Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

Asymmetric image encryption algorithm based on a new three-dimensional improved logistic chaotic map

Based on some analyses of existing chaotic image encryption frameworks and a new designed three-dimensional improved logistic chaotic map(3D-ILM),an asymmetric image encryption algorithm using public-key Rivest–Shamir–Adleman(RSA)is presented in this paper.In the first stage,a new 3D-ILM is proposed to enhance the chaotic behavior considering analysis of time sequence,Lyapunov exponent,and Shannon entropy.In the second stage,combined with the public key RSA algorithm,a new key acquisition mathematical model(MKA)is constructed to obtain the initial keys for the 3D-ILM.Consequently,the key stream can be produced depending on the plain image for a higher security.Moreover,a novel process model(NPM)for the input of the 3D-ILM is built,which is built to improve the distribution uniformity of the chaotic sequence.In the third stage,to encrypt the plain image,a pre-process by exclusive OR(XOR)operation with a random matrix is applied.Then,the pre-processed image is performed by a permutation for rows,a downward modulo function for adjacent pixels,a permutation for columns,a forward direction XOR addition-modulo diffusion,and a backward direction XOR addition-modulo diffusion to achieve the final cipher image.Moreover,experiments show that the the proposed algorithm has a better performance.Especially,the number of pixels change rate(NPCR)is close to ideal case 99.6094%,with the unified average changing intensity(UACI)close to 33.4634%,and the information entropy(IE)close to 8.

Design and Realization of Block Level Augmented Reality Three-Dimensional Map

In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map. The augmented reality three-dimensional map is produced based on skyline software. Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized. The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map. Those lay the groundwork for the application of augmented reality three-dimensional map. .

A modified method of discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces

This paper presents an automated method for discontinuity trace mapping using three-dimensional point clouds of rock mass surfaces.Specifically,the method consists of five steps:(1)detection of trace feature points by normal tensor voting theory,(2)co ntraction of trace feature points,(3)connection of trace feature points,(4)linearization of trace segments,and(5)connection of trace segments.A sensitivity analysis was then conducted to identify the optimal parameters of the proposed method.Three field cases,a natural rock mass outcrop and two excavated rock tunnel surfaces,were analyzed using the proposed method to evaluate its validity and efficiency.The results show that the proposed method is more efficient and accurate than the traditional trace mapping method,and the efficiency enhancement is more robust as the number of feature points increases.

Three-dimensional computed tomography mapping of posterior malleolar fractures

BACKGROUND Posterior malleolar fractures have been reported to occur in<40%of ankle fractures.AIM To reveal the recurrent patterns and characteristics of posterior malleolar fractures by creating fracture maps of the posterior malleolar fractures through the use of computed tomography mapping.METHODS A consecutive series of posterior malleolar fractures was used to create threedimensional reconstruction images,which were oriented and superimposed to fit an ankle model template by both aligning specific biolandmarks and reducing reconstructed fracture fragments.Fracture lines were found and traced in order to generate an ankle fracture map.RESULTS This study involved 112 patients with a mean age of 49,comprising 32 pronationexternal rotation grade IV fractures and 80 supination-external rotation grade IV fractures according to the Lauge-Hansen classification system.Three-dimensional maps showed that the posterior ankle fracture fragments in the supinationexternal rotation grade IV group were relatively smaller than those in the pronation-external rotation grade IV group after posterior malleolus fracture.In addition,the distribution analyses on posterior malleolus fracture lines indicated that the supination-external rotation grade IV group tended to have higher linear density but more concentrated and orderly distribution fractures compared to the pronation-external rotation grade IV group.CONCLUSION Fracture maps revealed the fracture characteristics and recurrent patterns of posterior malleolar fractures,which might help to improve the understanding of ankle fracture as well as increase opportunities for follow-up research and aid clinical decision-making.

Application of Three-dimensional Laser Scanning Technology in the Teaching Practice of Surveying and Mapping of Ancient Buildings

Based on the study of the application of three-dimensional laser scanning technology in ancient building surveying and mapping,this paper briefly describes the working principle and flow of three-dimensional laser scanning technology.Based on the practical application,this paper puts forward the discussion of related problems and matters needing attention.This has a certain reference significance for the study of new technology in surveying and mapping of ancient buildings.

Integration of spatial attractions between and within pixels for sub-pixel mapping

As a promising technique to enhance the spatial reso- lution of remote sensing imagery, sub-pixel mapping is processed based on the spatial dependence theory with the assumption that the land cover is spatially dependent both within pixels and be- tween them. The spatial attraction is used as a tool to describe the dependence. First, the spatial attractions between pixels, sub- pixel/pixel spatial attraction model （SPSAM）, are described by the modified SPSAM （MSPSAM） that estimates the attractions accord- ing to the distribution of sub-pixels within neighboring pixels. Then a mixed spatial attraction model （MSAM） for sub-pixel mapping is proposed that integrates the spatial attractions both within pix- els and between them. According to the expression of the MSAM maximumising the spatial attraction, the genetic algorithm is em- ployed to search the optimum solution and generate the sub-pixel mapping results. Experiments show that compared with SPSAM, MSPSAM and pixel swapping algorithm modified by initialization from SPSAM （MPS）, MSAM can provide higher accuracy and more rational sub-pixel mapping results.

Mapping spatial variation in acorn production from airborne hyperspectral imagery

Masting is a well-marked variation in yields of oak forests. In Japan, this phenomenon is also related to wildlife management and oak regeneration practices. This study demonstrates the capability of integrating remote sensing techniques into map- ping spatial variation of acorn production. The hyperspectral images in 72 wavelengths （407-898 nm） were acquired over the study area ten times over a period of three years （2003-2005） during the early growing season of Quercus serrata using the Airborne Im- aging Spectrometer Application （AISA） Eagle System. With the canopy spectral reflectance values of 22 sample trees extracted from the images, yield estimation models were developed via multiple linear regression （MLR） analyses. Using the object-oriented classi- fication approach in eCognition, canopies representative of individual oak trees （Q. serrata） were identified from the corresponding hyperspectral imagery and combined with the fitted estimation models developed, acorn yield over the entire forest were estimated and visualized into maps. Three estimation models, obtained for June 27 in 2003, July 13 in 2004 and June 21 in 2005, showed good performance in acorn yield estimation both for the training and validation datasets, all with R2 〉 0.4, p 〈 0.05 and RRMSE 〈 1 （the relative root mean square of error）. The present study shows the potential of airborne hyperspectral imagery not only in estimating acorn yields during early growing seasons, but also in identifying Q. serrata from other image objects, based on which of the spatial distribution patterns of acorn production over large areas could be mapped. The yield map can provide within-stand abundance and valuable information for the size and spatial synchrony of acorn production.

Machine Learning Mapping of Soil Apparent Electrical Conductivity on a Research Farm in Mississippi

Open-source and free tools are readily available to the public to process data and assist producers in making management decisions related to agricultural landscapes. On-the-go soil sensors are being used as a proxy to develop digital soil maps because of the data they can collect and their ability to cover a large area quickly. Machine learning, a subcomponent of artificial intelligence, makes predictions from data. Intermixing open-source tools, on-the-go sensor technologies, and machine learning may improve Mississippi soil mapping and crop production. This study aimed to evaluate machine learning for mapping apparent soil electrical conductivity (ECa) collected with an on-the-go sensor system at two sites (i.e., MF2, MF9) on a research farm in Mississippi. Machine learning tools (support vector machine) incorporated in Smart-Map, an open-source application, were used to evaluate the sites and derive the apparent electrical conductivity maps. Autocorrelation of the shallow (ECas) and deep (ECad) readings was statistically significant at both locations (Moran’s I, p 0.001);however, the spatial correlation was greater at MF2. According to the leave-one-out cross-validation results, the best models were developed for ECas versus ECad. Spatial patterns were observed for the ECas and ECad readings in both fields. The patterns observed for the ECad readings were more distinct than the ECas measurements. The research results indicated that machine learning was valuable for deriving apparent electrical conductivity maps in two Mississippi fields. Location and depth played a role in the machine learner’s ability to develop maps.

High Spatial Resolution Mapping of Dykes Using Unmanned Aerial Vehicle(UAV) Photogrammetry: New Insights On Emplacement Processes

Remote sensing has played a pivotal role in our understanding of the geometry of dykes and dyke swarms on Earth,Venus and Mars(West and Ernst,1991;Mege and Masson,1995;Ernst et al.,2005).Since the 1970’s

Development of Web Mapping Application for Spatial Ecotourism Information Using QGIS Plugin and Freely Available Web Platforms in North West Highlands of Ethiopia a Case Study: Chokie Mountain Watersheds

Ecotourism is a sustainable, green and smokeless industry of the society by providing alternative source to the livelihood and local community, in order to re-naturalize the environment to bring the man closer to the natural environment. The use of web application has changed the way tourists gather information about tourist attraction spots of the research area. The aim of the study is to assess and identify ecotourism attraction sites of Chokie Mountain watersheds for touristic activities to develop a web-based GIS mapping portal for the improvement of nature-based ecotourism activities. The web-based GIS portal for Web Mapping Application is available for the user with the skills necessary to create standard web mapping services. We have implemented web mapping services based on formal cartographic visualization rules in the open source QGIS software and threejs JavaScript plugin. Threejs plugin is used for 3D visualization, interaction and export terrain data, map canvas image and vector data to HTML page and JS. The result of web-based GIS portal supports spatial and non-spatial database of tourist attraction and tourist service data with attractive user interface.

Inferring Spatial Distribution Patterns in Web Maps for Land Cover Mapping

Web maps represent an effective source for land cover mapping in capturing human activities.However,due to spatial heterogeneity,previous research has mainly focused on generating land cover maps in partial areas.Inferring spatial distribution patterns in Web maps may provide an alternative perspective on improving map production on a larger scale.This paper represents a novel approach to investigating the spatial distribution in Web maps for land cover mapping.First,linear features from Web maps are utilised to delineate parcels with insufficient Web map data for classification.Then,spatial factors are constructed from point and polygon features to identify the spatial variety of Web maps,with an artificial neural network classifier being adopted to classify land cover automatically.Land cover mapping is finally proposed by combining classified parcels and existing polygon features.The proposed method is applied in Guangzhou,Guangdong Province,using a Web map from AutoNavi.The results show an approximately 88%classification accuracy and an overall mapping accuracy of 85.06%.The results indicate that the proposed approach has the potential to be utilised in land cover mapping,and the constructed spatial factors are effective at characterising land cover information.

Mapping Spatial Data on the Web Using Free and Open-Source Tools: A Prototype Implementation

There is a growing need for web-based geographic information systems for easy and fast dissemination, sharing, displaying and processing of spatial information. The tremendous growth in the use of web and open-source geospatial resources has sparked development of web-based spatial applications to address multidisciplinary issues with spatial dimensions. This paper presents the integration of open-source geospatial tools and web technology to visualize and interact with spatial data using web browser. The goal of this paper is to implement a prototype system for web-based mapping by providing step-by-step instructions in order to encourage the eager developers and interested readers to publish their maps on the web with no prior technical experience in map servers. The implementation of mapping prototype shows the utilization of open-source geospatial tools which results in a rapid implementation with minimal or no software input cost.

Utilization of Open Source Spatial Data for Landslide Susceptibility Mapping at Chittagong District of Bangladesh—An Appraisal for Disaster Risk Reduction and Mitigation Approach

Since creation of spatial data is a costly and time consuming process, researchers, in this domain, in most of the cases rely on open source spatial attributes for their specific purpose. Likewise, the present research aims at mapping landslide susceptibility at the metropolitan area of Chittagong district of Bangladesh utilizing obtainable open source spatial data from various web portals. In this regard, we targeted a study region where rainfall induced landslides reportedly causes causalities as well as property damage each year. In this study, however, we employed multi-criteria evaluation (MCE) technique i.e., heuristic, a knowledge driven approach based on expert opinions from various discipline for landslide susceptibility mapping combining nine causative factors—geomorphology, geology, land use/land cover (LULC), slope, aspect, plan curvature, drainage distance, relative relief and vegetation in geographic information system (GIS) environment. The final susceptibility map was devised into five hazard classes viz., very low, low, moderate, high, and very high, representing 22 km2 (13%), 90 km2 (53%);24 km2 (15%);22 km2 (13%) and 10 km2 (6%) areas respectively. This particular study might be beneficial to the local authorities and other stake-holders, concerned in disaster risk reduction and mitigation activities. Moreover this study can also be advantageous for risk sensitive land use planning in the study area.

Sparse three-dimensional imaging for forward-looking array SAR using spatial continuity

For forward-looking array synthetic aperture radar(FASAR),the scattering intensity of ground scatterers fluctuates greatly since there are kinds of vegetations and topography on the surface of the ground,and thus the signal-to-noise ratio(SNR)of its echo signals corresponding to different vegetations and topography also varies obviously.Owing to the reason known to all,the performance of the sparse reconstruction of compressed sensing(CS)becomes worse in the case of lower SNR,and the quality of the sparse three-dimensional imaging for FASAR would be affected significantly in the practical application.In this paper,the spatial continuity of the ground scatterers is introduced to the sparse recovery algorithm of CS in the threedimensional imaging for FASAR,in which the weighted least square method of the cubic interpolation is used to filter out the bad and isolated scatterer.The simulation results show that the proposed method can realize the sparse three-dimensional imaging of FASAR more effectively in the case of low SNR.

Balanced Functional Maps for Three-Dimensional Non-Rigid Shape Registration

Three-dimensional(3D)shape registration is a challenging problem,especially for shapes under non-rigid transformations.In this paper,a 3D non-rigid shape registration method is proposed,called balanced functional maps(BFM).The BFM algorithm generalizes the point-based correspondence to functions.By choosing the Laplace-Beltrami eigenfunctions as the function basis,the transformations between shapes can be represented by the functional map(FM)matrix.In addition,many constraints on shape registration,such as the feature descriptor,keypoint,and salient region correspondence,can be formulated linearly using the matrix.By bi-directionally searching for the nearest neighbors of points’indicator functions in the function space,the point-based correspondence can be derived from FMs.We conducted several experiments on the Topology and Orchestration Specification for Cloud Applications(TOSCA)dataset and the Shape Completion and Animation of People(SCAPE)dataset.Experimental results show that the proposed BFM algorithm is effective and has superior performance than the state-of-the-art methods on both datasets.

Mapping the Flood Risk Exposure Using Open-Source Geospatial Tools and Techniques: A Case of Gampaha Divisional Secretariat Division, Sri Lanka

The use of open-source data and tools in disaster exposure mapping is presented in this paper. Disaster exposure is a collection of the element at risk to potential loss. Gampaha divisional secretariat (DS) is a study area laid on the lower part of the Attanagalu Oya river basin. As the geospatial tools, OpenStreetMap (OSM), Java OpenStreetMap (JOSM), QGIS, GPS Essentials, and Open Map Kit (OMK) are used. The elements of disaster exposure, including the number of people or types of assets, are surveyed and inventoried using the OSM platforms. Local, national, and international agencies produce and evaluate the data. The study developed spatial data for building footprints of 165,000 households, street lengths of 2300 km, hospital units of 16, and utility units of 2300. This could overcome the main challenges of exposure mapping in the area. The procedure developed in the exposure mapping can be used in a data-sparse environment. Exposure mapping is generally used to estimate the impact of hazards or disasters, which are essential in effective disaster management. How are there still remaining challenges in disaster exposure mapping such as less awareness about the mapping procedure, lack of government support, internet access, hardware, and inability to understand the value of exposure mapping?

基于SuperMap iDesktop空间数据库的地形图快速生产

基于SuperMap iDesktop 10软件平台,提出了通过方案定制和协同编辑实现地形图快速生产的技术路线,以全要素1∶10000比例尺地形图数据制作1∶25000比例尺地形图为例,对实现地图快速保障的关键环节进行了阐述。该技术路线能够基于已有的多源地理信息数据和制图方案,快速提供和灵活制作符合要求的标准产品及定制化成果,从而缩短成图周期、实现快速保障应用,对新型测绘体系下的快速精准保障模式进行了有益探索。

GPS probe map matching algorithm based on spatial data model

To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.

Oracle Spatial & MapViewer在汽车导航定位上的应用

本文通过Oracle数据库的空间数据管理模块Oracle Spatial & MapViewer,将汽车导航定位的实时数据直接写入空间数据库,再用MapViewer发送回终端进行显示;提出了一种用Oracle Spatial & MapViewer对实时定位数据进行存储显示和共享的新方法。