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Reconstruction Method of Satellite Gravity Gradient Measurement Angular Velocity by Combining Star Tracker Quaternion
A Multi?Pedestrian Tracking Algorithm Based on Center Point Detection and Person Re-identification
Dual Recognition Method of Spatial Layout Fusion for Complex Architectural Plan Drawings
A Data-driven Method for Traversability Analysis and Dataset Generation on Extraterrestrial Terrain
Geodesy and Navigation
The Concept of Resilience of National Comprehensive PNT System
Review of PEIV Model Parameter Estimation Theory and Its Applications
Linearization Estimation Algorithm for Universal EIV Adjustment Model
Classical Least Squares Method for Inequality Constrained PEIV Model
Analysis of Pseudorange and Carrier Ranging Deviation of BDS-3 Using Parabolic Directional Antenna
Elimination of Colored Noise in GNSS Station Coordinate Time Series by Using Wavelet Packet Coefficient Information Entropy
Adaptive Algebraic Reconstruction Algorithms for GNSS Water Vapor Tomography
Influence Analysis of High-order Seafloor Topography on Sea Surface Gravity Information
Cartography and Geoinformation
Connotations and Spatial Delimitation of Urban Area
A Real-Time Cleaning Method for Marine Non-Combat Targets
Application of Surveying, Mapping and Remote Sensing
Keel Morphology Analysis on Winter Sea Ice in Northwestern Weddell Sea, Antarctica
Adaptive Matched Filtering Algorithm for High-Precision Laser Bathymetry
A Point Cloud Vector Tracing Algorithm for Automatic Drawing of Interior Plan
Effects of Urban Morphology on Land Surface Temperature in Local Climate Zones
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:
Matching of Heterologous Images Considering Anisotropic Weighted Moment and Absolute Phase Orientation
Assessment of Position Performance of BDS for Space Application Based on FY-3D Satellite
Time Series Offsettracking of Baige Landslide Based on Sentinel-2 and Landsat 8
Study on Recognizing the Penguin Population in UAV Image Based on Object Otiented Classification
A novel implicit cutting method for 3D geological body model
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
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
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
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
A Method of Generating and Displaying Trajectory Line Heat Map with GPU Acceleration
A Probabilistic Prediction Model for Displacement of Super High Arch Dams Considering the Deformation Spatial Association
A Survey on Ship Detection Technology in High-Resolution Optical Remote Sensing Images
Fuzzy Logic Approach for Regional Landslide Susceptibility Analysis Constrained by Spatial characteristics of Landslide Disaster Environmental Factors
Improved Finite State Machine Step Detection Algorithm for Smartphone
A GNSS/INS Vehicle Integrated Navigation System Based on LSTM-EKF
Influence of the Element Beampattern on Synthetic Aperture Sonar Imagery
Short-edge Structure Recognition and Progressive Simplification for Buildings Using “Calculation Regions”
Highway slope deformation monitoring based on car-borne dual-antenna InSAR system
A New Data Preprocessing Method for Beidou Satellite Clock Bias
Regional Ionospheric TEC Modeling and Accuracy Analysis Based on Observations from a Station
Seasonal Rainstorm and Flood Risk Assessment Method for ImmovableCultural Relics: A Case Study of National Ancient Sites in Fujian Province
An adaptive Voronoi diagrams Algorithm for matching multi-scale areal Residential Areas
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
Research on Centimeter-Level Real-Time Orbit Determination Using Space-Borne GPS Measurements with IGS-RTS data receiving interruption
Time-varying analysis of backscatter coefficient corresponding to different surface types in the Tibetan Plateau
A Method to Evaluate Sampling Scheme Adopted in Surveying and Mapping Products' Inspection
Evaluation of Urban Ecological Environment and Its Relationship with Human Activities Based on Multi-Source Data
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
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
Infrastructure for Tomorrow's Smart Cities
Personal location prediction algorithm taking into account similar user characteristics
A Reference Satellite Image Retrieval Method for Drone Absolute Positioning
Multi-angle Remote Sensing Images Super-resolution Reconstruction Using Dynamic Upsampling Filter Deep Network
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](639) [PDF 1818KB](81)
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

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.

FANG Zhixiang

Pedestrian Relative Positioning Method Based on Visible and Invisible Landmarks

  Objectives  Visible landmarks and invisible landmarks are important aids for research into and design of applications for some target route.  Methods  We propose a pedestrian relative positioning method by fusing the visible landmarks and invisible landmarks, considering the data variance in different environ‐ ments and the pedestrian customary behavior during pedestrian positioning. Firstly, the invisible landmarks (e.g., magnetic changes, WiFi(wireless fidelity) updates) along the target route are detected by smartphone sensors, and the evidence framework is built by segmenting the target route with data characteristics of sen‐ sors. Then the salient visible landmarks could be detected, and the relative spatial relations between land‐ marks and panoramas could be derived based on their coordinates.Secondly, the probability values of pedes‐ trians in the road segments are respectively obtained, based on the similarly of the real‐time sensor data and sensor data from each of the evidence framework. And the relative azimuth relations of landmarks in the panoramas could be updated instantly. Finally, based on the Bayesian probability fusion method, the pedes‐ trian positioning results could be computed through fusing the results of sensors and panoramas.In detail, the probability values of pedestrians in the road segments will be recalculated based on the panoramic image results.  Results  The experimental results demonstrate that the proposed method could improve the posi‐ tioning accuracy in a single pedestrian walking environment by fusing multi‐source data.In an environment with fewer sensor features, the accuracy achieved by this method increases by 12.78%, which is higher than that of the invisible landmark‐based method.  Conclusions  The pedestrian relative positioning method not only solves the problems of sensor instability and less sensor features, but also improves the positioning accuracy.

HE Jianhua

Reconstruction of Rural Settlement Based on the Characteristics of Livability and Population Flow Network

  Objectives  The spatial optimization and reconstruction of rural settlement is one of the important content of promoting rural revitalization. Through livability and population flow analysis, to scientifically reconstruct rural settlement and optimize spatial allocation.  Methods  Starting with the basic needs of life, this paper takes Ezhou City as study area, builds a livability evaluation index system and evaluates the livability level of Ezhou City. We construct rural-urban population flow network through network analysis method and find the pattern of rural population flow, and integrate the combined characteristics of livability and the intensity of population flow to reconstruct rural settlement.  Results  The experimental results show that: (1)Overall, the livability of Ezhou City is relatively high. There is a small gap in survival guarantee function, while there are large gaps in life service function and life improvement function.(2)The population flows according to the priority order of the main urban area, the subordinate towns, and nearby advantageous towns. The radiation range of town is limited, and the existing point-axis structure cannot function well. It is urgent to develop central villages, general villages and basic villages to form a complete rural structure to drive region‐wide development.(3)Based on the livability and the intensity of population flow, rural settlements are divided into the type of relocation and demolition, the type of suburban integration and the type of agglomeration promotion (central village, general village and basic village).  Conclusions  The results facilitate to reshape the core of rural and complete the rural structure to promote the optimal allocation of resources. This paper will provide a decision-making basis for the reconstruction of rural settlement where population flows rapidly.

ZHANG Chunsen

A Change Detection Method for Remote Sensing Image Based on Vector Data

  Objectives  Change detection is a process of recognizing the state changes of ground surface by multiple observations. With the improvement of image data quality, it provides more possibilities for people to realize change detection. Traditional multi-temporal remote sensing image change detection is easily affected by the season in which the images were taken, solar altitude angle and shooting angle etc. In addition, the traditional calculation methods of change index, variables which susceptible to the interference of change object are often introduced, such as mean value, median value and so on. To solve such problems, we proposed a change detection method based on vector data.  Methods   Firstly, since traditional change detection method is always influenced by shooting season, shooting angle, etc, we use a vector-image method, which is different from the previous image-image method. With the application of this method, the change differences between the old and new images were calculated by using a similarity measurement method, and the change object will identified by a threshold value. The vector-image method using the vector data and the new time image data detect the changes. Secondly, the anomaly detection method in the data mining method can be introduced into the change detection method, hence the outlier has a fewer and different characteristics compared with the normal object. In this paper, we firstly got the object through incremental segmentation under the constraints of the previous vector image, then extracted its texture and spectral features to get the dataset by the principal component analysis transform. After that, using isolation forest method to calculate object's change index, we obtained the change threshold by Bayes method.  Results  We took two experiments, and the effectiveness of the proposed method was verified by comparing image-image and vector-image change detection methods, as well as Markov distance and isolation forest change methods, among which, the accuracy rate of experiment 1 is 0.923 5 and that of experiment 2 is 0.931 8.  Conclusions   By comparing the image-image method with the vector-image method, the experimental results show that the proposed method can not only improve the accuracy of change detection, but also improve the automation and intelligence of image-based change detection.

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