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Display Method:
A Multi-mouted PDR Algorithm Based on Wearable MEMS Sensors State Recognition
Real Time Localization and Mapping Integrating Multiple Prism LiDARs/IMU/RTK on Railway Locomotive
Pedestrian Indoor and Outdoor Seamless Positioning Technology and Prototype System Based on Cloud-End Collaboration of Smartphone
Review and Verification for Brain-Like Navigation Algorithm
Performance Analysis of Ionospheric Enhanced PPP-RTK in Different Latitudes
Evaluation of Arctic Sea Ice Concentration Estimated by Fengyun-3D Microwave Radiation Imager
Analysis of Semi-tightly Coupled Multi-GNSS PPP-RTK/VIO for Vehicle Navigation in Urban Areas
Reinforcement Learning Based End-to-End Autonomous Driving Decision-Making Method by Combining Image and Monocular Depth Features
Design and Implementation of Cloud Positioning System for Massive Intelligent Terminals
On the Accuracy and PPP Performance Evaluation of the Latest Generation of Real Time Tropospheric Mapping Function
An Underwater Array Localization Method Using Two-Stage Learning Model
A New RAIM Algorithm Based on the Density Center of Observed Dataset
An Improved Shadow Matching Method for Smartphone Positioning
Extrinsic Calibration Method for LiDAR and Camera with Joint Point-Line-Plane Constraints
Adaptively CDF Matching Method in GNSS-R Wind Speed Retrieval
Ultra-rapid Orbit Determination of GLONASS Satellite After Ambiguity is Fixed
High Accuracy Differential Positioning with Smartphone GNSS Raw Measurements
Articles online first have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
Types of Potential Landslide and Corresponding Identification Technologies
A Denoising Method for GNSS Time Series Based on GAVMD and Multi-Scale Permutation Entropy
Combinations of the simplex and weighted distance-based grey wolf algorithms for the seismic source parameter inversion with GPS measurements
Establishment of Vertical Movement Model of Chinese Mainland by Fusion Result of Leveling and GNSS
A Registration method of remote sensing image and vector data using Mask R-CNN
Analysis of Reflected Signals During GPS Radio Occultation Observations of COSMIC Products in China
Source Parameters and Slip Distributions of the 2016 and 2022 Menyuan,Qinghai Earthquakes Constrained by InSAR Observations
Integrated GB-SAR Images and Terrain Data for Emergency Deformation Monitoring Assisted by Point Clouds
An Algorithm for Ambiguity Resolution of BDS Undifferenced and Uncombined Long-range Reference Stations
Spatial non-stationary response of the tradeoff/synergy between ecosystem services to influencing factors in ecological functional areas——A case study of Fujian province
Assessment of Position Performance of BDS for Space Application Based on FY-3D Satellite
Landslide Detection and Segmentation Using Mask R-CNN with Simulated Hard Samples
Study on Recognizing the Penguin Population in UAV Image Based on Object Otiented Classification
Potential Contribution from Tianwen-1 Extended Mission to Mars Low-Order Gravity Field
Characteristics of the Computer Game Map
Application of EM Algorithm in the Parameter Estimation of P-norm Mixture Mode
The Research on the Tensor Invariant Method for Determining the Earth Gravity Field from Satellite Gravitational Gradient Data
The Multi-scale Edge Detection of Potential Field Using the BEMD and Wavelet Modulus Maximum Method
Symbolic Expressions of Difference Between Auxiliary and Reduced Latitudes
Application of the Harmonic Model with Variable Coefficients to Polar Motion Prediction
A Multi-scale Adaptive Slope Filtering Algorithm of Point Cloud
A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling
Boundary Identification and Extraction of Fault Structure in South China Sea Using Full Tensor Gravity Gradient Combinations
Simulated Analysis of EOP Measurement Accuracies with participation of Chinese VGOS Stations in International Observations
SBAS GEO Satellite User Range Error and Position Augmentation Research
Short-term Prediction for Polar Motion Based on Chaos and Volterra Adaptive Algorithm
Application of EMD in GNSS Time Series Periodic Term Processing
Accuracy Assessment of Multi-frequency and Multi-GNSS Velocity Estimation With Time Differenced Carrier Phase Method
Analyzing Disparity of Regional Development in Pakistan Under Perspective of Night-Time Light Remote Sensing
Spatial Scan Statistic Method for Discovering Regional Network Co-location Patterns
The Identification of Secondary Craters based on the Distribution of Iron Element on Lunar Surface
Vehicle Attitude Estimation Model Using Optimized Time-Differenced Carrier Phase
Development of Asteroid Optical Determination Software and Data Processing Analysis
Research on Traffic Lights Timing Optimization and Simulation
Hyperspectral Image Spatial-Spectral Classification Using A Capsule Network Based Method
Soil heavy metal Pb content inversion method by combining field with laboratory spectra
Performance Evaluation of BeiDou-3 Spaceborne Atomic Clock Using Different Time Synchronization Systems
BDS-3/GNSS uncombined precise point positioning
Distributed Visible Query Method for Regional Objects Using Map-Reduce
A Method of Generating and Displaying Trajectory Line Heat Map with GPU Acceleration
A Method of Using Unity3D to Simulate the Whole Process of Three-dimensional Movement of Rockfall
A Probabilistic Prediction Model for Displacement of Super High Arch Dams Considering the Deformation Spatial Association
Spatial and temporal characteristics of AOD and meteorological factors in China during the period of COVID-19
Improved Finite State Machine Step Detection Algorithm for Smartphone
A GNSS/INS Vehicle Integrated Navigation System Based on LSTM-EKF
Trajectory Estimation Analysis and Low Degree Gravity Field Recovery Based on Juno Tracking Data
Dense Optical Flow Method for Intelligently Extracting Mosaic Lines of Orthophotos
Influence of the Element Beampattern on Synthetic Aperture Sonar Imagery
Air Temperature Estimation in Yangtze River Economic Zone Using Geographically and Temporally Neural Networks
Highway slope deformation monitoring based on car-borne dual-antenna InSAR system
Semantic segmentation of point clouds using local geometric features and dilated neighborhoods
A New Data Preprocessing Method for Beidou Satellite Clock Bias
Regional Ionospheric TEC Modeling and Accuracy Analysis Based on Observations from a Station
Signal Quality Analysis and Orbit Accuracy Verification of BDS-3
The Temporal and Spatial Analysis of Land Subsidence in Beijing Plain based on TPCA
Improved YOLOv5 Method for Detecting Shipwreck Target with Side-scan Sonar
Trial and comparative study of some encoder-decoder based deep learning models for the automated generalization of buildings
Research on Oblique Factor Model for Selecting Training Samples
Seasonal Rainstorm and Flood Risk Assessment Method for ImmovableCultural Relics: A Case Study of National Ancient Sites in Fujian Province
A deep learning remote sensing estimation method (UnetR) for regional forest canopy closure combined with UAV LiDAR and high spatial resolution satellite remote sensing data
A Geo-coded Stabilization Approach for Optical Video Satellites in Object Space
Performance Analysis of BDS-3 Multi-frequency Pseudorange Positioning
Intelligent Optimization Learning for Semantic Segmentation of High Spatial Resolution Image
Line Matching Algorithm Based on Pair-wise Geometric Features and Individual Line Descriptor Constraints
Performance Evaluation of BDS-3 PPP-B2b Service
Spatial-temproal variation characteristics and geographic detection mechanism of land subsidence in Wuhan city from 2007 to 2019
An adaptive Voronoi diagrams Algorithm for matching multi-scale areal Residential Areas
Spatiotemporal Interpolation Methods of NPP/VIIRS Sequence Images Considering Neighbor Relationships
Encoding and operation for the aperture 4 hexagonal discrete global grids on uniform tiles
A Method for Constructing Automatically 3D Property Right Cluster of Apartment Buildings
Integrating Sentinel Active and Passive Data to Map Land Cover in a National Park from GEE Platform
GPS receiver differential code bias estimation with the Swarm LEO constellation
Time-varying analysis of backscatter coefficient corresponding to different surface types in the Tibetan Plateau
An Adaptive Terrain Simplification Algorithm Based on Centroidal Voronoi Diagram
A Method to Evaluate Sampling Scheme Adopted in Surveying and Mapping Products' Inspection
Tourism Flow Network Structures of Different Types of Tourists Using Online Travel Notes: A Case Study of Yunnan Province
Research and Application of Gravity Anomaly Spectrum Analysis Method
A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test
Evaluation of Urban Ecological Environment and Its Relationship with Human Activities Based on Multi-Source Data
A Point Cloud Registration Method Based on Dual Quaternion Description Under the Constraint of Point and Surface Features
Establishment of sea-land vertical datum transformation for hydrography with combining geoid, sea surface topography and numerical simulation of tidal wave motion in Yangtze Estuarine waters
Study on Regional Land Surface Temperature Variation on the Influence of the Shrinkage of the Aral Sea Area
Simulation of Spatial Distribution of Monthly Average Precipitation Driven by Temporal Variation Function
Determining the Relative Weight Ratio of Joint Inversion Using Bias-corrected Variance Component Estimation Method
A One-Step Modelling for BeiDou Satellite Observations Multipath Delay Based on Prior Constraints
Multi-level Similarity Sub-segment Matching Method for Spatiotemporal Trajectory
Remote Sensing Monitoring of Agricultural Drought and Vegetation Sensitivity Analysis in the Middle and Lower Reaches of Yangtze River from 2001 to 2019
Smart City Sensing Base Station: An Integrated Sensing Infrastructure for Further Smart Citie
Personal location prediction algorithm taking into account similar user characteristics
A Reference Satellite Image Retrieval Method for Drone Absolute Positioning
Population Spatialization by Considering Pixel-level Attribute Grading and Spatial Association
The Wet Tropospheric Correction of Wide-swath Altimeter using Optimum Interpolation Method
ChangeDetection byMulti-ScaleFuzzyFusionon High Resolution Images
Comprehensive evaluation and comparison of nonlinear inversion about simulated annealing, genetic algorithm and neural network algorithm
Grid Pattern Recognition in Road Networks Using Link Graph
Consistency Evaluation of Land Use Spatial Distribution Pattern Supported by Autocorrelation
Articles just accepted have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
Applications of the UAVs in the Antarctic Scientific Research: Progress and Prospect
LI Teng, ZHANG Baogang, CHENG Xiao, ZHANG Yuanyuan, HUI Fengming, ZHAO Tiancheng, QIN Weijia, LIANG Jianhong, Yang Yuande, LIU Xuying, LI Xinqing
 doi: 10.13203/j.whugis20200098
[Abstract](848) [PDF 1818KB](104)
Abstract:
Unmanned Aerial Vehicle; Antarctic Expedition; Climate Change; Photogrammetry; Glaciology; Ecology; Geomorphology

Start in 1957 Monthly

ISSN 1671-8860

CN 42-1676/TN

中国中文核心期刊

中国科技核心期刊

Ei核心期刊

Special Recommend

DAI Keren

  Objectives  The Sichuan-Tibet railway is not only a state key project in China, but also the most difficult super project in railway construction history due to the most complex terrain and the active geological structure. Interferometric synthetic aperture radar (InSAR) has proved to be a critical tool for detecting and monitoring geohazards because of its wide coverage, high precision, and high efficiency. Howe-ver, due to its side-looking geometry, InSAR faces serious geometric distortions in mountainous areas, particularly in extremely steep high mountain and gorge areas along the Sichuan-Tibet railway.  Methods  Utilizing the full open-access Sentinel-1 data, which has the wide coverage and a short revisiting time, we carry out satellite radar geometric distortion and feasibility analyses along the Sichuan-Tibet railway. Taking into account synthetic aperture radar(SAR) imaging geometry, the variations of the incidence angles across the whole SAR image, and the passive geometric distortions, we present an integrated approach to accurately determine the areas with SAR geometric distortions.  Results  Our results for Sentinel-1 data show that the areas with geometric distortions for observations with a single-orbit (i.e. ascending or descending) reach 31%—35% along the Sichuan-Tibet railway, whilst the geometric distortion areas reduce to 1.5% for observations with both ascending and descending orbits; furthermore, about 35% of the whole area is suitable for joint analyses with both ascending and descending observations.  Conclusions  The quantitative result also reveals the feasibility to use the Sentinel-1 data to detect and monitor geohazards along the Sichuan-Tibet railway from the perspective of geometric distortions. It can not only improve the overall understanding of the applicability of Sentinel-1 based InSAR and the InSAR results interpretation in this area, but also provide a guideline for efficiently selecting other satellite SAR datasets for detecting and monito-ring geological disasters along the Sichuan-Tibet railway.

ZHU Qing

  Objectives  The complex geological conditions in the mountainous areas of western China, with strong internal and external dynamics effects, make catastrophic landslides frequent. The analysis of landslide susceptibility has become a necessary means for scientific early warning and active prevention before disasters.In the traditional landslide susceptibility analysis method, the general calculation accuracy of the single knowledge-driven model is limited, and the weight of the impact factor is highly subjective. The data-driven model also relies too much on the quality and quantity of sample data, and the heterogeneity of the landslide disaster environment is prominent.  Methods  In order to overcome the problems of limited quantity and quality of sample data and large differences in landslide disaster environment, we propose a regional landslide susceptibility method that couples the contribution weight of landslide disaster environmental factors and heuristic knowledge fuzzy logic model. The proposed method uses spatial statistical indicators such as the historical landslide frequency ratio and the information entropy weight of the landslide disaster environmental factors to explicitly describe the contribution and spatial distribution characteristics of the landslide disaster environmental factors, which measures the constraint relationship and the mapping structure between multi-factors and landslides, and realizes multi-factor coupling regional landslide susceptibility.  Results  The experiment selects the disaster-prone areas in Fengjie, Chongqing for verification and evaluation; The results show that the proposed method has a more uniform and reasonable partition area, with an area under curve(AUC) value of 0.854, and the best prediction accuracy, than single information value(IV) model and information value and logistic regression(IVLR) model, which ensures the reliability and accuracy of the method.  Conclusions  The proposed method overcomes the strict requirements of landslide susceptibility analysis on the number of historical observation samples, improves the accuracy of landslide susceptibility analysis through a hierarchical stacking strategy, and provides reliable technical support for the susceptibility analysis of large-scale.

TANG Xinming

  Objectives  Improving the accuracy of block adjustment with few or even no ground control points (GCP) is one of the core issues for high-precision mapping of areas difficult to get GCP, and it is also a major technical difficulty. In order to make full use of the footprint image and the excellent high accuracy of elevation, and the high relative accuracy between the laser altimetry data and stereo images, we propose a combined adjustment method of Gaofen-7 (GF-7) satellite stereo images aided with laser altimetry data.  Methods  In this method, the elevation control points are automatically extracted by registering the laser footprint images and stereo images, and then they are used as the vertical control in the combined adjustment to improve the elevation accuracy.  Results  The combined block adjustment experiments performed in Shandong with different terrains show that using only laser altimetry data as elevation control, the root mean square errors of elevation can be significantly improved from the original 7.97 m to 0.79 m, and the maximum elevation error is better than 1.5 m.  Conclusions  The experimental results reveal that the proposed method can substantially improve the elevation accuracy of satellite imagery. Additionally, with integration of few horizontal control points, the plane accuracy and elevation accuracy can be simultaneously improved. The proposed method is of great significance to reduce the field survey and improve the efficiency of block adjustment.

ZHU Jianjun

Challenges and Development of Data Processing Theory in the Era of Surveying and Mapping Big Data

With the development of information technology, the rise of surveying and mapping big data and artificial intelligence, the lack of data is no longer a problem. However, the existing surveying and mapping data processing technology has been pursuing the accuracy of data (micro), and big data research just allows the data to be mixed and uncertain (macro). Therefore, although the traditional surveying and mapping data processing theory has accumulated a large number of technical advantages in micro data processing, the large-scale and complexity of big data has become increasingly prominent, in which traditional calculation model and analysis algorithm cannot effectively support the efficient analysis and processing of big data. As the key to the intelligent era, data processing theory and method, how to adapt to the challenges and opportunities of new technology is worth our deep thinking. Driven by big data, new ideas and methods such as large-scale data mining, machine learning and deep learning are booming, which greatly promote the fusion of multi-source heterogeneous big data inside and outside the scene, effectively extract surface feature information from a variety of sensor data, and constantly improve the ability of surveying and mapping information acquisition and analysis. We think that the theory of surveying and mapping data also needs to be followed up, and the existing data processing methods need to be intelligent. Combined with the frontier hot spots, development trends and existing challenges of intelligent surveying and mapping, this paper explores the expansion direction of data processing theory. One is to promote the further development of surveying data processing theory, and the other is to provide reference for graduate students who are interested in entering the field of surveying and mapping big data.

XU Qiang

Time Series InSAR Monitoring and Analysis of Spatiotemporal Evolution Characteristics of Land Subsidence in Yan'an New District

  Objectives  Yan'an New District has attracted much attention because of its large-scale mountain excavation and city construction project. Such mega-scale land creation, rapid urban construction and complex geological conditions has induced wide land subsidence in the region.  Methods  In this paper, the temporal and spatial evolution of land subsidence in Yan'an New District was assessed using small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) to process the Sentinel-1A images covering the period from May 2016 to October 2019. Then, the mechanism and evolution trend of land subsidence in the new district was analyzed.  Results  Experimental results suggest that the spatial evolution pattern of land subsidence in Yan'an New District is highly relevant with the process of land creation project. The land subsidence area in the new district gradually expanded from the major urban area to the area of forest along with the land creation project, and its area decreased gradually with the passing of time. The temporal deformation evolution of land subsidence in the new district is related to the thickness of the fill, and all exhibit non-linear subsidence with various velocities. The temporal evolution of land subsidence undergoes three processes of rapid-slow-steady. The greater the thickness of the fill, the larger the amount of sedimentation, the longer it takes for the sedimentation to stabilize.  Conclusions  The main internal mechanism of land subsidence is the consolidation and compression deformation of the loess fill, which can be divided into three stages: Instantaneous settlement, consolidation settlement, and secondary consolidation settlement. Based on the characteristics of different stages combined with time series deformation, the land subsidence process and development trend can be analyzed. The research results provide a scientific reference for further monitoring and early warning, urban planning, and prevention and control of subsidence disasters in the new district.

LI Qingquan

Collaborative Inspection for the Sewer Pipe Network Using Pipe Capsules

  Objectives   The sewer pipeline network is an essential urban infrastructure. It is easy to be with faults because of the complicated circumstance under the ground, as well as undertaking the transportation and circulation of water. To avoid serious accidents caused by the faults, periodic and systematical inspection devices and methods are necessary. While current methods exist a variety of limitations, especially for large-scale and hard-inspected urban sewer pipe networks. Thus, we proposed a novel collaborative inspection method with high efficiency and availability, and low cost for urban sewer pipe networks.  Methods  Firstly, we invent a novel device named pipe capsule equipped with video cameras, lights, and a data storage facility. It will be dropped into pipes, move along with water flow, and record the videos of the inner walls until salvaged by the staff from the downstream. Such that, the video is captured to inspect the underground pipe. Multiple capsules are cooperated to complete the inspection task. A collaborative inspection method is designed through well design practice plan by maximizing the inspection range and degree, as well as minimizing the traveling length and time of the workers. Simulated annealing with a simple neighborhood search strategy is used to find the best practice plan.  Results  Taking the sewer pipe network at Shenzhen University, China an example, an experiment was conducted to verify the performance of the proposed approach. The results demonstrate that the collaborative inspection method achieves the same inspection with a shorter working time.  Conclusion  This study presented a collaborative inspection approach to detect the large-scale and complicated urban sewer networks with machine vision. It will benefit the inspection and operation of the urban underground pipe network.

CAO Buyang

Hilbert Curve and Cassandra Based Indexing and Storing Approach for Large-Scale Spatiotemporal Data

  Objectives  Because of the fast growing acquisition of real-time spatiotemporal data for various applications such as smart city or real-time air-quality monitoring, the traditional database technologies can-not satisfy the higher standards for large-scale data indexing, querying, and storing operations. As the via-ble alternative, NoSQL databases that are scalable and possess fast input/output capabilities offer potential solutions to accommodate the needs.  Methods  We propose a Hilbert curve and Cassandra technologies based approach for efficient indexing and storing of large-scale spatiotemporal datasets aiming to provide an effective framework for processing, querying, and analyzing large amount of data with spatial and temporal features. For example, the dataset of vehicle trajectories contains valuable spatial and temporal features those are being employed in the real world. The collected spatiotemporal datasets are preprocessed in order to fit the proposed structures for different applications. Specifically, two types of query applications com -monly used in the real world are the spatiotemporal range query and query upon vehicle IDs respectively. Two corresponding indexing structures are designed and implemented in order to accommodate the requests. S2 Geometry Library open sourced by Google is utilized to divide the earth surface into grids, and data points fall in grids are assigned with the specific IDs as the keys. The keys and columns are so designed by applying the Hilbert curve and Cassandra techniques that the resultant structures will physically store the spatially neighboring data points close to each other, and they are more suitable for large-scale spatiotempo-ral data querying and analyzing applications.  Results  The datasets acquired from the real applications are used to conduct the computational experiments to validate the efficiency of the proposed approach. The que-ry efficiency and the time consumed to store large amount of spatiotemporal data are investigated and bench-marked against some existing database technologies.  Conclusions  The computational experiments reveal the superiority of the proposed approach comparing to the existing methodologies, the required time to store (insert) data in the database is reduced by 6 times while the time needed to query data is decreased by at least 10 times. The efficiency of the proposed methodology is validate further by applying it to query the vehicle trajectories gathering the real-time air quality data.

YING Shen

Sunlight Pollution Analysis of Glass Curtain Wall in 3D City

  Objectives  Sunlight pollution caused by glass curtain walls of buildings in urban environment has brought great threats to traffic safety, fire control and residents?? health. At present, most researches on architecture sunlight pollution traditionally focus a local small range at specific construction based on simula-tion or measurement methods. We keep the way of three-dimensional (3D) computation, dissimilarly inte-grates geographic resources to expand the perception range of city sunlight pollution brought by building glasses.  Methods  The calculation technique of sunlight pollution builds 3D spatial relationship among road, building facade and sunlight in real urban environment, using deep-learning image segmentation to extract glass curtain walls. Then, combined with glare evaluation model, we develop an innovative sunlight pollu-tion model from perspective of drivers to evaluate the suitability for people.  Results  Taking Shenzhen Fu-tian Center as an example, the multi-level analyses of sunlight pollution are implemented by means of calcu-lation under real time and real location, and path selection based on evaluation. Through these instances, the time sequence regularity, the spatial distribution characteristics and the path estimation of architecture sunlight pollution are revealed.  Conclusions  The analyses retain space computation mode with innova-tions, fully utilize street view resources, and provide people the macroscopic concept, which indicates rela-tive strength of building sunlight pollution. Additionally, the method ensures instantaneity of urban sunlight pollution acquisition and computation, to a certain extent covers shortages of current researches, and is fur-ther capable of reference evaluation in environment protection, accurate warnings and predictions of glare intensity for pedestrians and drivers.

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