingbang XIAO, Lingxiao ZHU
    Acta Geodaetica et Cartographica Sinica    2026, 55 (1): 1-9.   DOI: 10.11947/j.AGCS.2026.20251218
    Abstract417)   HTML64)    PDF(pc) (1718KB)(431)       Save

    Quantum positioning, navigation and timing (quantum PNT) technology is an interdisciplinary field integrating quantum physics, quantum sensing and self-perception navigation, and quantum timing. Quantum PNT sensors represent a crucial development direction for autonomous PNT terminals characterized by covert, continuous, and robust. The definition and the concept as well as the connotation of quantum PNT are given. The relationship with exist PNT systems, including satellite-based PNT, comprehensive PNT system, resilient PNT, and intelligent PNT etc. are discussed. The significance quantum PNT system is described. Also, the current development status and existing problems of quantum PNT are sorted out, and the research content and key technologies of quantum PNT are mainly analyzed. The quantum PNT development directions are divided into supply side and application side. Key development directions for the supply side are to tackle issues such as the quantum PNT integrated principle and uncertainty control. In the supply side, the integration of quantum sensors and comprehensive PNT terminals should be concentrated, especially the development of chip-based quantum PNT sensors and the miniaturization integration of multiple-principle PNT terminals. The manuscript aims to provide a new approach for secure PNT, trusted PNT, and autonomous PNT services.

    Table and Figures | Reference | Related Articles | Metrics
    Research progress and key issues in spatial grid interoperability
    Xuesheng ZHAO, Wenlan XIE, Wenbin SUN
    Acta Geodaetica et Cartographica Sinica    2025, 54 (10): 1727-1740.   DOI: 10.11947/j.AGCS.2025.20250070
    Abstract409)   HTML94)    PDF(pc) (4313KB)(403)       Save

    Spatial grids have excellent features such as discreteness, hierarchy, and regularity, making it an ideal framework for constructing realistic 3D scenes. Efficient interoperability among different types of grids is one of the key issues for achieving multi-source heterogeneous data fusion and analysis. This paper first reviews the current research progress in grid interoperability, including the general latitude and longitude middleware method and the “isomorphic” and “heterogeneous” grid encoding mapping conversion methods. It then analyzes the key issues in the interoperability process, pointing out the inherent difficulty of heterogeneous grids in overcoming the challenge of non-coplanarity, the lack of interoperability methods for both 3D grids and spatiotemporal grids, and the lack of a comprehensive reliability evaluation system and control methods for interoperability. Finally, the paper discusses future research directions, suggesting a focus on “grid points”, exploring unified underlying descriptions of grids to build a foundation model for interoperability, developing efficient mapping algorithms for “heterogeneous” grid encoding to address efficiency bottlenecks, expanding grid interoperability dimensions to support the construction of 3D reality China and establishing an “uncertainty” evaluation system for grid interoperability to ensure the quality and reliability of interoperability.

    Table and Figures | Reference | Related Articles | Metrics
    Theoretical foundation of gravity field and improvement of classical concepts for geodetic height datum unified in the terrestrial reference system
    Chuanyin ZHANG, Tao JIANG, Baogui KE
    Acta Geodaetica et Cartographica Sinica    2025, 54 (9): 1561-1571.   DOI: 10.11947/j.AGCS.2025.20250102
    Abstract1054)   HTML113)    PDF(pc) (1832KB)(402)       Save

    The current theory of geodetic height datum were mainly established during the era of traditional terrestrial geodesy, and have difficulty adapting to the rapid development of the Earth's gravity field and satellite geodesy. This paper strictly follows the principles of geometric and physical geodesy and the uniqueness and precise measurability requirements of geodetic elements and concepts, and deduces the theoretical and logical relationship among the height datum, the terrestrial reference system and the gravity field concisely and clearly by conducting scientific research on the theoretical foundations and implementation principles necessary for unifying the elements of physical geodesy into the terrestrial reference system, and then re-examines some classical concepts of the height datum. The paper presents the following main results and their specific geodetic evidences. ①It is demonstrated that whether it is the orthometric height, normal height or geopotential number system, the height starting datum surface is the geoid if the deformation of the geoid is ignored, and it is pointed out that the analytical orthometric height is more suitable for the purpose of the height datum than other types of orthometric heights. ②The theoretical foundation of the gravity field for the geodetic height datum unified in the terrestrial reference system is improved, and the geodetic datum conditions and technical implementation principles for the GNSS replacing leveling technology are derived. ③The theoretical method of Earth's center of mass and shape polar positioning based on space geometric and physical geodesy is derived. Which neither relies on geophysical assumptions or geodynamic protocols, nor on the principle of earth rotation and its dynamics, but rather realizes scientifically the positioning and orientation of the terrestrial reference system only based on the theory of geodesy. ④It is demonstrated that the surfaces of orthometric equi-height are parallel to the geoid and the normal gravity field can be fully determined with only three parameters. Thus the trouble of coordination and consistency between the geoid defined by the Gaussian convention and the gravity geoid has been effectively solved.

    Table and Figures | Reference | Related Articles | Metrics
    Smart city logical framework and digital-twin platform technical requirements
    Renzhong GUO, Biao HE, Zhigang ZHAO, Xiaoming LI, Xi KUAI, Haojia LIN, Yebin CHEN, Ding MA
    Acta Geodaetica et Cartographica Sinica    2025, 54 (5): 777-784.   DOI: 10.11947/j.AGCS.2025.20240001
    Abstract429)   HTML80)    PDF(pc) (2439KB)(390)       Save

    Cities are open, complex, and dynamically changing “nature-society” mega-systems, where various functional and structural subsystems continuously interact and influence one another, forming the inherent logic of urban operations. Smart cities present viable solutions to address the broad systemic issues within urban areas. However, the traditional vertical coupling architecture, despite its self-sufficiency, has failed to align effectively with urban operational logic, resulting in numerous “data islands” and “information silos” that impede the process of high-quality urban development. This article adopts an urban system perspective, grounded in the developmental needs of smart cities in the information and communication technology (ICT) era. It proposes a lateral coupling system architecture that facilitates joint construction and sharing for smart city development from theoretical, technological, and methodological standpoints. Furthermore, the study seeks to clarify the concept of the urban system from a philosophical perspective and to identify the key technical requirements for a digital twin platform, thereby providing guidance for the engineering practice and innovative application of smart cities.

    Table and Figures | Reference | Related Articles | Metrics
    Consistency analysis of GNSS precise orbit and clock products based on globally unified coordinate frame
    Xuexi LIU, Shouqing ZHU, Guo CHEN, Kefei ZHANG, Nanshan ZHENG, Jingxuan LIU
    Acta Geodaetica et Cartographica Sinica    2025, 54 (3): 432-447.   DOI: 10.11947/j.AGCS.2025.20240248
    Abstract497)   HTML35)    PDF(pc) (9371KB)(348)       Save

    Precise satellite orbit and clock offset are the key to fast fixing undifferenced ambiguity and achieving high-precision positioning services. The combination of orbit and clock offset product requires the unification of the spatial and temporal references between products from different analysis centers. This paper first solved for the Bursa coordinate transformation parameters to analysis the difference of similar transformation parameters between the precise satellite orbit products provided by different analysis centers, and statistically calculated the correlation coefficient between the similar transformation parameters of each system of analysis centers. Secondly, the benchmark differences of the precise clock products are analyzed and it is found that there is a significant constant bias in the linear transformation by estimating a set of linear transformation parameters using the clock data of all the satellites. The GPS and Galileo have a constant deviation of up to 200 ps, while the constant deviation of the GLONASS and BDS can reach 1000 ps and 2400 ps respectively. In this paper, we propose a method to eliminate this constant bias by estimating a set of linear transformation parameters for each satellite clock. Thirdly, this paper analyses the benchmark consistency between the orbital and station coordinates and the Earth's rotation parameter products. The correlation coefficients of most of the rotational components are more than 0.5, which indicates that the orientation benchmark differences are more consistent among the analysis centers. Finally, the consistency of orbit and clock is analyzed by making the double difference of orbit and clock. After removing the constant deviation of clock, most of the correlation coefficients of the double difference of orbit and clock of GPS and Galileo are more than 0.9, and the correlation coefficients of GLONASS and BDS are a little bit worse but the correlation coefficients also exceed 0.6. This indicates that the nonlinear parts of the second difference between the precision satellite orbits and the clock products are more consistent, showing a high degree of conformity between orbital changes and clock variations.

    Table and Figures | Reference | Related Articles | Metrics
    A general method for determining the key parameters of GNSS water vapor tomography modeling
    Qingzhi ZHAO, Duoduo JIANG, Hongwu GUO, Zufeng LI, Chen LIU, Yibin YAO
    Acta Geodaetica et Cartographica Sinica    2025, 54 (3): 410-421.   DOI: 10.11947/j.AGCS.2025.20240293
    Abstract501)   HTML54)    PDF(pc) (3891KB)(339)       Save

    The existing global navigation satellite system (GNSS) water vapor tomography is mostly empirically selected in the determination of key parameters such as tomography height, vertical stratification, horizontal step size, etc., and lacks a general determination method, resulting in large differences in tomography results and difficulty in realizing the application of general water vapor tomography results. Because of this situation, this study proposes a theoretical method for determining the generality of key parameters of GNSS water vapor tomography to solve the problem that the optimal modeling parameters cannot be determined in the process of water vapor tomography. Firstly, the principle of determining the optimal height of the tomographic region by combining the vertical layered profile data and the water vapor density threshold is proposed. Secondly, the optimal vertical resolution determination method based on the equal weight principle of vertical stratified water vapor is proposed. Thirdly, considering the information on station density and satellite cut-off elevation angle, the optimal horizontal step size determination method based on the idea of joint grid coverage maximization and non-uniform symmetric horizontal grid division is developed. The data of 12 GNSS stations and 1 radiosonde station in Hong Kong from May 1 to 14, 2013 were selected for experiments. Compared with the existing classical methods, compared with radiosonde data, the average improvement rate of the retrieved water vapor density profile is 12%. Compared with the slant water vapor (SWV) calculated by the fifth-generation reanalysis dataset (ERA5) released by the European Centre for medium range weather forecasts (ECMWF), the average improvement rate of SWV obtained by the proposed scheme is 29.5%.

    Table and Figures | Reference | Related Articles | Metrics
    Reflections and practices in 3D realistic geospatial scene geographic entity modeling
    Jiping LIU, Tingting ZHOU, Po LIU, Shenghua XU, Yong WANG, Liang ZHAI, Zhuolu WANG, Junjie QI, Menghe MA
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 650-660.   DOI: 10.11947/j.AGCS.2025.20240422
    Abstract356)   HTML16)    PDF(pc) (7585KB)(339)       Save

    Geographic entity modeling is a central task and crucial component in 3D realistic geospatial scene reconstruction of China. It involves the abstraction and digitization of real-world geometric spaces, along with its associated attributes and relationships, to generate 3D realistic geospatial scene model. Firstly, geographic entity modeling techniques and methods are thoroughly considered and summarized from the perspective of the construction and application in the 3D realistic geospatial scene of China. The evolution of geographic entity modeling is outlined across three stages: two-dimensional plane, three-dimensional surface, and 3D realistic geospatial scene. Secondly, this paper elaborates on the connotation and extension of the 3D realistic geospatial scene geographic entity modeling. Reviewing research progress in geographic entity modeling, including geometric modeling, attribute modeling, relationship modeling, and temporal modeling in geographic entities. Then, taking the temporal management for geographic entities and the application of spatiotemporal association techniques as examples, the application of 3D realistic geospatial scene geographic entity modeling is presented. Finally, this paper explores future directions for 3D realistic geospatial scene geographic modeling technology, focusing on cross-domain collaborative interaction fusion modeling, pan-spatial integrated and unified modelling, multi-granularity panoramic association modelling, and adaptive intelligent temporal modeling.

    Table and Figures | Reference | Related Articles | Metrics
    The technological advancements in 3D mapping abroad
    Jun ZHU, Jianlin WU, Zhilin LI, Yukun GUO, Jigang YOU, Yakun XIE, Weilian LI
    Acta Geodaetica et Cartographica Sinica    2025, 54 (4): 661-674.   DOI: 10.11947/j.AGCS.2025.20240186
    Abstract326)   HTML16)    PDF(pc) (8750KB)(329)       Save

    3D modeling is one of the core technologies in the digital earth, and it plays a significant role in the development of digital cities, digital earth, and digital economies. Currently, many countries have initiated various 3D modeling projects to support natural resource management, urban planning, emergency response, and sustainable development. At the same time, these projects have also promoted the development of 3D modeling technology. This article analyzes the research and application of 3D mapping across different countries, focusing on four aspects: “needs assessment” “tasks” “technologies” and “applications” based on the fundamental definitions and connotations of 3D mapping. By summarizing and analyzing typical 3D modeling engineering, products, technology, standards, and applications in these regions, the article explores insights into the construction of 3D realistic geospatial scene in China and provides references and insights for the development of realistic model projects domestically.

    Table and Figures | Reference | Related Articles | Metrics
    A dynamic weighted fusion SLAM method using multi-source sensor data in complex underground spaces
    Xiaohu LIN, Xin YANG, Wanqiang YAO, Hongwei MA, Bolin MA, Xiongwei MA
    Acta Geodaetica et Cartographica Sinica    2025, 54 (3): 523-535.   DOI: 10.11947/j.AGCS.2025.20230586
    Abstract728)   HTML47)    PDF(pc) (6662KB)(312)       Save

    Simultaneous localization and mapping (SLAM) is pivotal for autonomous detection, automatic inspection, and emergency rescue in underground spaces. However, the challenges of narrow and long tunnels, complex terrain, and uneven illumination in underground spaces make LiDAR point cloud and visual image matching highly susceptible to degradation. This, in turn, results in insufficient accuracy or even failure of SLAM when fusing multi-sensor data. To address this challenge, we propose a dynamic weighted fusion SLAM method for multi-source sensor data with enhanced robustness. First, during the visual image preprocessing stage, an image enhancement technique based on the hue, saturation, and value (HSV) color space is employed. This method combines single-parameter homomorphic filtering with contrast limited adaptive histogram equalization (CLAHE) to effectively enhance the brightness and contrast of the image. This improvement strengthens the robustness of visual odometry. Next, the data quality of each sensor is evaluated using a Mahalanobis distance consistency test, which analyzes potential data degradation and adaptively selects the most suitable sensor data for fusion based on the current scene. Finally, considering the key parameters of each sensor, we construct the multi-source sensor factor graph model. The dynamic combination of multi-source sensor data weights is then formed according to the data quality model, allowing for the dynamic adjustment of the weight of each sensor data fusion factor. To verify the effectiveness of the proposed method, experiments were conducted in typical underground spaces such as underground corridors, excavated subway tunnels, and coal mine tunnels using self-designed and integrated mobile robots. Qualitative and quantitative comparative analyses were performed against various state-of-the-art methods. The results demonstrate that the maximum root mean square error (RMSE) of the proposed method is only 0.19 m. The average cloud to cloud (C2C) distance is less than 0.13 m, referencing the point cloud acquired by high-precision terrestrial 3D laser scanning. Additionally, the constructed point cloud maps exhibit superior global consistency and geometric structure authenticity. These findings confirm that the proposed method offers higher accuracy and robustness in complex underground spaces.

    Table and Figures | Reference | Related Articles | Metrics
    Monitoring method of Earth's center of mass, figure pole and various rotational dynamics parameters
    Chuanyin ZHANG, Wei WANG, Tao JIANG
    Acta Geodaetica et Cartographica Sinica    2025, 54 (7): 1157-1169.   DOI: 10.11947/j.AGCS.2025.20250141
    Abstract948)   HTML174)    PDF(pc) (3104KB)(304)       Save

    The Earth's center of mass and figure pole are geodetic datum for describing and measuring the rotation of the Earth. The inability to accurately measure mass redistribution within the Earth's interior and geomaterial motion results in more uncertainties in geophysical excitations estimated from geophysical fluid data, thereby limiting in-depth investigations into the rotational dynamics of the Earth. In this paper, various geodetic measurements and Earth rotation motion are unified in an only Earth-fixed reference system, and the effects of Earth's figure polar shift and rotation variation on various geodetic elements are investigated. And then a time-synchronized monitoring methodology for Earth's figure pole and various rotational dynamic parameters is present by multi-geodetic collaboration, which can provide more favorable scientific and technological conditions for the in-depth study of the excitation dynamics mechanism of the Earth's rotation and the interaction of the Earth's spheres. The paper presents the following main results. ① The theoretical method for positioning of Earth's center of mass and figure pole is derived by space geometric and physical geodetic collaboration, which can not only accurately measure the variation time series of Earth's center of mass and figure pole, but also position and orient the current terrestrial reference system to the mean center of mass and mean figure pole in a specified time period. ② This paper presents the monitoring algorithms of the Earth's center of mass, figure pole and various rotational dynamics parameters by collaborating with the Earth's satellite observation, VLBI kinematics measurement, and the site's radial placement and gravity variation observations, which can improve the constraints of the study on the mechanism of the Earth's rotational dynamics.

    Table and Figures | Reference | Related Articles | Metrics