Table of Content

11 May 2026, Volume 55 Issue 4

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Coastal and Marine Surveying, Mapping, and Remote Sensing

A review of intertidal topography reconstruction methods: current status, challenges and trends

Peng LI, Jiahan ZHANG, Zhihan WANG, Houjie WANG, Zhenhong LI

2026, 55(4):  571-587.  doi:10.11947/j.AGCS.2026.20260037

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As the core interface for the coupling of terrestrial and marine processes, the intertidal zone exhibits significant spatiotemporal complexity in topographic evolution driven by periodic tidal cycles. Accurate acquisition of high-accuracy and high-resolution topographic data remains a critical challenge in coastal monitoring due to physical constraints such as vegetation interference, poor accessibility of tidal flats, and periodic submergence. This paper provides a systematic review of intertidal topographic reconstruction methods based on multi-source platforms, including satellite, airborne, shipborne, and ground-based systems, and analyzes research progress under complex environmental conditions. Furthermore, it examines the limitations of existing Digital Elevation Models (DEMs) regarding spatial coverage, vertical accuracy, temporal resolution, and the unification of land-sea vertical datums. By identifying technical bottlenecks in current achievements, this study aims to provide a reference for constructing robust topographic inversion models and discusses emerging trends in multi-source collaborative sensing, data-physics dual-driven modeling, and the development of dynamic digital twin systems.

SAR high-precision inversion of sea surface current over offshore China

Hongmei WANG, Lihua WANG, Benhua TAN, Xiaoyi JIANG, Lili SONG, Weiwei SUN

2026, 55(4):  588-603.  doi:10.11947/j.AGCS.2026.20250444

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Sentinel-1 synthetic aperture radar (SAR) level-2 radial velocity (RVL) products have significantly enhanced the capacity to monitor and quantify mesoscale and sub-mesoscale ocean current features. However, challenges remain in large-scale, high-precision SAR current mapping and systematic multi-source validation within the complex dynamic systems of offshore China. To address these issues, this study performed non-geophysical and geophysical error corrections on all Sentinel-1 RVL data covering offshore China in 2021, generating a high-precision monthly surface current monitoring product. Furthermore, multi-source data, including in-situ station observations, hybrid coordinate ocean model (HYCOM) reanalysis, and Himawari-8(H-8) derived currents, were utilized to systematically evaluate the stability, applicability, and structural characterization capabilities of SAR-derived currents. The results indicate significant spatial heterogeneity in current velocity across offshore China, characterized by the highest velocities in the South China Sea, followed by the East China Sea, and the lowest in the Bohai and Yellow Seas. Current directions are primarily governed by the East Asian monsoon, exhibiting a typical monsoon-driven circulation pattern: overall northward/northeastward in winter and reversing to northward/northeastward in summer. Validation shows that SAR currents achieve good consistency with in-situ data, with a mean bias of 0.08 m/s and a correlation coefficient of 0.58. Compared to HYCOM and H-8 products, SAR is more sensitive to localized high-speed flows and sub-mesoscale structures, enabling a refined depiction of complex flow fields. The high-precision mapping and multi-source validation framework established in this study effectively enhances current monitoring capabilities in complex coastal environments and provides a scientific basis and technical support for the operational application of SAR ocean current products.

Multi-scene analysis of mangrove soil spectral response characteristics and inversion of soil organic carbon content based on measured full-spectrum hyperspectral data

bolin FU, Keyue HUANG, Yanli YANG, Weiwei SUN, Zhaoyin WANG

2026, 55(4):  604-617.  doi:10.11947/j.AGCS.2026.20250393

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Mangroves, as an important component of the coastal ecosystem, the determination of soil organic carbon (SOC) content within them is of great significance for evaluating the carbon storage capacity of the coastal ecosystem. At present, research on mangrove soil is relatively scarce both at home and abroad. To address the issues of unclear spectral characteristics of mangrove soil and the difficulty in exploring SOC sensitive spectral subdomains, this study innovatively proposed the continuous wavelet spectral similarity angle (CSS) analysis method to systematically analyze the spectral response mechanism of mangrove soils. It also developed the soil sensitive spectral subdomain capture (CT-2DCOS) method to achieve accurate extraction of sensitive spectral subdomains for soil organic carbon (SOC) across multiple scenarios. Using in-situ full-band hyperspectral data (350~2500 nm) as the data source, this study combined the aforementioned methods to investigate the spectral reflection mechanisms of mangrove soils under three scenarios (different depths, tree species, and habitats), and further developed an adaptive ensemble learning (AEL) model to complete high-precision inversion of SOC content under these three scenarios. On this basis, it quantified the degree of influence of the three scenarios on SOC content via factor analysis and revealed the intrinsic correlations between mangrove SOC content and depth, tree species, and habitat by integrating significance tests. The results showed that: ① The soil spectra in the 400~800 nm band interval exhibited significant correlations with mangrove SOC content, among which the linear correlation between the spectra around 600 nm and SOC content was more prominent.②The sensitive spectral subdomains of soils at different depths were mainly concentrated in the 350~800 nm band, those of soils under different tree species were dominated by the 600~900 nm band, while those of soils in different habitats were distributed in two band intervals (350~900 nm and 1500~2200 nm).③The AEL model effectively achieved high-precision inversion of SOC content. Among the 42 inversion schemes, the coefficient of determination (R²) ranged from 0.46 to 0.98 within the 0~60 cm soil depth range, the 0~10 cm soil layer showed the optimal SOC inversion effect (R²=0.96), and this layer also had the highest SOC content, accounting for 25.05%; among the 5 mangrove tree species, the soil under Bruguiera sexangula forests exhibited the best SOC inversion effect (R²=0.97) and the highest SOC content, accounting for 27.16%; among the 3 habitats, the near-natural restoration area had the highest SOC inversion accuracy, with SOC content accounting for 45.24%. This study systematically clarifies the spectral response mechanism of mangrove soil under different scenarios, accurately captures its SOC diagnostic spectral bands, and achieves high-precision inversion of SOC content. Among them, the mining of the diagnostic spectral bands of mangrove soil can precisely match the bands of satellite images, providing scientific support for the hyperspectral remote sensing estimation of blue carbon in the coastal zone under large-scale and multi-scenario conditions.

An Euler embedding and complementary feature modeling framework for hyperspectral change detection in coastal wetlands

Lanxin WU, Jiangtao PENG, Weiwei SUN, Bing YANG

2026, 55(4):  618-631.  doi:10.11947/j.AGCS.2026.20250409

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Coastal wetlands are vital ecosystems for maintaining ecological balance and mitigating climate change, and their dynamic monitoring relies heavily on remote sensing technologies. With abundant spectral information, hyperspectral remote sensing can accurately identify subtle differences in wetland surface features, providing essential data support for ecosystem protection and resource management. However, existing hyperspectral change detection methods based on convolutional neural networks are limited by their local receptive fields, making it difficult to capture long-range dependencies effectively. Although Transformer-based methods possess global modeling capability, they often fail to adequately distinguish between changed and unchanged information in change detection tasks, thereby constraining overall detection performance. To address this issue, this paper proposes an Euler embedding and complementary feature modeling method (EECFM) for hyperspectral change detection in coastal wetlands. The proposed method consists of three core modules. First, an Euler-transformation-based spatial-spectral feature extraction module (ETSS) jointly models images from horizontal, vertical, and spectral channel dimensions, fully exploiting the complementarity between spatial structures and spectral information. Second, a bi-temporal image similarity enhancement module (BSE) employs cosine similarity to extract invariant features, while a Scharr-based differential attention module (SDA) leverages Scharr operators in both horizontal and vertical directions to capture fine-grained differences, thereby improving the discriminability of change regions. Finally, a multi-stage loss function is designed: in the initial stage, cross-entropy is adopted to ensure stable convergence, and in the subsequent stage, a class-reweighted Focal loss is integrated with cross-entropy to enhance robustness to long-tailed classes and improve sensitivity to change regions. The experimental results on three representative wetland remote-sensing datasets demonstrate that EECFM delivers superior accuracy and robustness in change detection, providing a technical pathway for dynamic wetland monitoring under complex environmental conditions.

Multi-dimensional spatiotemporal monitoring and analysis of tidal flats in the Maowei Sea using integrated optical remote sensing and SAR

Ertao GAO, Jing LIU, Shujin LI, Guoqing ZHOU, Bolin FU, Shuxian LI

2026, 55(4):  632-646.  doi:10.11947/j.AGCS.2026.20250412

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Tidal flats are transitional areas where land meets the sea and play a crucial role in maintaining the health of coastal ecosystems and in sequestering blue carbon. With the challenges posed by global sea-level rise, increased human activities, and frequent natural disasters, there is an urgent need for effective monitoring and analysis of the spatial and temporal distribution, as well as the surface deformation, of tidal flats. This study focuses on the coastal zone of Maowei Sea in the Beibu Gulf, China. By integrating Sentinel-2 imagery from 2015 to 2023 with low-tide Sentinel-1 imagery and various other data sources, including sea-level changes, precipitation, and hydrological variations, the following investigations were conducted: ① Employing the Google Earth Engine (GEE) cloud platform, this study used time-series Sentinel-2 imagery along with the enhanced mangrove vegetation index (EMVI), normalized difference water index (NDWI), the maximum spectral index composite (MSIC) algorithm, and Otsu's method (OTSU). This approach successfully identified intertidal flats within the study area. Results demonstrated an overall accuracy of 96.6% and a Kappa coefficient of 0.92, confirming the reliability of this identification method. The tidal flat area in Maowei Sea decreased from 19.98 km² in 2016 to 15.80 km² in 2023, a 20.9% reduction. Land use types shifted from tidal flats to mangrove forests, construction land, and other categories. ② A deformation extraction method termed “PS+SBAS-InSAR” was developed, incorporating partial permanent scatterers (PS) into small baseline subset synthetic interferometric aperture radar (SBAS-InSAR) technology to monitor tidal flat deformation. Results show that between 2015 and 2023, the surface deformation rates on the tidal flats ranged from－54.72 mm/a to 41.71 mm/a. During this period, 98.77% of the area experienced deformation rates between－20 mm/a and 20 mm/a, and 84.62% of the area had rates between－10 mm/a and 10 mm/a, indicating overall stable ground deformation. The most significant subsidence was observed at Mangrove Bay, with a cumulative total of－308.21 mm, while the highest uplift occurred at Kangxi Ridge, with a cumulative total of 311.90 mm. The tidal flats of Maowei Sea show uneven deformation patterns, mainly characterized by slight uplift. Specifically, subsidence occurs along both banks of the Jianshan River and in Hongshu Bay, while uplift is observed at Kangxi Ridge and in the northwestern part of Jianshan. Irregular uplift and subsidence patterns are evident along both banks of Longmen Qishierjing. ③ Comprehensive analysis of multiple data sources shows that precipitation, hydrological movement, sea-level rise, and mangrove changes are the main factors affecting tidal flat surface deformation. Sea-level rise is negatively related to this deformation. Precipitation and extreme-weather patterns are seasonal, while mangrove dynamics, sea-level rise, and coastal aquaculture have long-term effects.

An automated seamount detection method integrating vertical gravity gradient anomaly and seafloor topographic models

Yi GAO, Xin LIU, Daocheng YU, Shaoshuai YA, Shaofeng BIAN, Heping SUN, Jinyun GUO

2026, 55(4):  647-657.  doi:10.11947/j.AGCS.2026.20250319

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The accurate, global-scale detection of seamounts is of significant importance to the Earth sciences. While traditional shipborne bathymetry methods are costly and have limited coverage, satellite altimetry provides an effective means for identifying seamounts on a global scale. This study proposes an automated seamount detection method that integrates vertical gravity gradient anomalies (VGGAs) and bathymetric models. The method begins by preprocessing the VGGA data with a Gaussian filter to identify local maxima, which are treated as potential seamount centers. Subsequently, closed VGGA contours generated around these centers are subjected to a rigorous screening process based on multiple constraints: area (>50 km²), VGGA amplitude (>12 E), shape fidelity (circular/elliptical fitting errors <10%/15% and a Jaccard index >0.6), and spatial location (excluding continental slopes and their 20 km buffer zones). For regions with complex topography, a marker-controlled watershed algorithm is employed to segment the VGGA signal, after which each subregion is screened independently using the same criteria. Finally, for the candidate regions that pass the screening, the seamount's basal depth is determined by automatically identifying the foot of the slope within the GEBCO_2024 data. This identification is achieved by analyzing the first and second derivatives of bathymetric profiles, enabling an accurate estimation of the seamount's height. Applied to the South China Sea and its surrounding regions, the method identified 278 seamounts taller than 100 m, achieving a 98% spatial match with the SIO 2023 global seamount catalog. Furthermore, our study identified 109potential, previously uncatalogued seamounts. Comparisons with ship-based data demonstrated a root mean square error (RMSE) of 354.4 m in height estimates, validating the method's effectiveness and reliability. This method offers robust technical support for enhancing the global seamount database and advancing related marine research.

A topographic photon extraction method for intertidal zones using ICESat-2 satellite altimeter data

Hao XU, Nan XU, Huichao XIN, Yue MA, Wei TU, Qingquan LI

2026, 55(4):  658-672.  doi:10.11947/j.AGCS.2026.20250419

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To overcome the limitations of traditional intertidal topographic extraction methods, including limited spatial coverage, high costs, and difficulty in maintaining accuracy under complex environments, this study proposes a topographic photon extraction method for intertidal zones using ICESat-2 satellite altimeter data. Focusing on typical tidal flats and sandy beaches, photon-counting LiDAR data acquired by the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) are used, together with OpenStreetMap (OSM) sandy beach masks and the GWL_FCS30 tidal flat mask, to construct spatial prior constraints for photon confidence screening and type-based zoning. Addressing the characteristic differences between different geomorphic types, scenario-specific extraction strategies are designed. In tidal flat areas, seawater photon removal, skeleton seed extraction, and robust outlier elimination are integrated, and an elliptically shaped density-based spatial clustering of applications with noise (DBSCAN) clustering with adaptive orientation is introduced to accommodate the anisotropic features of gentle slopes and tidal creeks. In sandy beach areas, the ordering points to identify the clustering structure (OPTICS) algorithm based on reachability distance sequences is adopted, and the clustering scale is determined using an Otsu adaptive threshold to adapt to the strongly fluctuating photon density distribution. The results show that the proposed method maintains high extraction accuracy across multiple complex intertidal environments. On the overall validation dataset, the method achieves a Precision of 0.99, a Recall of 0.91, anF₁-score of 0.95, and a Kappa coefficient of 0.90. Further topographic consistency analysis indicates that, at the overall scale, the extracted results differ from reference data by approximately 0.01 m in mean elevation, 0.83 m in elevation range, and 0.46° in slope, demonstrating that the extracted photons can effectively represent intertidal topographic characteristics. This study provides a feasible approach for the application of ICESat-2 data in large-scale, high-precision intertidal topographic monitoring and supports coastal zone management, erosion and accretion assessment, and coastal wetland studies.

Improved latitude difference method for calculating crossover point position from wide-swath measurement data

Chengcheng ZHU, Zhen LI, Jinyun GUO, Maosheng ZHOU, Wanqiu LI

2026, 55(4):  673-683.  doi:10.11947/j.AGCS.2026.20250341

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The wide-swath sea surface height (SSH) data obtained by the SWOT satellite are of great significance for improving the resolution of the ocean gravity field. Compared with traditional altimeter data, wide-swath two-dimensional data increases the time consumption for calculating crossover points. Therefore, the improved latitude difference method for calculating crossover points is proposed. The size and position of the crossover area are determined based on different latitudes, and then crossover point position within this area are calculated. Compared with other methods, the proposed approach identifies crossover points accurately while requiring only 20% of the time needed by the latitude difference method. In addition, the accuracy of SWOT SSHs was analyzed by using the SSH discrepancies at crossover points. Compared with Level 2 products, Level 3 SSH products show an accuracy improvement of more than 90%. The accuracy of Level 2 SSH products is lower at the edge of the crossover area than elsewhere, whereas Level 3 products exhibit no obvious spatial distribution pattern within the crossover area. Overall, the improved latitude difference method effectively improves the calculation efficiency of the crossover point.

Geodesy and Navigation

Construction of an empirical model for estimating the global wave period of spaceborne GNSS-R

Jinwei BU, Shuhui LIU, Shunshuang XU, Tongsu XIANG, Qiulan WANG, Chaoying JI, Xiaoqing ZUO

2026, 55(4):  684-697.  doi:10.11947/j.AGCS.2026.20250239

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Wave period is one of the important parameters of ocean waves, usually obtained by backscatter coefficient and significant wave height (SWH) using satellite altimeters. However, due to the long revisit period and signal attenuation during heavy rain, this method is difficult to meet the needs of dynamic changes. Spaceborne global navigation satellite system reflectometry (GNSS-R) provides a new method for wave period estimation, but currently there is little research on wave period estimation, and there is a lack of reliable estimation models in complex marine environments. Therefore, on the basis of existing scattering theory, this article proposes a method for constructing a wave period estimation model for spaceborne GNSS-R by systematically sorting out the physical and mathematical relationship between the spaceborne GNSS-R observables and the wave parameters (SWH and wave period). Using spaceborne GNSS-R data and ERA5 data under low wind speed (<10 m/s) and high wind speed (>10 m/s) sea conditions, empirical linear models and power function models were proposed for the relationship between wave period, SWH, and GNSS-R observables. And using ERA5, WW3, Jason-3, and buoy wave period data as references, verify the performance of the proposed model in estimating wave periods. The experimental results show that the wave period estimation accuracy of normalized bistatic radar cross-section (NBRCS) observable is slightly better than leading edge slope (LES) observable, and the three parameters power function model is slightly better than the linear model and the two parameters power function model. Compared with existing models, the proposed model can improve root-mean-square error (RMSE), correlation coefficient (CC), and mean absolute percentage error (MAPE) by up to 16.44%, 13.33%, and 12.65%, respectively. Furthermore, it shows good agreement with different validation datasets under both low and high wind speed conditions. Comparative analysis between proportional division validation and 5-fold cross validation shows that the model proposed in this article has both good generalization ability and stable model structure, which fully demonstrates the high reliability of the model.

Buoys-aided integrated navigation method for UUV under ice with sea ice drift compensation

Siyuan BAI, Hongzhou CHAI, Qing WU, Gen LI, Yuhao YE, Honglei MA

2026, 55(4):  698-707.  doi:10.11947/j.AGCS.2026.20260028

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To address the problem that the measurement values of the upward-looking Doppler velocity log (DVL) are significantly affected by sea ice drift when unmanned underwater vehicle (UUV) navigate under ice, a buoy-aided integrated navigation method for UUV under ice is proposed. Firstly, a sea ice drift motion model is established to clarify the coupling mechanism of sea ice drift on UUV velocity measurements. Secondly, the measurement error equations of each sensor considering sea ice drift are derived in detail, and the Kalman filter models for the UUV inertial navigation/upward-looking DVL integrated navigation assisted by single-buoysanddouble-buoysareconstructedrespectively. Finally, simulation experiments are designed. The results show that, in the single-buoy-aided mode, the proposed algorithm effectively suppresses the systematic errors induced by sea ice drift, achieving a positioning error reduction of 81.96% over the traditional SINS/upward-looking DVL integrated navigation method ignoring sea ice drift errors. In the dual-buoy-aided mode, by leveraging baseline motion information, the algorithm enables accurate estimation of sea ice drift errors, further reducing positioning error by 93.29% compared to traditional method. This provides an effective solution for long-endurance, high-precision UUV navigation under ice.

Improved baseline method for time-variable gravity field recovery

Xiaolei YANG, Yun XIAO, Liqing YANG, Xiaodong HONG, Enze GUO, Han WANG

2026, 55(4):  708-720.  doi:10.11947/j.AGCS.2026.20250515

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To address the challenge of suppressing high-frequency errors in high-precision time-variable gravity field inversion, this paper investigates and develops the baseline method. An improved baseline inversion model is constructed by introducing a decorrelation method to optimize observation error processing and adopting a short-term time-variable parameter estimation strategy to enhance time-variable signal capture capability. The study focuses on comparing its performance with the traditional short-arc method in terms of spectral response and noise control. Based on 2021 GRACE-FO real data, monthly gravity field models up to degrees 60, 96, and 120 are derived. Results indicate that in the low-frequency band (below degree 30), both methods achieve comparable accuracy. However, in the mid-to-high frequency range (above degree 30), the improved baseline method significantly outperforms the short-arc method; notably, its cumulative geoid height error at degree 120 is reduced by approximately 8 cm, demonstrating superior capability in suppressing high-frequency noise. Furthermore, the model derived from the improved baseline method (referred to as the Baseline model) is validated against the CSR RL06.3 model released by Center for Space Research, University of Texas at Austin, the HUST-Grace2024 model released by Huazhong University of Science and Technology, and the Tongji-Grace2022 model released by Tongji University. The comparison reveals that the Baseline model achieves better overall accuracy above degree 60. The global equivalent water height derived from the Baseline model exhibits a more reasonable spatial distribution with less striping noise. Specifically, its RMSE over the ocean is significantly lower than that of the CSR RL06.3, HUST-Grace2024, and Tongji-Grace2022 models, and its signal-to-noise ratio is superior to these models, demonstrating optimal high-frequency noise suppression capability. The study concludes that the improved baseline method, through the combined enhancements of decorrelation processing and short-term time-variable parameterization, effectively improves the accuracy and stability of gravity field models in mid-to-high frequency bands, providing an effective approach for constructing high-resolution and high-reliability time-variable gravity field products.

Century-scale projection of terrestrial water storage anomaly and drought risk in the Poyang Lake Basin using a CMIP6-driven Transformer-GRU model

Yang LI, Haijun HUANG, Sulan LIU, Xiaohui WU, Qi LIU, Qipei PANG, Yunlong WU

2026, 55(4):  721-738.  doi:10.11947/j.AGCS.2026.20260016

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The impact of drought on human society is becoming increasingly severe, making accurate prediction of future terrestrial water storage anomaly (TWSA) data crucial for water resource management and drought monitoring. This study integrates GRACE/GRACE-FO satellite observations, reconstructed long-term TWSA data, and CMIP6 multi-scenario climate model outputs to forecast future TWSA in the Poyang Lake Basin. To precisely capture the complex response relationship between climate drivers and water storage changes, we propose a hybrid Transformer-GRU model driven by climate factors. The model employs a customized cross-attention module that takes the current TWSA state as the guiding query to compute attention weights for precipitation, air temperature, and potential evapotranspiration (PET), together with their lagged terms, and then fuses these variables according to the learned weights to form an integrated climate signal for TWSA prediction, thereby achieving dynamic weighting and effective coupling of multi-source climate drivers. The model, validated through rolling-window cross-validation and independent testing, demonstrated reliable predictive accuracy (correlation coefficientr=0.87, RMSE=5.17 cm during the independent test period). Based on the prediction results, the water storage deficit index (WSDI) for the Poyang Lake Basin was calculated to assess the evolution of drought risk under different emission scenarios. The results indicate that under the high-emission SSP5-8.5 scenario, both the frequency and intensity of droughts are significantly higher than under the SSP2-4.5 scenario, revealing an elevated risk of intensified hydrological drought in the Poyang Lake Basin under a high-emission pathway. This research provides a credible technical solution for effective, century-scale TWSA forecasting with limited observational data, offering a scientific reference for water resource adaptation strategies in the Poyang Lake Basin.

Cartography and Geographic Information

Intelligent design of terrain visualization for online maps

Xini HU, Mengjun KANG, Liang GE, Shiliang SU, Min WENG

2026, 55(4):  739-752.  doi:10.11947/j.AGCS.2026.20250523

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Terrain visualization is a core component of map services for representing landforms and surface characteristics. However, existing terrain visualization methods are often highly specialized and poorly adapted to diverse application scenarios, which limits their ability to meet the growing demands of map services. This study proposes a multi-agent 3D terrain visualization method, in which the terrain design process is decomposed into a hillshade agent (HSAgent), a color-relief agent (CRAgent), and a evaluation agent (EAgent). The proposed method supports user intent analysis, cartographic strategy reasoning, iterative self-optimization, and online visualization output in a coordinated workflow. Case tests were carried out in preset scenes and free scenes, covering generative and revised tasks, and subjective visual evaluation and scene matching questionnaire survey were carried out for verification. The results show that this method can realize the rapid design of terrain style, which is superior to the style generated by ArcGIS Pro in visual performance and functional support, and has good generalization effect in different scenarios. It provides an efficient and versatile technical path for online terrain visualization.

Summary of PhD Thesis

Research on high-available visible light intelligent positioning technology

Xiansheng YANG

2026, 55(4):  753-753.  doi:10.11947/j.AGCS.2026.20240424

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Research on pedestrian indoor and outdoor positioning based on smartphone multi-sensor fusion

Jijun GENG

2026, 55(4):  754-754.  doi:10.11947/j.AGCS.2026.20240425

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Research on key technologies for reconstructing building models with multi-LODs using point clouds

Zexin YANG

2026, 55(4):  755-755.  doi:10.11947/j.AGCS.2026.20240436

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Tropospheric corrections augmented PPP-AR: theory, methods and the application in aviation navigation

Hongyang MA

2026, 55(4):  756-756.  doi:10.11947/j.AGCS.2026.20240437

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Generalized similarity feature-based robust matching of multi-modal remote sensing images

Yongxiang YAO

2026, 55(4):  757-757.  doi:10.11947/j.AGCS.2026.20240438

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Research on low-latitude ionospheric scintillation monitoring and forecasting methods using ground-based GNSS and space-borne GNSS-R observations

Hang LIU

2026, 55(4):  758-758.  doi:10.11947/j.AGCS.2026.20240445

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Study on the spatiotemporal distribution of sporadic E layers based on GNSS radio occultation

Haifeng LIU

2026, 55(4):  759-759.  doi:10.11947/j.AGCS.2026.20240446

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Research on key technologies of global localization using multisource geo-referenced point cloud

Dong XU

2026, 55(4):  760-760.  doi:10.11947/j.AGCS.2026.20240460

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