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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 Abstract （1405）   HTML （471）    PDF（pc） （3633KB）（1620）       Knowledge map    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

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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 Abstract （1054）   HTML （113）    PDF（pc） （1832KB）（402）       Knowledge map    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

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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 Abstract （991）   HTML （139）    PDF（pc） （6221KB）（866）       Knowledge map    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

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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 Abstract （948）   HTML （174）    PDF（pc） （3104KB）（304）       Knowledge map    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

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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 Abstract （728）   HTML （47）    PDF（pc） （6662KB）（312）       Knowledge map    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

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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 Abstract （715）   HTML （530）    PDF（pc） （1847KB）（1213）       Knowledge map    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

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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 Abstract （701）   HTML （93）    PDF（pc） （14201KB）（504）       Knowledge map    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

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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 Abstract （638）   HTML （77）    PDF（pc） （2825KB）（489）       Knowledge map    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

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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 Abstract （617）   HTML （40）    PDF（pc） （1853KB）（442）       Knowledge map    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

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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 Abstract （607）   HTML （76）    PDF（pc） （9549KB）（587）       Knowledge map    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

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Multi-label scene classification method based on fusion of SAR and optical remote sensing images Yiming ZHAO, Kelin HU, Kelong TU, Yaxian QING, Chao YANG, Kunlun QI, Huayi WU Acta Geodaetica et Cartographica Sinica    2025, 54 (5): 911-923.   DOI: 10.11947/j.AGCS.2025.20240281 Abstract （558）   HTML （28）    PDF（pc） （6463KB）（269）       Knowledge map    Save Deep convolutional neural networks have proven to be one of the most effective methods for scene classification of high-resolution remote sensing images. Most previous studies focus on scene-level classification of single optical remote sensing images and are primarily limited to single-label classification. However, single optical remote sensing images are often constrained by weather conditions, and single-label annotations cannot fully describe complex image contents. Therefore, in this paper, we constructed a multimodal, multi-label scene classification dataset called SEN12-MLRS, using SAR and optical remote sensing images acquired by the European Space Agency in 2020. We proposed a parallel dual attention fusion network (PDANet) for multi-label scene classification. PDANet achieves optical and SAR image feature extraction as well as multi-modal and multilevel feature fusion through two-branch feature extraction, adaptive feature fusion, and multilevel feature fusion. Experimental results demonstrate that PDANet achieves superior performance compared to many state-of-the-art models on the SEN12-MLRS dataset. The effectiveness of the proposed network and its modules is further validated through ablation experiments. Table and Figures | Reference | Related Articles | Metrics

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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 Abstract （525）   HTML （78）    PDF（pc） （3680KB）（474）       Knowledge map    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

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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 Abstract （501）   HTML （54）    PDF（pc） （3891KB）（339）       Knowledge map    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

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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 Abstract （497）   HTML （35）    PDF（pc） （9371KB）（348）       Knowledge map    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

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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 Abstract （470）   HTML （708）    PDF（pc） （4666KB）（1108）       Knowledge map    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

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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 Abstract （468）   HTML （83）    PDF（pc） （4381KB）（519）       Knowledge map    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

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A method for satellite ultra-rapid orbit and clock offset estimation based on the prior information of the GNSS clock parameters Qianxin WANG, Chao HU, Tong CHENG Acta Geodaetica et Cartographica Sinica    2025, 54 (6): 982-994.   DOI: 10.11947/j.AGCS.2025.20240451 Abstract （458）   HTML （22）    PDF（pc） （6705KB）（183）       Knowledge map    Save GNSS ultra-rapid orbit and clock products are widely used in the area of real-time and near-real-time fast location-based services. However, due to the restriction of time-consuming and observations quality in the parameters estimation, the correlation between orbit and clock offset parameters in ultra-rapid determination is not considered. In addition, the merits of satellite onboard clock information is ignored. Therefore, in this research, an improved ultra-rapid orbit and clock estimation method is proposed based on the prior constraint on the GNSS clock parameters. First, the time-difference carrier phase algorithm is used to epoch-wisely update the satellite clock offset by fixing satellite orbit. Second, the short-term prediction model of clock offset is constructed to extract the prior information and model the satellite onboard atomic clock parameters. Third, the augmented model of ultra-rapid orbit and clock offset is constructed by the constraint of satellite onboard clock parameters in orbit determination equation. According to the experiment results, it is indicated that the significant correlation among orbit and clock offset parameters is presented, in which the accuracy of ultra-rapid clock offset can be improved with 30.9%~50.7%, compared with the traditional ultra-rapid clock products by fixing the orbit parameters. Meanwhile, the millimeter-level and at least 32.9% for orbit and clock offset accuracy improvements can be obtained by the prior constraint on clock parameters. Additionally, the performances of static PPP solution are respectively improved with 9.9%, 16.9% and 9.3% for E, N and U directions, compared with the traditional ultra-rapid orbit and clock products. Therefore, the proposed GNSS satellite orbit and clock offset method can effectively improve the performances of ultra-rapid products, which will further provide supporting for the high-quality PNT services. Table and Figures | Reference | Related Articles | Metrics

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Analysis of the spatio-temporal evolution and driving factors of urban ecological quality based on long-term Landsat image time series Yonggang GAO, Yuting LIU, Hanqiu XU Acta Geodaetica et Cartographica Sinica    2025, 54 (3): 510-522.   DOI: 10.11947/j.AGCS.2025.20240147 Abstract （445）   HTML （45）    PDF（pc） （9345KB）（266）       Knowledge map    Save Analyzing the spatio-temporal evolution of urban ecological quality and its driving factors is crucial for regional environmental protection and sustainable development. This paper presents a robust analytical framework for urban ecological quality evaluation based on multi-temporal Landsat satellite remote sensing imagery and auxiliary data. The framework integrates the remote sensing ecological index (RSEI) with Theil-Sen estimation, Mann-Kendall trend test, Hurst index, optimal parameters-based geographical detectors (OPGD), and multi-scale geographically weighted regression (MGWR). To verify its applicability and effectiveness in the context of rapid urbanization, this framework was used to investigate ecological quality changes and influencing factors in Dongguan city over the past 20 years. The results show that Dongguan's ecological environment has undergone a complex dynamic process of deterioration-improvement-re-deterioration during the 20-year period. Furthermore, forward-looking predictive analysis identified key areas of future ecological change and regions facing severe ecological risks as well as those with significant improvement potential. This comprehensive analysis provides scientific support for ecological management in Dongguan and offers valuable insights for similar regions undergoing rapid urbanization. Table and Figures | Reference | Related Articles | Metrics

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Assessment of GNSS ionosphere models based on FY-3 TEC in polar regions Yang SHEN, Guangyun LI, Mingjian CHEN, Linyang LI, Xingyu SHI, Wei CAI, Weifeng HAO Acta Geodaetica et Cartographica Sinica    2025, 54 (6): 995-1008.   DOI: 10.11947/j.AGCS.2025.20240202 Abstract （433）   HTML （21）    PDF（pc） （7804KB）（122）       Knowledge map    Save In view of the lack of detailed reference for the correction accuracy of the existing ionospheric model in the polar region, especially in the polar region where GNSS monitoring stations are lacking, the correction effects of GPS Klobuchar, Galileo NeQuickG, BeiDou-3 BDGIM and IGS GIM models in the polar region were evaluated based on the ionospheric TEC observations of Fengyun satellite in the Arctic and Antarctic in 2021 and 2023. The correction accuracy of four ionospheric models in the whole polar region, different places and different latitudes is analyzed respectively. The results show that the correction effect of the four ionospheric models in the Arctic is better than that in the Antarctic. The model deviation and standard deviation of the high solar activity year 2023 are significantly larger than those of the low solar activity year 2021. The RMS values of Klobuchar, NeQuickG, BDGIM and GIM models are 11.30, 5.74, 6.75 and 4.40 TECu, respectively, and the correction percentages are 33.34%, 58.81%, 44.87% and 65.32%, respectively. The correction percentages of GIM and NeQuickG fluctuate less with local time, while the correction percentages of BDGIM and Klobuchar change greatly with local time, and reach the maximum at 12:00—16:00 pm. The RMS value of Klobuchar fluctuates violently with latitude, which is basically not suitable for ionospheric correction in high latitudes. The RMS values of NeQuickG, BDGIM and GIM models change little with latitude, and the correction percentage generally decreases with the increase of latitude. Table and Figures | Reference | Related Articles | Metrics

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Wide area coastal subsidence monitoring and driver analysis with multi tracks of TS-InSAR—a case study of Shandong province Peng LI, Jianbo BAI, Zhenhong LI, Houjie WANG Acta Geodaetica et Cartographica Sinica    2025, 54 (7): 1178-1191.   DOI: 10.11947/j.AGCS.2025.20250061 Abstract （431）   HTML （30）    PDF（pc） （13186KB）（180）       Knowledge map    Save Coastal subsidence will exacerbate relative sea level rise and increase the risk of flood-related coastal infrastructure inundation and soil salinization. As a major economic province in the east coast of China, the coastline of Shandong accounts for about 1/6 of the country. However, the spatiotemporal evolution characteristics and key drivers of land subsidence in Shandong are still unclear. In this paper, we conducted multi-track radar interferometry (InSAR) time series analysis with the Sentinel-1 imagery from 2019 to 2022. Firstly, we proposed a multi-track InSAR uncontrolled splice method applicable to the interface region between land and sea to correct the systematic bias of interferograms from adjacent tracks. Then, we generated a large-scale land subsidence rate map of the whole province with good consistency. Furthermore, we found multiple sinking funnels over 50 mm/a. Based on Sentinel-2 multispectral remote sensing images, deformation time series and principal component analysis, we revealed the spatiotemporal change of the heterogeneous sedimentation funnel and its drivers. The results show that human activities related to groundwater pumping and coal mining are the main factors causing land subsidence in Shandong province. This study is expected to provide technical support and scientific basis for large-scale coastal subsidence monitoring and risk management, and further improve the understanding of coastal geological disaster risk. Table and Figures | Reference | Related Articles | Metrics