最新刊期
卷 28 ， 期 5 ， 2024
- “在人文地理学领域，专家引入数字孪生方法，构建了依实驱虚、依虚控实、虚实协同演进的新模式，为避免扰乱现实环境、深度探索复杂问题、优化现实地理问题调控方案等提供了解决方案。”
摘要：The human geographic environment is a comprehensive environment formed by the interaction of human activities and the geographic environment, which is complex and highly vulnerable. Introducing the digital twin method to build a new framework of research on human geography issues has great disciplinary importance and application value because this framework has the characteristics of driving the virtual according to the real, controlling the real according to the virtual, and the coordinated evolution of the virtual and the real. It also helps avoid disturbing the real environment, explores complex problems in depth, and optimizes the control scheme of real geographical problems. Based on the review of relative research in China and abroad, a conceptual model of the digital twin human geographic environment is proposed, and its systematic connotation is elaborated. The major components of this system include the real human geographic environment, the virtual human geographic environment, and the information interaction between them. Through the digital twin construction and simulation of the geographic environment, human activities as well as human-nature interaction, the virtual and real synergy, complementary advantages, and coevolution between the virtual and the real environment can be realized. Furthermore, a technical framework with bilateral technology roadmap for the implementation of digital twin human geographic environments is proposed. One route is to complete the comprehensive perception and twin reproduction of the real human geographic environment through digital accurate mapping to the virtual geography environment, and the other route is to achieve intelligent feedback of the virtual human geographic environment and its manipulation on the real human geographic environment through multichannel virtual-real interaction. On the basis of the above, a hierarchical construction scheme of the digital twin human geographic environment platform, which covers five sub platforms, namely, collaborative monitoring and environmental awareness platform, multimodal full-scale database, intelligent modeling and simulation technology integration, high-performance spatiotemporal computing engine, and cross-domain knowledge application for decision making is designed. Supported by the Nanchang Subcenter of the UNESCO International Natural and Cultural Heritage Space Technology Center, the digital twin of Jiangxi Bailudong Academy, the education base of Chinese Confucian culture, is taken as a typical case to demonstrate the construction method, main function, and result form of the digital twin human geographic environment. The conclusions are drawn from three perspectives: (1) The digital twin human geographic environment should be taken as a creative method for the exploratory learning of human geography. (2) The digital twin human geographic environment is currently the best way to build a geographic metaverse with human activities. (3) The virtual geographic environment can provide theoretical basis for the construction of the digital twin human geographic environment. Lastly, the purpose of this paper is to throw bricks and spark jade to arouse scholars’ thinking on the research of coupling digital twins and human geographic environment, and to promote the sustainable development of human geography jointly.关键词：remote sensing;Digital twins;Human geographic environment;virtual geographic environments;collaboration between the real and the virtual;Bailudong Academy- 715
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发布时间：2024-05-30 -
Primary exploration of geographic metaverse from the perspective of virtual geographic environment AI导读
“最新研究进展揭示了元宇宙、数字孪生和虚拟地理环境的内涵及其发展趋势。专家提出地理元宇宙概念，定义了三类数字地理环境，并探讨了其基本特性。基于人地关系，建立了地理元宇宙平台概念架构，为虚拟地理环境工程学的发展奠定了基础。”
摘要：The connotation, initial characteristics, and development trend of association and integration of the three concepts of metaverse, digital twin, and virtual geographic environment are scrutinized. The concept of geographic metaverse is proposed, and three types of digital geographic environments of the geographic metaverse are defined and distinguished based on the relationship between virtual and real contents and the parallel superposition of virtual and real spaces, that is, the virtual geographic environment of digital native, the virtual geographic environment of digital twin, and the augmented geographic environment of digital– real superposition. The essential characteristics of the geographic metaverse are discussed in terms of time–space, avatar, spatial reference system, and presence–absence. Based on the human–earth relationship and the technical requirements of geographic metaverse construction, the conceptual architecture of geographic metaverse platform is established. In the face of the emerging virtual geographic space, avatar society, and virtual–real composite human–land relationship system. In this paper we proposes to establish virtual geographic environment engineering and to promote the construction of geographic metaverse platform and related theoretical application research.Furthermore, grounded in the human-earth relationship and the technical prerequisites for the construction of the geographic metaverse, a conceptual architecture for a geographic metaverse platform is delineated. In light of the emergent virtual geographic sphere, avatar societies, and the composite virtual-real human-land relational framework, it is proposed to establish virtual geographic environment engineering as a pragmatic instrument for advancing the geographic metaverse. Virtual geographic environment engineering, predicated upon virtual reality, augmented reality, and mixed reality technologies alongside geography, seeks to explicate fundamental theories, methodological frameworks, and the engineering creation and application of virtual geographic environments to bolster global and regional sustainability endeavors.A conceptual framework for the geographic metaverse is advanced, comprising three core components. Firstly, the “Human-Object-Field-Process” mapping modeling is advocated to facilitate a three-dimensional equivalence of virtual geographical environments. Secondly, the spatial information infrastructure underpinning the geographic metaverse, encapsulating sensing, computation, and terminal technologies, is expounded upon. Thirdly, emphasis is placed on virtual geographic experimentation and management optimization, enabling innovative practices such as virtual geographical simulations and the enhancement of real geographical systems, alongside virtual social geographic experiments and the optimization of digital societal systems.It is underscored that the development of the geographic metaverse remains in its nascent phase, beset by various theoretical and technical challenges including prospective social and ethical dilemmas, the specter of virtual economic bubbles, and legal quandaries. Nonetheless, the digital spatial domain, virtual human societies, the burgeoning digital creative economy, and the emergent virtual-real symbiotic milieu are projected to engender a novel form of composite computable human-land relationships, profoundly influencing the evolutionary trajectory of global and regional human-land systems and fostering sustainable societal development.In geographic metaverse, interdisciplinary and systematic innovative research endeavors are deemed imperative, necessitating breakthroughs in foundational theories, pivotal technologies, and engineering applications. This undertaking presents a new frontier, concurrently constituting an opportunity and challenge for the innovative advancement of virtual geographic environment engineering, geographical information science, and earth sciences alike.关键词：remote sensing;Geographic metaverse;digital twin;virtual geographic environment;augmented geographic environment;computable human‒land relationship;virtual science- 237
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发布时间：2024-05-30 - “在文旅行业领域，元宇宙的快速发展正推动着行业的变革。专家基于文旅行业特征，提出了文旅元宇宙的基本定义、概念模型及主要特征，并展望了其在文化遗产数字化与保护、景区开发与管理等方面的应用场景，为文旅元宇宙未来研究提供了新方向。”
摘要：The cultural tourism industry emphasizes creativity and scene experience, which is highly compatible with the metaverse. The research of the cultural tourism metaverse is in the infancy stage. The concept, key technologies, and application scenarios are still being explored.First, the paper reviews the evolutionary process of the metaverse. The paper proposes the basic definition, conceptual model, and key features of the cultural tourism metaverse. The paper considers the cultural tourism metaverse as a subsystem of the metaverse. It is a cultural tourism Internet form formed by existing information technology in the cultural tourism industry. It is a reconfiguration and virtual symbiosis of cultural tourism activities in a 3D digital world. It provides an immersive experience of cultural tourism scenes based on extended reality technology. Based on the digital twin technology, it generates a mirror image of the real-world cultural tourism scene. It relies on the political, economic, and cultural systems under the unified architecture of the metaverse and realizes the all-around integration of the virtual world and the real world of the cultural tourism industry. The conceptual model of the cultural tourism metaverse consists of key technologies, guarantee systems, participating subjects, and product services. The development of the cultural tourism metaverse cannot be achieved without the support of key technologies. As an industry metaverse application, it does not exist in isolation. Its smooth, reliable operation is closely related to the social, political, economic, cultural, legal, and moral system established by the future holistic metaverse. The participating subjects of the cultural tourism metaverse include suppliers, consumers, developers, governors, and researchers. It is immersive, interactive, customized, cultural, educational, connected, and interdisciplinary.Second, the paper summarizes the research progress and application of key technologies in the field of cultural tourism. These key technologies include basic support technologies (such as intelligent communication, Internet of things perception, artificial intelligence, positioning and navigation, and big data computing and storage), virtual-real connection technologies (such as virtual geographic environment, digital twin, virtual digital human, and decentralization) and virtual-real interaction technologies (such as extended reality, brain-computer interface, and video games). The cultural tourism metaverse involves much more information technologies than what is mentioned in the paper. Moreover, all information technologies developed so far in the real world will be reflected in future metaverse scenarios or continuously upgraded and improved.Lastly, the authors look forward to the application scenarios of the cultural tourism metaverse such as cultural heritage digitization and protection, scenic spot (hotel) development and management, guided tour service, cultural tourism marketing, and industry supervision. The paper argues that the future research directions of the cultural tourism metaverse include personalized construction of cultural tourism virtual scenes, rapid migration of existing virtual reality cultural tourism scenes, integration of virtual and real cultural tourism scenes, seamless positioning and navigation of the cultural tourism metaverse, visitor experience and interaction, business models and monetization, and interoperability standards for virtual and real cultural tourism scenes. Metaverse development also faces issues such as ethics, security and privacy, technology, and the challenge of realistic national sovereignty. While technology is always hovering, these technologies will eventually reshape the future shape of society and human life.关键词：remote sensing;Metaverse;Cultural tourism;virtual geographic environment;Virtual and reality integration;Virtual world;Extended reality- 583
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发布时间：2024-05-30 - “在无人平台复杂环境认知领域，专家提出了一种新型机器地图建图理论模型，为数字孪生或虚拟地理环境的构建提供新目标与要求。”
摘要：Unmanned platforms are rapidly being used in many different fields. However, improving their cognition and understanding of complex environments remains a challenging research problem. Machine maps are a new class of maps proposed to address this problem. Based on the conceptual model of the machine map, this paper adopts the research perspective of cognitive science and further proposes a theoretical model of the machine map’s construction, which is cognitive, plausible, and consistent with the cognitive structure. This paper first discusses the theoretical roots of machine maps in cognitive science in terms of the origin, formation, and development of machine maps. Second, this paper briefly reviews the research on the structure and generation of memory models, mental image maps, cognitive architectures, and environmental cognition issues of robotic systems. Furthermore, it discusses the cognitive structure of the machine map and its supporting role in the map construction model of machine maps. Third, this paper proposes the design principles of the machine map’s construction model, which includes the organization of environment information using distributed representations, structural design of the machine map using a multistore memory system, and modeling of the generation of the machine map with a reference of brain cognitive activities. Furthermore, this paper presents the task objectives, content classification, detailed logical structure, and generation of the machine map’s construction. The perceptual map conducts preliminary processing of information acquired by sensors to obtain information about the features, location, geometry, and semantics of entities in the surrounding environment. The working map is functionally similar to the working memory in human brains, which contains visual information, spatial information, situational information, and specialized maps constructed to accomplish specific tasks. The long-time map uses perceptual map and working map as information sources, and the fragmented information in the perceptual map and working map is associated, managed, and processed more extensively to form an environment model with global reference. Finally, the machine map generation’s primary activities (e.g., understanding, attention, inference, learning, and action) and processes (e.g., implicit map generation and explicit map generation) are discussed based on the logical structure. Implicit map generation refers to the process in which the content and knowledge in the long-term map are continuously enriched and accumulated through the continuous evolution and support of the perceptual map and the working map during the operation of the unmanned platform. This process contains three activities: shallow understanding, deep understanding, and implicit learning. Explicit map generation refers to the process in which the working map forms a specialized map for a given task to meet the specific task requirements and supports the generation of spatial behavior under the support of itself, perceptual map, and long-term map. The process consists of six activities: superficial understanding, inference, attention, deep understanding, episodic learning, and action. The cognitive structure and map construction model, which is an interpretation of the machine map cognitive computing system, can serve as a basic framework for researchers interested in the machine map, enabling them to carry out collaborative research at a more abstract level, and provide references for the integration, evaluation, and application of related technologies and data. This paper also describes new requirements and goals for constructing digital twin or virtual geographic environments.关键词：remote sensing;machine map;cognitive logic;map construction model;unmanned platform- 62
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发布时间：2024-05-30 - “最新研究进展表明，地理信息系统在智能化矿山和工厂建设中发挥着重要作用。专家提出了工业地理信息系统IGIS的概念及数据模型，并构建了包括设备层、数据采集传输层、IGIS平台层、业务服务层和应用决策层的框架体系。该平台已在中国多对煤矿的矿井和选煤厂得到初步应用，验证了系统的实用性和可行性。”
摘要：Since the emergence of Geographic Information System (GIS) theory, technology, and software and hardware systems in the 1960s, it has been widely applied in traditional geosciences, digital cities, intelligent transportation, high-technology warfare, and other fields. On a global scale, the construction of intelligent mines and intelligent plants is the trend, the related workshops, equipment, components, and working environment are also geographical spatial objects, and spatial relationships exist among these entities. Therefore, based on the analysis of the current research and application status of traditional or existing GIS in the industrial field, this paper proposes the concept of Industrial Geographic Information System (IGIS). Based on the theory and methods of Temporal Geographic Information System (TGIS), IGIS comprehensively utilizes the information technologies such as the Internet of things, big data, digital twins, and industrial control, faces the need of intelligent production and manufacturing in the industrial field, through expressions of spatiotemporal modeling and spatial relationship of the entire scene of industrial production, equipment subsystems or components, and the entire production, and constructs a bidirectional mapping and collaborative linkage framework between digital scenes and geographic physical scenes to achieve data collection, transmission, storage, query, analysis, control, inspection, and collaborative work for the safety production of industrial spatial objects, and to provide a visual remote digital twin control platform or system for intelligent plants and intelligent mines.The research objects of IGIS have multidimensional characteristics such as macro and micro, static and dynamic, and visualization and control. Industrial objects are in dynamic changes and interconnected state, requiring feedback on the digital and physical worlds, which is a complex giant system. This paper proposes a composite spatiotemporal object model for IGIS, which is elaborated in an object-oriented manner from three dimensions: (1) In the temporal change dimension, a spatiotemporal version of the spatial object is established, and the entire spatiotemporal change in version increments is recorded. (2) In the dimension of object features, following the geometric and attribute feature expression methods of traditional geographic information system, an extensible integrated expression system for geometry and attributes of macro and micro spatial object is set up. (3) In the behavioral interoperability dimension, the behavioral state characteristics of various industrial spatial objects are demonstrated based on the business process needs of various industrial objects, and the response method of objects to their own attributes and external driving data are examined.Based on the composite spatiotemporal object model, this paper designs key functional modules such as multiscale data management, macro and micro integrated display, spatiotemporal object spatial analysis, and industrial object adaptive response and control, and proposes the IGIS technical framework. Based on unified data standards, the framework from bottom to top includes equipment layer, data acquisition and transmission layer, IGIS platform layer, business service layer, and application decision layer: (1) The equipment layer acts as the data collector and the executor of decision execution information. (2) The data acquisition and transmission layer is a channel for connection and interaction between the equipment layer and the upper layer resources, which is connected to the IGIS platform layer and the business service layer through the industrial network. (3) The IGIS platform layer is the core of the entire system, including various functions and modules to achieve adaptive response and intelligent control of industrial production processes. (4) The business service layer is responsible for the aggregation, storage, sharing, fusion, and intelligent analysis and processing of industrial production scene and process data. (5) The application decision-making layer is composed of intelligent comprehensive control centers established on many subsystems, completing intelligent production scheduling and command.Finally, key technical issues such as data standard specifications, spatiotemporal data collaborative processing, industrial environment digital twins, industrial equipment digital twins, spatiotemporal data intelligent analysis, and configuration control are elaborated, and solutions are provided to achieve integrated topological expression, storage. Analysis and collaborative control provide a unified TGIS remote control platform. The platform has been preliminarily applied in multiple coal mines and coal preparation plants in China, verifying the practicality and feasibility of the system.关键词：remote sensing;Industrial Geographic Information System (IGIS);intelligent mine;intelligent plant;digital twin;visual management and control- 8
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发布时间：2024-05-30
Scholar's View Points
- “在遥感航测领域，研究团队提出了一种基于无人机平台的地表环境实时稠密点云生成与数字模型构建方法。该方法突破了在线数据获取与位姿解算、实时稠密点云生成等关键技术，提升了建模速度30—50倍，为灾害预警救援、应急管理等提供技术支撑。”
摘要：The development of high-fidelity 3D digital model of the land surface environment in real time has become essential in many fields, including urban planning, agricultural surveying and mapping, disaster management, and military applications. Building a high-fidelity digital model of the land surface environment in real time is the key foundation for realizing the virtual mapping of the geographic environment and then forming a digital twin geographic environment. However, current methods for constructing these models suffer from several challenges such as slow speed, low timeliness, and limited application in large scenarios. To overcome these challenges, this paper proposes a new real-time dense point cloud generation and digital model construction method based on unmanned aerial vehicle (UAV) platforms. The proposed algorithm remarkably improves the speed and accuracy of land surface model construction compared with existing algorithms and improves the degree of online data collection and real-time modeling. The algorithm is based on a general simultaneous localization and mapping framework. The technical chain from data acquisition, data processing, feature extraction and matching to 3D point cloud generation, digital model reconstruction, and result analysis is unobstructed. The algorithm breaks through the key technologies in scene reconstruction such as online data acquisition and pose problem solving, real-time dense point cloud generation, digital surface model, and digital orthophoto map construction.According to the experimental results of the dataset containing different land surface environments such as cities, farmland, mountains, and deserts, the algorithm proposed in this paper can process high-quality land surface environment dense point clouds and digital models while being 30—50 times faster than existing algorithms such as Pix4DMapper. On average, it can process a high-resolution image in less than 1 second, whereas the interval for general aerial survey drones is 1—2 seconds. Furthermore, the application of the algorithm proposed in this paper to emergency rescue work of mountain flood disasters can assist in the real-time reconstruction of inaccessible areas, survey the area and location of washed-out and sediment areas, and support emergency rescue work.The proposed real-time dense point cloud generation and digital model construction method based on UAV platforms represents a considerable advancement in the field of geographic information systems. It can revolutionize various geographic fields, including disaster warning and management, emergency response, military applications, and agricultural and urban planning. Additionally, due to the breakthrough of the algorithm, it solves the core problem of real-time mapping from reality to virtual in the construction of digital twins in geographic environments. Therefore, it can empower digital twins and provide a digital foundation for digital twin applications in geographic environments. Based on the real-time mapping of 3D information of the ground environment, parallel simulation and decision making can be conducted. Therefore, it is also expected to achieve functions such as emergency warning, scheme evaluation, and decision optimization based on the dynamic monitoring of target information in the scene, further improving the automation and intelligence level of the applied system.关键词：remote sensing;Real-time reconstruction;Dense Point cloud;digital twin;Terrain environment;Digital model- 202
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发布时间：2024-05-30 - “在城市地物三维模型构建领域，研究者提出了一种基于激光扫描点云数据的树木三维模型高保真仿生重建方法。该方法通过参数化重构、精细化建模和纹理自动映射贴图，实现了树木模型的自动化重建，为智慧城市建设提供了高保真树木模型。”
摘要：Trees are an important part of the cityscape, and 3D models of trees are indispensable for real-time 3D design, construction of virtual geographic environments, and construction of digital twin cities. Current 3D models of trees are reconstructed based on images or model libraries. The former show cluttered triangular network clusters, and the latter are vastly different from the real situation in terms of geometric expression and realism, which makes directly using the reconstructed tree models in the practical applications of smart cities difficult. Therefore, in this paper, a bionic reconstruction method for 3D tree models is proposed based on high-precision laser scanning point cloud data for building realistic scenes in virtual geographic environments, which enables the automated reconstruction of 3D tree models at multiple levels of detail while preserving morphological features.First, a skeleton-based parametric tree model reconstruction method that extracts branch geometry by generalized cylinder fitting and extracts the trunk, main branches, models of fine branches, and crown elements in a hierarchical manner according to the growth parameters of the tree is proposed. Second, the refinement requirements of modeling distinct parts of trees are considered, and a refined tree geometry reconstruction method by integrating the conformal Poisson network and parametric fitting is presented. Finally, the texture mapping method is applied to map the texture of multilevel tree branches automatically to achieve a detailed 3D reconstruction of tree models by considering the texture extension of the tree structure. Based on the laser point cloud acquired with a backpack or station, this method can produce a refined 3D tree model with high accuracy of morphological features.The overall geometric error of the model is better than 10 cm, and the geometric error of the trunk model is better than 3 cm. Under the same data conditions, the method has the highest degree of reproduction of 3D tree morphology and real texture compared with various mainstream tree modeling methods. Based on the results of this paper, the method can further advance the extraction of tree structure information and the calculation of 3D green volume for the realistic 3D China and national strategies such as green low-carbon development, which have great practical value.This paper proposes a 3D bionic reconstruction method for constructing high-fidelity scenes in virtual geographic environments to achieve highly accurate geometric reconstruction and texture mapping of individual tree roots, trunks, branches, and leaves. The core of the method is to consider the requirements of distinct parts of the tree reconstruction at multiple levels of detail and integrate Poisson mesh and parameter fitting to complete the 3D reconstruction of the tree with high accuracy. The experimental results show the proposed tree 3D reconstruction method provides a highly accurate reconstruction of the tree geometry and texture. The research results are used for the accurate extraction of tree parameters, which can provide an important basis for tree structure information extraction, 3D green volume calculation, and realistic modeling and simulation of virtual geographic environments.关键词：remote sensing;3D modeling;tree reconstruction;virtual geographic environments;parametric modeling;laser point cloud- 603
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发布时间：2024-05-30 - “在三维虚拟地形生成领域，研究人员提出了一种改进的生成对抗网络方法，通过优化网络结构和训练过程，成功提高了虚拟地形的真实感和生成效率。这一成果为三维地形建模与编辑提供了新的解决方案，展现出广阔的应用前景。”
摘要：The 3D virtual terrain generation is currently used in geography teaching and setting up relevant virtual scenes according to the teaching content, which can visually display the verification experimental conditions and results and enhance the universality of virtual geography experiments. In the field of digital twin smart city, traffic, and water simulation, constructing virtual terrain according to the real terrain can provide the basic environment for subsequent development and experiments. In military simulation, it can quickly build beyond the real scenes of extreme training environment, which has a key role in improving military training and enhancing combat capabilities. Hand-drawn feature sketches can express 3D virtual terrain under human subjective perception. Therefore, how to use hand-drawn feature sketches to build 3D terrain environment quickly and generate realistic virtual geographic environment is a hot spot and difficult point for the creation and development of geographic metaverse with virtual geographic environment as the core in the future. Although the traditional method of generating 3D virtual terrain provides an important reference for image cross-domain generation from hand-drawn feature sketch to virtual terrain, problems such as insufficient realism of the generated terrain remain. Especially when the terrain feature outline is too sparse, the generated terrain will have duplicate terrain blocks and grid artifacts. On this basis, a hand-drawn feature sketch virtual terrain generation method with improved generative adversarial network is proposed. The model is based on extracted data samples and hand-drawn sketch characteristics, and the input terrain feature information is involved in the sampling of each layer by improving the generator U-Net network, which enhances the control role of terrain features in the invisible space, reduces the possibility of model collapse, increases the random noise input, and improves the realism of the generated terrain, especially the detail when the terrain feature elements in the sketch are sparse. L1 loss (mean absolute value error function) and L2 loss (mean variance error function) are combined to form smooth L1 loss, and then optimized with CGAN loss function to form a new generator loss function to improve the stability and efficiency of model training. The Digital Elevation Model (DEM) data of some areas of the Loess Plateau with high accuracy is selected to produce data. The DEM data with high accuracy are selected and used for model training to compare and evaluate the terrain generation enhancement effect quantitatively before and after model improvement. Finally, the model inference process from hand-drawn feature sketch to virtual terrain is completely constructed. The experimental results show the improved virtual terrain generation model with the Loess Plateau terrain data can represent the hand-drawn feature sketch well, and the generated terrain conforms to the distribution and orientation of the terrain features described in the sketch, especially in the case of sparse sketch, and the generated terrain has high realistic surface details. This model is applied to the real natural landscape display and terrain evolution, and it can meet the user’s needs to obtain the virtual terrain with high realistic feeling after inputting the hand-drawn terrain feature sketch. This improved model proposed in this paper has good prospects for 3D terrain modeling and editing.关键词：remote sensing;3D virtual terrain;CGANs;Hand-drawn feature sketch;DEM- 123
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发布时间：2024-05-30 -
Progress in neural radiance field and its application in large-scale real-scene 3D visualization AI导读
“在地理实景三维场景领域，神经辐射场NeRF技术的研究进展备受关注。该技术通过神经隐式立体表达和可微渲染，实现高质量视图合成，为大规模实景三维场景可视化提供了新思路。然而，目前研究在多源数据融合、视觉效果优化等方面仍面临挑战，未来值得进一步探索。”
摘要：Geographical real-scene 3D scenes are an important national digital infrastructure, which extends geographic information from 2D to 3D. Real-scene 3D data are stored and expressed in the form of an explicit 3D model, which has the problems of large amount of data and rough visualization effect. Neural Radiance Field (NeRF), realizing differentiable rendering based on neural implicit volume representation, is an innovative approach of high-quality view synthesis. First proposed by Mildenhall et al. (2020), NeRF has become one of the hottest research direction in the field of computer vision due to its realistic view synthesis effect. A large amount of literature about NeRF have been published since NeRF was proposed, and the application of NeRF in large-scale real-scene 3D visualization has begun to attract the attention of some published papers.View synthesis, which uses sparse 2D images to generate realistic new views at any viewpoint in 3D space without the reconstruction of 3D models, is a novel way to realize the representation of 3D scenes. The development of view synthesis technology has gone through several stages: image mosaicking, 3D model reprojection, view interpolation, and volume representing technology. NeRF, as an innovative approach of view synthesis, samples 5D coordinates (location and viewing direction) along camera rays, feeds those locations into a multilayer perceptron network to produce color and volume density, and uses volume rendering techniques to composite these values into a new image. NeRF not only produces remarkably higher-quality rendering than prior volumetric approaches but also requires just a fraction of the storage cost of other sampled volumetric representations. However, it faces problems such as requirements for high quality of source data, failure to support dynamic objects, low efficiency in processing, and single type of render target. Moreover, NeRF-related research are mostly conducted based on laboratory environment or standardized data at present. Due to these drawbacks, many obstacles need to be overcome before applying NeRF to large-scale real-scene 3D visualization.This paper reviews the workaround of unbounded scene, aliasing, luminosity consistency, scene relighting, and visibility field in the Block-NeRF algorithm, a variant of NeRF that can represent large-scale environments (Tancik et al. 2022). The Block-NeRF algorithm splits the environment into a set of Block-NeRFs that can be independently trained in parallel and composited during inference, and it selects relevant Block-NeRFs for rendering, which are then composited smoothly when traversing the scene. To aid with this compositing, Block-NeRF optimizes the appearance codes to match lighting conditions. It trains individual Block-NeRFs using techniques such as appearance embeddings, learned pose refinement, exposure input, transient objects, and visibility prediction.Nowadays, the studies of applying NeRF to large-scale real-scene 3D visualization are being conducted extensively, which has attracted much attention and plays a pioneering, leading role in further research. The results of these studies achieve the most basic 3D visualization large-scale real-scene effect, but they are limited by some conditions and their universality needs to be strongly improved. Because NeRF is still far from practical applications in producing large-scale real-scene 3D visualization, any slight progressive exploration is likely to become a continuous research hotspot. This paper identifies the challenges of NeRF research, including multisource data fusion, visual effect optimization, and virtual environment perception, which need more research.关键词：remote sensing;Neural Radiance Field;View synthesis;Implicit volume representing;computer vision;virtual geographic environment- 1225
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发布时间：2024-05-30 - “在地理分析模型领域，专家系统性梳理了研究进展，提出了地理分析模型容器化的新思路，为构建虚拟地理环境提供了新解决方案。”
摘要：Geographic analysis models serve as crucial resources for tackling geo-problems, simulating geographic environments, and supporting decision-making analysis. They play a key role in constructing virtual geographic environments (also known as digital twin geographic environments). Integrating geographic analysis models with diverse simulation capabilities from various fields enables a comprehensive representation of real geographical environments. This integration supports the development of visual, usable, analyzable, and interactive virtual geographic environments.This study systematically examines the current research progress in the integration methods of geographic analysis models. In general, integrating physical and social processes and merging big data with deep learning have gained increased attention in recent years. Compared with using a single model, multimodel integration enhances the understanding of the objective geographical world by integrating multiple elements and processes. Integrating models within a single domain or across domains ultimately involves basic execution links, such as combining, nesting, and connecting multiple models in a specific computing environment. In response to this, customized integration and modular integration are the main approaches to current geographical analysis model integration research. Customized integration offers tailored solutions for specific models considering cognitive and technical characteristics. However, it is heavily influenced by individual model characteristics and may become unsustainable during the integration of numerous models, leading to frequent revision activities. Modular integration relies on standardized components with clear association logic and supports component replacement. However, it faces strong technical dependencies and constraints, such as those that involve programming language, data structure, and operating environment. In practice, current model integration research often varies between customization and modularity, with the former lacking sustainability and the latter being limited by compatibility issues.In this study, the idea of a “geographic analysis model container” is proposed, and the methods are implemented to address the problems mentioned. With the assistance of the concept of containerization, the data, programs, and computing resources upon which geographical models rely are loaded into a “container.” Then, the model is developed in a customized manner within the container, while the modular model integration work occurs outside the container. Striking a balance between customized and modular approaches is anticipated to enhance the overall effectiveness of geographic modeling and simulation efforts. Conducting a multilevel, multigranularity, and multiscale integration across elements, processes, and functional relationships is necessary for addressing specific geographical problems. The development of “geographic analysis model containers” tailored to express geographical system evolution laws and driving mechanisms has become crucial.Accumulating and improving model integration capabilities based on containers is expected to establish an effective bridge between model construction, transformation, and integration. This advancement can promote geographical models from experimental tools to essential components of social service infrastructure. Decision-making analysis, solution simulation, and customized planning capabilities can be provided for various digital twin geographical scenarios (such as digital twin cities, digital twin river basins, and digital twin water conservancies) by integrating geographical analysis models. This integration drives advancements in digital twins, metaverses, and digital human technology, spanning visual experiences, operation, and maintenance management. It also incorporates geographical knowledge, enhances interactive functions, and promotes a comprehensive understanding.关键词：remote sensing;geographical analysis models;virtual geographic environment;digital twin geographic environment;model integration;geographical analysis model container- 115
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发布时间：2024-05-30 - “河北省塞罕坝机械林场的数字林业研究取得新进展，利用遥感技术实现单木信息提取和三维模型重建，开发数字林业系统，为森林经营管理提供数据支持。”
摘要：Digital forestry is the foundation of forestry informationization and modernization, which can help management with scientific programming, scientific management, and scientific decision. With the development of 3S (GIS, RS, and GNSS) technology, improving the level of digital forestry becomes feasible, especially for the monitoring scale from forest-compartment level to single-tree level by using high spatial- and spectral-resolution remote sensing data and Light Detection And Ranging (LiDAR). This paper aims to develop a forestry digital system by combining the advantages of remote sensing and GIS technology, which can improve the precision management ability of forest farm.Saihanba Mechanical Forest Farm in Hebei Province, China is taken as the research area, and airborne data, including LiDAR, CCD image, and hyperspectral image, are used to study single tree segmentation and classification methods. First, an algorithm combined water shed and Connection Center Evolution methods is applied to segment each single tree based on the airborne LiDAR scanner (ALS). Then, the random forest algorithm is applied to classify the tree species of each single tree based on the combination of the 50 characteristics from ALS, CCD, and hyperspectral image. The 3D model reconstruction is also examined by using terrestrial laser scanning data, with the procedure of branch reconstruction and leaf addition. Forest scenarios are reconstructed based on each single tree model. Finally, WebGIS technology is used to develop a forestry digital system with the functions of data storage, management, query, analysis, and visualization.More than 9706 thousand single trees within the airborne flight area of 270 km2 are segmented and classified. Combined with the survey data of ground quadrats, the single tree segmentation accuracy can reach over 0.6 matching rate, and the single tree classification accuracy of four typical tree species in the study area can reach more than 97%.The information of single tree, including location, tree height, crown breadth, and the structures of branches and leaves, are extracted based on airborne and field data, which can help analyze the multiscale forest characteristics from organs (branches and leaves)-single tree-region scales. On this basis, this paper explores the forestry digitization method based on single tree information and develops a digital forestry system using WebGIS technology. The system preliminarily completes the functions of storage, management, query, analysis, and visualization of relevant data in the study area, providing reliable basic data for forest management and decision-making planning.关键词：remote sensing;digital forestry;lidar;hyperspectral image;tree segmentation;classification;3D reconstruction- 8
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发布时间：2024-05-30
Key Technologies
- “在地理学和GIS领域，专家提出了微观人群数字孪生概念，构建了基础逻辑框架，为微观人群时空行为研究提供新视角和方法。”
摘要：raditional geography/GIS research on the spatiotemporal behavior of people focus on the meso and macro scale, while the research on the micro spatiotemporal behavior is relatively insufficient. To address this problem, first, a new concept of micro crowd digital twins is proposed. The idea is to map the real crowd and their behaviors into the virtual space, calculate and simulate the crowd behavior, mine the evolution mechanism, discover the operation rules, predict the trends, locate the abnormalities in advance, propose optimization strategies, and improve the efficiency and safety of real crowd and real society. The micro crowd digital twins can be divided into two stages, namely, special digital twins and general digital twins, according to whether they are synchronized in time between the real crowd and the virtual one.Then, the technical basis and research status of micro crowd digital twins are summarized from the aspects of crowd behavior experimental approaches, basic behavior/scenario behavior modeling, and typical applications. (1) According to the types of places and events, the crowd behavior experiment approaches can be divided into “real place-real event,” “real place-simulated event,” “simulated place-simulated event,” and “virtual place-virtual event.” (2) The status of crowd behavior modeling is summarized, which can be divided into basic micro crowd behavior models and scenario behavior models. The basic micro crowd behavior models are to model individual behaviors in a simple and abstracted space, with general interactions between individuals and obstacles. The scenario behavior models are to model crowd behaviors in complex and detailed space, with comprehensive interactions between crowds, environments, and geo-events. The advantages and disadvantages of typical basic micro crowd behavior models such as Social Force Model, Velocity Obstacle model (ORCA model), and Artificial Intelligence (AI) model are analyzed. (3) A typical case of micro crowd digital twins in a school evacuation is analyzed. The platform of digital twins of crowds is developed to simulate and examine the disordered behaviors and orderly behaviors, and the spatial layout of the school and the crowd evacuation strategies are optimized. In this manner, the special micro crowd digital twin is realized.Finally, the future research of crowd behavior experiments, crowd modeling, and theoretical system of micro human-land relationship are awaited from the perspective of geography. (1) New approaches such as credible micro crowd behavior experiment should be developed. In the crowd behavior experiments, the behavior errors caused by subjective and objective factors in crowd experiments need to be calibrated qualitatively and quantitatively, and the deviation correction algorithm should be developed to obtain reliable experimental results. (2) New micro crowd behavior modeling ideas should be proposed. Behavior models should focus on not only emergency disordered behaviors but also those orderly behaviors under the constraints of social rules and social orders in common daily conditions. The rules of individual “self-interest” used in traditional behavior modeling also need to be expanded, and the crowd interests should be introduced to build behavioral models considering “self-interest” and “altruism” rules. (3) The deterministic and stochastic characteristics of crowd behaviors should be considered. In view of the complementary characteristics of AI behavior models and traditional mathematical behavior models as well as the advantages of AI model in stochastic modeling, they can be combined to achieve this goal. (4) On the basis of the digital twinning of micro crowd, the innovative theoretical system of “micro human-land relationship” can be developed in the future, which will break through the traditional concept of “macro human-land relationship” modeling, and will make the theoretical system and modeling system of the study of human-land relationship in geography more complete. Then, the research of geography, geographic information system, and virtual geographic environments on modeling of micro crowd behaviors, micro spaces, and the applications can be promoted.关键词：remote sensing;Digital twins of micro crowd;micro spatiotemporal crowd behavior;behavior modelling;VGE;geography- 482
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发布时间：2024-05-30 - “数字孪生技术为人群行为研究带来新视角，本文构建了数字孪生人群行为实验理论框架，通过VR实验揭示了群组疏散行为特征，为地铁站疏散规划和应急预案提供优化建议。”
摘要：The concepts of “digital twin” and “meta-universe” provide new ideas for the field of crowd behavior simulation. Using digital twin methods to conduct crowd behavior experiments to obtain data and then researching on human spatial and temporal behavior in specific scenarios have become important directions in the field of crowd simulation and indoor GIS research. Digital twin crowd behavior experiment is an innovative geographical experiment to explore crowd behavior, geographical phenomena and processes, and human-geography relationship in a real geographical environment. This paper proposes a theoretical framework for conducting digital twin experiments on crowd behavior from experimental purpose, object, process, evaluation, and results and analysis. The framework summarizes the basic theories, including geographic cognitive, similarity, scale, complexity problem, and geographic intelligence simulation theories. We also summarize the experimental principles of digital twin crowd behavior, such as experimental similarity, collaboration and heterogeneity, and standardization and normalization. Furthermore, we propose the content and classification of experiments on digital twin crowd evacuation. On the basis of this theoretical framework, a VR-based social group evacuation digital twin experiment is conducted in the Olympic Park Station. The spatial structure and evacuation behavior of social groups are qualitatively and quantitatively analyzed using experimental data. We evaluate the spatial structure characteristics of two- and three-member social groups, the characteristics of the angle and distance between social group members, the information diffusion way within social group members, and the evacuation and eye-tracking point trajectories of social groups. Results show that during the evacuation process, social group members exhibit V and “side-by-side” structures. They maintain a compact spatial structure in an emergency, indicating that group members have the desire to find a safe exit together, and this willingness has a crucial effect on crowd evacuation behavior. In some special areas such as stairs and escalators, the spatial structures of social groups have significant changes. They show a tendency to improve the walking speed through these areas as soon as possible rather than to maintain the compact spatial structures. The angle between the facing direction of an evacuee and that of other social group members is less than 60°, and smaller distances and information diffusion interactions among social group members significantly improve the evacuation efficiency. The analysis of the evacuation and eye-tracking point trajectories in the digital twin scenario reveals that the evacuating crowd interacts considerably with pillars, exits, and transfer channels, indicating a great need for direction information in these areas. Optimizing an evacuation sign system in these key areas can greatly improve the evacuation efficiency. The above findings on crowd behavior are of great significance to crowd behavior modeling, and the digital twin experiment results can identify bottleneck areas in the subway station selected in this study, providing optimization suggestions for layout design and emergency plans. The ability of subway station managers to predict and respond to emergencies can be further strengthened. The results of this study have important practical application value to reduce personal and property losses in disaster events.关键词：remote sensing;digital twin;crowd behavior experiment;subway evacuation;social groups;interactive behavior- 8
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发布时间：2024-05-30 - “在防洪领域，数字孪生流域技术取得新进展。专家构建了虚拟地理环境技术框架，为流域防洪中人地关系建模及洪水场景表达与风险认知提供新视角和方法。”
摘要：Flood control is the main application field of the digital twin basin. The application of flood control in the digital twin basin not only needs to express the natural elements in the basin scientifically but also must describe the characteristics of human activities. Virtual geographic environment integrates natural elements and human elements, focuses on building an immersive experimental and cognitive environment, and provides a new perspective and method for the modeling of man-land relationship, flood scene expression, and risk cognition in the digital twin basin flood control. This article takes the application of digital twin watershed flood control as research field and proposes a four-layer technical framework for digital twin watershed flood control based on virtual geographic environment. The resource layer covers the hardware resources involved in data acquisition, storage, and calculation in the digital twin watershed flood control application, and realizes unified storage from global watershed feature awareness to data baseboard framework. The data layer provides the relevant data foundation for digital twin flood control applications, including four categories of data: basic data, business data, monitoring data, and geographic data. It also provides the twin layer with the necessary data service support through the steps of data resource extraction, aggregation, cleaning, conversion, and governance. The twin layer is the core of the technical framework, reflecting the interactive mapping between the model watershed and the real watershed. Model watersheds focus on building water models and human-land relationship models. Based on the natural laws of the water cycle, mathematical language and methods are used to describe the changes in the elements of a real watershed, reflecting the laws of human activity and the correlation between human activities and the natural elements of the watershed. Real watersheds lead the construction of digital twin watersheds, upgrade traditional monitoring systems, enhance automatic monitoring and computational feedback control of digital twin watersheds, and support flood control construction and management of watersheds. The application layer is based on the main idea of virtual geographic environment, relying on wearable technology, eye movements, gestures, brain wave, large screens, digital sand tables, and other devices to provide a multiuser, touchable, interactive, and scene-responsive digital twin watershed environment. On this basis, the “four pre” application of digital twin watershed flood control is conducted. Subsequently, the paper elaborates on key technologies such as digital watershed scene construction, digital watershed state synchronization, flood spatiotemporal process modeling and experiment, human-land relationship modeling, and flood scene expression and risk perception, and looks forward to the future development of VR/AR applications in digital twin watersheds and public participation in flood control. The research trend of virtual geographic environment in digital twin river basin flood control can be summarized as follows: further developing relevant disciplines such as geographic human-land relationship, geographic spatial cognition, and behavioral geography; constructing an immersive flood evacuation spatial cognitive environment that allows participants to obtain real-time, authentic, and rich environmental information for interdisciplinary research; and conducting cognitive experiment activities with public participation.关键词：remote sensing;virtual geographic environment;digital twin basin;flood disaster;augmented reality;metauniverse- 107
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发布时间：2024-05-30 - “在桥梁建设领域，数字孪生技术为实现智能化提供了新途径。本文分析了数字孪生在桥梁智能建造中的应用背景和发展趋势，提出了全过程数字孪生构建方法，并探讨了关键技术。以复杂山区大型桥梁为例的案例分析，为复杂环境大型桥梁工程智能建造提供了理论指导和技术支持。”
摘要：In recent years, China’s infrastructure construction has expanded into remote, rugged mountainous regions, making bridge construction more challenging than ever before. These difficult environments make collecting data, simulating scenarios, and managing information effectively extremely challenging, resulting in the need for improved quality assurance during construction. To meet these challenges, the concept of digital twinning has emerged as a crucial tool for achieving intelligent construction. By mapping the attributes, structures, states, performances, and behaviors of real-world bridges onto a virtual twin, a highly realistic, interconnected digital representation of the bridge and its surroundings can be created. This virtual geographic environment provides a powerful means of comprehending and controlling the construction more precisely. This paper provides an in-depth analysis of the background and development trends of high-precision digital twinning for bridges and their environment as well as intelligent bridge construction. This paper introduces the theory of virtual geographic environments and digital twinning, and explores the use of dynamic data and simulation models to drive spatial modeling and virtual-real mapping throughout the bridge construction. The proposed approach is divided into four stages. First, a monitoring data correlation fusion model is constructed by integrating space, air, and ground monitoring technology. This step enables data perception of the physical space of the bridge construction and makes information on the bridge construction visible. Second, intelligent modeling methods are studied for the digital twinning scene of bridge construction. This step achieves a refined characterization and accurate description of the bridge construction environment using advanced modeling techniques. Third, dynamic simulation and intelligent prediction methods are established for bridge construction. This step utilizes the bridge construction digital twinning scene and combines it with multisource monitoring data to enable dynamic diagnosis, evaluation, and intelligent prediction of the states and quality of bridge construction. Fourth, the bridge data, simulation models, and modeling knowledge are integrated to establish an intelligent management mechanism for the entire bridge construction. This step enables actively controlling the construction, completing the iterative and interactive evolution, and achieving an intelligent closed-loop of “data perception-simulation analysis-intelligent prediction-optimization control” of bridge construction. To validate our methodology, a case study of a large bridge constructed in a complex, difficult mountainous area is presented. Our approach provides effective theoretical guidance and key technological support for the intelligent construction of large bridges in complex environments.关键词：remote sensing;virtual geographic environment;intelligent construction of bridge;digital twin;simulation prediction;intelligent modeling- 668
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发布时间：2024-05-30 -
A preliminary study of semantic virtual geographic environment in the context of wetland monitoring AI导读
“在地理分析领域，专家提出了语义虚拟地理环境，利用知识图谱和实时数据，实现对现实地理环境的映射和语义整合，为湿地监测等提供知识化搜索和决策支持。”
摘要：The abundance of geospatial big data has created unprecedented opportunities for the development of Virtual Geographic Environments (VGEs), but with the gradual ease of data acquisition, VGEs generally suffer from the problem of being “visual” but not “intelligent” and have yet to meet the demand for real-world geographic environments that are computable, manageable, and decision-ready. This paper first summarizes the challenges that geospatial big data pose to virtual geographic environments and proposes that improving the semantic interoperability of geospatial big data is the key to solving the aforementioned problems in virtual geographic environments. This involves using a machine-readable and human-understandable language to establish semantic relationships between data in a structured manner within virtual geographic environments. Therefore, the concept of Semantic Virtual Geographic Environments (SVGEs) is proposed. Semantic Virtual Geographic Environments use Semantic Web technologies such as ontologies and knowledge graphs to unify the description, management, and analysis of fragmented, unstructured, and non-explicitly related raw data generated by geographic objects and geographic processes in real-world environments with more standardized semantics, thus building a highly integrated digital geographic environment with data connectivity and interoperability. Semantic Virtual Geographic Environments are a type of virtual geographic environment that is semantically enhanced in the context of geospatial big data. SVGEs have characteristics such as knowledge-driven, semantic collaboration, and structural unity. Considering that the knowledge graph is the culmination of knowledge engineering in the era of big data, it can provide solutions for data knowledge organization and intelligent application in virtual geographical environment due to its powerful semantic expression ability, storage capacity and reasoning ability. Therefore, the semantic virtual geographic environment can use the knowledge graph as the formal expression of the real geographic environment, and form the mapping of the real geographic environment in the virtual space by integrating the real-time perception data and the interactive data information between the virtual and the real. Finally, this article takes wetland monitoring as an example and combines knowledge graph with virtual geographic environment to construct a semantic virtual geographic environment for wetland monitoring. Based on the characteristics of wetland monitoring data, conceptual modeling and formal expression of monitoring data were carried out, and a wetland monitoring ontology was constructed. The knowledge graph ontology can achieve a comprehensive, clear, and unambiguous description of monitoring data, laying the foundation for interoperability of monitoring data in virtual geographic environments. On the basis of wetland monitoring ontology, large-scale multi-source heterogeneous monitoring data is semantically mapped, achieving dual integration of isolated and scattered monitoring data in both logical and physical aspects in a virtual geographic environment. Then, the rich semantic relationships between monitoring data can be utilized to achieve knowledge-based search of monitoring data. In addition, the semantic virtual geographic environment also has strong inference ability, which can generate new knowledge through inference from native associated monitoring data, thus providing support for the comprehensive information management decision-making of wetlands. This study is a preliminary attempt to explore the theory, methods, and applications of semantic virtual geographic environments. However, further exploration is needed to truly achieve the full utilization of data in virtual geographic environments.关键词：remote sensing;virtual geographic environment;semantic virtual geographic environment;Knowledge Graph;ontology;wetland monitoring- 100
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发布时间：2024-05-30 - “在环境管理领域，研究人员提出了一种多粒度时空实体建模方法，通过建模分析污染企业时空实体特征和关系，实现污染企业数字孪生体模型的精准构建，为污染企业场地管控智能化提供有效方法和数据模型基础。”
摘要：Digital twin entity refers to the information model that exists in the computer virtual space that is completely equivalent to the physical entity, which is a multidimensional, multiscale description and portrayal of the physical entity, and can achieve the real mapping and simulation analysis of the physical entity. The field of ecological environment has many types of soil-groundwater pollution sources and pollutants in production enterprises, complex source-sink relationship, pollution early warning, and traceability difficulties. The use of digital twinning technology must be studied to establish a real-life 3D model of the plant area of the production enterprise and a digital twin model within the plant, incorporate real-time monitoring data into the simulation system of soil and groundwater twinning, carry out rapid data fusion and simulation derivation, and eventually form a complete digital twin system of a multigranularity polluting enterprise plant. When facing the above problems, the current construction method of digital twin model focuses on the construction of a 3D model, ignoring the complete expression and description of the enterprise entity’s geometrical parameters, attributes, relationships, and other characteristic data, so it is unable to meet the requirements of comprehensively and multidimensionally dynamic portrayal of the enterprise entity. To achieve the accurate construction of the twin entity model of the pollution enterprise, a more efficient way needs to be adopted to organize and manage the characteristic data of the enterprise entity, and select a suitable data model to model the enterprise scene. The traditional GIS data model uses conventional map data as a template for indirect spatial modeling of entities, which limits the application of spatial data and hinders adapting to new expression needs such as real-time dynamic correlation in multimodal situations. To address this problem, Hua Yixin proposed a multigranularity spatiotemporal object data model from the perspective of data model. The model provides an all-round description of multigranularity spatiotemporal entities from spatiotemporal reference, spatial location, attribute characteristics, spatial morphology, and compositional structure, with multidimensional and all-attribute characteristics. The model also increases the description of characteristic information such as behavioral ability and association relationship, and the expression content is more comprehensive and more in line with the actual entity expression. Therefore, this paper proposes a multigranularity spatiotemporal entity modeling method for constructing a digital twin of a polluting enterprise, which achieves the comprehensive multidimensional information description and portrayal of the site entity of a polluting enterprise in the form of a data model by modeling, and analyzing the relevant features and relations of the spatiotemporal entity of the polluting enterprise. A rubber factory in Guangzhou City is taken as a case study for instance validation of the data model.Results show the multigranularity spatiotemporal entity modeling can efficiently organize and express the multidimensional features of the entity, achieve the accurate construction of the digital twin body model of the pollution enterprise, and provide an effective method and data model basis for the application service of the digital twin of the pollution enterprise.关键词：remote sensing;polluting companies;digital twins;entity feature data;multi-granularity spatio-temporal entity modelling;data models- 9
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发布时间：2024-05-30
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