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A Change Detection Method for Remote Sensing Image Based on Vector Data
Automatic Shadow Compensation Based on Improved Wallis Model for High Resolution Remote Sensing Images
A Real-Time Video Flame Detection Algorithm Based on Improved Yolo-v3
Face Swapping Using Convolutional Neural Network and Tiny Facet Primitive
Analyzing the Ecological Environment of Mining Area by Using Moving Window Remote Sensing Ecological Index
Segmentation Method of Building Facade Using Multi-scale Tensor Voting
Cartography and Geoinformation
Method of Calculating the Convergence Based on Mobile Laser Scanning in Circular Shield Tunnel
Geodesy and Navigation
An Improved Model for Inter-System Bias Estimation Based on BDS-2/BDS-3 Combined Precise Orbit Determination
Application of Wavelet Decomposition and Singular Spectrum Analysis to GNSS Station Coordinate Time Series
Influence Analysis of Vertical Deflection on Attitude Accuracy of CHZ-Ⅱ Gravimeter Stabilized Platform
Structured Total Least Squares Method Based on Variable Projection
Inversion and Analysis of Atmospheric Boundary Layer Height Using FY-3C Radio Occultation Refractive Index Data
Photogrammetry and Remote Sensing
Reconstruction of Rural Settlement Based on the Characteristics of Livability and Population Flow Network
An Optimization Algorithm for Boundary Points and Boundary Lines Extraction
Analysis of the Factors Affecting the Degree of Urban Expansion: Taking Wuhan City as an Example
Automatic Generalization Methods of Cyberspace Point Cluster Features Considering Characteristics
Non-rigid Shape Correspondence Between Partial Shape and Full Shape
Evaluation of Landslide Susceptibility by Multiple Adaptive Regression Spline Method
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:
Characteristics of the Computer Game Map
Application of EM Algorithm in the Parameter Estimation of P-norm Mixture Mode
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](425) [PDF 1818KB](54)
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

SUI Haigang

Reflection and Exploration of Rapid Remote Sensing Emergency Response for Typical Natural Disasters

  Objectives  Rapidly developing remote sensing technology provides powerful technical support for natural disaster emergency response. However, deep coupling between remote sensing technology and emergency response is lacking. Considering disaster emergency response involves the joint cooperation of multiple resources and systems, the rapid emergency response based on remote sensing technology require systematically studied.  Methods   Faced with the great demand of emergency response of disaster remote sensing, we conduct the research on the intelligent, dynamic and fast emergency service of emergency response. In view of the challenge for rapid emergency response of remote sensing, some key technique involved in rapid emergency response of disaster remote sensing are especially discussed, including making the emergency preplan, constructing collaborative emergency service framework of remote sensing, allocation of emergency monitoring resources, remote sensing cooperative of air-space-ground resources, the design optimization for emergency processing mode and the quick intellectual processing for remote sensing emergency.  Results   Based on above methods and technologies, we conducted the field application of security system for disaster emergency service, on-board video intelligent processing, real-time processing of on-board disaster emergency information, and rapid processing of ground emergency information.  Conclusions   Rapid emergency response for typical natural disasters requires more in-depth research based on remote sensing technologies. Only by achieving universal-coverage and integrated study ranging from emergency service system to concrete algorithm optimization, the timeliness of disaster emergency can be ensured.

ZHU Qing

Classification and Coding of Entity Features for Digital Twin Sichuan-Tibet Railway

The heterogeneous multidisciplinary spatial information data with multi-granularity and sophisticated semantics of features in the wide area of Sichuan-Tibet railway, which leads to the inconsistency of data content/format and spatio-temporal datum.Therefore, it is difficult to integrate/analyse relevant data efficiently. In order to establish the concept system of cognitive sharing for the unified expression of spatial information of Sichuan-Tibet railway, firstly, this article has studied and depicted the geometry, scale, topology, attribute, behavior characteristics and interactive relationship of different feature types such as "geography""geology""facilities""meteorology""ecology""disaster" and "personnel"; secondly, according to the framework of relevant national standard classification and coding system, the study has regulated the unified coding rules and expanding methods, conducted substantialization classification upon various feature types into the minimum management unit. Based on the rules, the classification in higher level (primary category, subcategory, large class and medium class) and the classification in lower level (level Ⅰ, Ⅱ and Ⅲ subclasses) was expanded and reduced according to the application requirements of Sichuan-Tibet railway respectively, leaving 2 primary categories, 6 subcategories, 27 large classes and 87 medium classes in total. On this basis, each feature entity in the classification system was coded and given a unique and unambiguous identity, so as to implement the precise mapping between three-dimensional spatial information and feature entities and provide support for the construction of Sichuan-Tibet railway.

JIAO Limin

Sustainable Urbanization and Territorial Spatial Optimization

Sustainable territorial spatial development faces severe challenges globally, especially the threats from rapid urbanization. It is important for territorial spatial planning in the new era to explore the principles, methodology and models for the territorial spatial optimization aiming sustainable urbanization from global and national perspectives. This paper rethink the spatial optimization for sustainable development by reviewing the literature on urbanization, spatial optimization and sustainable development. The results show that there is no ready-made path for sustainable territorial spatial development, and sustainability should be the fundamental objective of territorial spatial optimization. Cases from the globe and China show that urban sprawl tends to make cities disperse, decline population density, and fall in a path-dependency. Cities should be laid at the core of territorial spatial optimization. Chinese sustainable urbanization should be characterized by compact development, high-density, livable urban development, and low carbon. The concepts of sustainable urbanization oriented territorial spatial optimization include ecological protection, resource saving, intensive development, and green development, which forms the path of sustainable territorial spatial development. The modeling of territorial spatial optimization can be reconstructed from index system and quantification, setting of objectives, and constraint rules in a multi-objective collaborative optimization model. In this paper, we conclude that China has to build her own way of sustainable spatial development in accordance with the conditions of the nation, promoted by territorial spatial optimization with sustainable urbanization as a core.

WANG Mi

Extraction and Analysis of Global Elevation Control Points from ICESat-2 /ATLAS Data

ICESat-2's laser data has the highest elevation accuracy up to date, and its observation range covers the global land, which can be used as basic data for the high-precision global ground elevation reference. Based on ICESat-2 /ATLAS global laser data product ATL08, this paper obtained ICESat-2 laser points on the global land, and studied the method of extracting global elevation control points based on elevation reference and attribute parameters, and used reference elevation data to verify their accuracy. The obtained laser points were verified by airborne laser data in Shandong experimental field and Henan experimental field in China. And the root mean square error (RMSE) were 1.11 m and 1.39 m respectively before filtering. After filtering with elevation reference and slope constraints, the mean RMSE were 0.69 m and 0.57 m respectively, and the corresponding data retention rates were 61.38% and 60.00%, which proved that the proposed method in this paper could effectively improve the elevation accuracy while ensuring the data retention rate. The airborne laser data from the western, central and eastern United States experimental fields were used to verify the elevation control points. The RMSE of each experimental field was less than 0.9 m, which proved that the extraction method proposed in this paper could be used to extract elevation control points worldwide. This method can automatically extract global elevation control points with high density and high precision, providing support for the stereo mapping of domestic high-resolution satellites without or with few ground control points, and assistance in evaluating the quality of DEM/DSM products.

XU Qiang

Understanding and Consideration of Related Issues in Early Identification of Potential Geohazards

  Objectives  In China, geohazards are wide-ranging. Traditional artificial investigations have found nearly three hundred thousand locations of potential geohazards. However, the recent occurred catastrophic geohazards are not within these determined locations. Widely identification of potential geohazards become one of the most important jobs for geohazard prevention and mitigation.  Methods  We propose some suggestions to promote early identification for potential geohazards.  Results  (1) Recently, various remote sensing techniques play an significant role in geohazard identification, but each technique has its limitation to recognize geohazards with different types and characteristics. Only integrated technologies, mutual complementation and verification, can effectively solve the problem. (2) Combination between traditional geological surveys and modern technologies (LiDAR, aerial and semi-aerial geophysical exploration, etc.) can improve the efficiency and accuracy for identification of the most difficult and unstable slops.(3) The deep machine learning is expected to realize the intelligent automatic identification of geohazards. Currently, it shows good performance in new geohazards with significant spectral and texture characteristics, while the accuracy of automatic identification for other types, such as ancient landslides and normal potential geohazards, is still not enough.  Conclusions  More efforts are in urgent need for further research in related fields.

SUI Haigang

Detecting Building Façade Damage Caused by Earthquake Using CBAM-Improved Mask R-CNN

  Objectives  Building damage information can provide an important basis for the decision making of rapid post-earthquake assessment. Traditional building damage detection techniques mainly focus on the roof surface, thus many damaged buildings with an intact roof surface but collapsed middle floors may be neglected. We propose a method of building façade damage detection based on deep learning and multiresolution segmentation algorithm.  Methods  The method which integrates the instance segmentation and multiresolution segmentation algorithm is applied to detecting the post-earthquake building façade damage. The first thing is to collect the ground images of post-earthquake buildings in the field and perform the data augmentation. Secondly, we use the convolutional block attention module (CBAM) to improve Mask R-CNN. Then the dataset is input to the improved model for training, and finally a multiresolution segmentation algorithm is adopted to post-process the building façade damage detection results output by the CBAM-Improved Mask R-CNN.  Results  The experimental results show: (1) Collecting ground images of buildings in the field and performing image augmentation can effectively guarantee the necessary training sample size of the instance segmentation model. (2) The Mask R-CNN improved by CBAM attention mechanism significantly improves the post-earthquake building facade damage detection capabilities, which realizes the precise extraction of damage information from complex building façade backgrounds. (3) In addition, using the multiresolution segmentation algorithm to post-process the building facade damage detection results can obviously solve the blurred boundary problems caused by the accumulation of convolutional layers.  Conclusions  The proposed method can significantly improve the capability of post-earthquake building façade damage detection when compared to the traditional methods, which also raises the Mask R-CNN's accuracy, precision, recall and F2-score to a certain degree. It can be inferred that the proposed method has the strong potential to be applied to the post-earthquake building façade damage detection and therefore provides an important technical means for detecting the comprehensive and detailed building damage detection caused by earthquake.

DU Zhiqiang

Knowledge Graph Construction Method on Natural Disaster Emergency

Natural disasters occur frequently and pose a huge threat to China. Disaster prevention, mitigation, and disaster relief are eternal topics of human survival and development. However, in the field of disaster relief and emergency response, the relevant data increase sharply while the critical knowledge of emergency is obviously lacking. The "data-information-knowledge" transformation capacity is insufficient to meet the urgent needs of disaster prevention and reduction. Firstly taking natural disasters as the core, and around four elements of natural disaster events, disaster emergency tasks, disaster data, and methods, this paper proposes a knowledge graph construction method by combining a top-down approach and a bottom-up approach. Then, concept layer of knowledge graph is built from top to down, and the conceptual framework is formed through ontology modeling. Data layer of knowledge graph is built from bottom to top, and the relationship between entities is established through data acquisition, knowledge extraction, fusion, and storage. Finally, a flood disaster emergency knowledge graph is built to verify the validity of the proposed method. The concept layer in flood disaster emergency knowledge graph defines the conceptual levels, the attributes and the semantic relationships of flood disaster events, disaster emergency tasks, disaster data, and methods. The data layer in flood disaster emergency knowledge graph realizes the extraction of entities and relationships from multi-source data. After the knowledge fusion process, 3 054 nodes and 12 689 relationship edges are obtained and stored in the Neo4j graph database. The flood disaster emergency knowledge graph realizes the transformation from multi-source data to interrelated knowledge.

LÜ Guonian

Role of Geometric Algebra in High Dimensional Space Representation of Geographic Information

Geographic information space is a high-dimensional space combining virtual and real. Geographic information system (GIS) based on European geometry plays an important role in the development of geographic information science. However, because the expression of GIS geographic objects and phenomena in European-style space depends on object coordinates and the adopted coordinate system, it is difficult for the expression, calculation and analysis of geographic objects to form a multi-dimensional unified operation rule and framework, which increases the algorithm's complexity and reduces the efficiency of algorithm analysis. Geometric algebra is a kind of combination algebra based on dimensional operation. Space can be defined as the operation between vector sets. The dimension of space is directly determined by the algorithm, which realizes the unification of high-dimensional geometric calculation and analysis. Based on the unified calculation and analysis framework of geometric algebra, GIS can better express and analyze high-dimensional objects, and then improve the ability of expressing complex geographical objects and dynamic geographical phenomena, analyzing spatiotemporal multi-scale objects and integration of different scale geographical models. This lays the theoretical foundation for the development of GIS towards holographic maps with real-time dynamics, virtual-real fusion, full perspective, full elements and full content expression.

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