Data model
Including: mapping methods of Geographic space and geometric algebra space, representation method for continuous and discrete Geographic objects, scene data model, GIS data structure and Geographical law-based data index.
Yuan Linwang, Male, born in November 1973, Jiangsu Haian, Ph.D., professor, doctoral supervisor, winners of National Outstanding Youth Fund. In 1995, he graduated from the department of Geography of Nanjing Normal University. In 1998 and 2001, he received the master degree in Cartography and Remote Sensing from Nanjing Normal University and a doctorate in Physical Geography. From 2009 to 2010, he studied in the University of Texas at Dallas as a visiting scholar. He was selected as the "talent training program for the new century" of the ministry of education, the "youth academic leader of qinglan project" in jiangsu province and the "100 leading talent training program" of the University. Won the third jiangsu province youth geography science and technology award and jiangsu excellent teaching achievement first prize. His academic participation include "deputy director of the youth workgeographical of society of China", "director of the GIS and technology specialized committee of the remote sensing and GIS in Jiangsu province,...
Read moreResearch Direction
Computation model
Including: new GIS computing framework, Computating operator library, Analyze template with unified structure, algorithm development methods based on scripting, algorithm optimization and parallelization.
Analysis model
Including: adaptive integration and transformation of geographic models; embedding of GIS dynamic models, embedding of structural feature models, embedding of continuous geographic models.
GA based GIS system
Including: System architecture, Computating operator library, Computing engine, System functions and screenshots, Typical analysis cases, e.g. case study of 3D city, Antarctic sea-land-ice evolution, emergency evacuation and so on.
The Latest Progress
1. Introduction to the report
From October 24th to October 25th, 2020, Professor Yu Zhaoyuan participated in an academic seminar on geographic information perception and service organized by the Institute of Geographic Information and Tourism of Zhangzhou College, and gave an academic report entitled “Quantum Simulation Model Study of Highway Traffic Flow”. Based on the problems existing in the classical traffic flow simulation model, the paper introduces the cause of the study of quantum traffic simulation model, puts forward the highway traffic flow simulation model based on quantum resonants and quantum random walk, constructs the non-observable human social process dynamic simulation method based on quantum random travel, and realizes the accurate simulation and scenario prediction of near-individual particle degree intercity highway traffic flow. Read More
On 20 October 2020, Associate Professor Rowan joined other teachers and some graduate students in the ENGAGE at workshop at CGI 2020 conference and gave an academic presentation entitled “Geometric algebra-base multilevel declassification method for geographical field data”, The report discusses the need for multi-layered GIS data decryption due to the diversity of GIS application patterns, for example, the need to decrypt publicly used data to hide confidential spatial information, the common arrangement of data that is not a regular encryption method, and the need to preserve general geospatial characteristics of the restored data. In addition, different levels of restore are required when faced with different levels of confidentiality.The report describes the use of geometric algebra (GA) to achieve a controlled method of precision decryption and restoration. The geographic field is represented as a GA object and further implements a uniform represent of the field. Read More
The 2020 Geographic Information Technology Innovation Conference, held in Beijing from October 13-16, 2020, was jointly organized by the China Geographical Information Industry Association, the China Surveying and Mapping Society, the China Regional Science Association, the China Mayors Association, the School of Earth and Space Sciences of Peking University, the School of Resource and Environmental Sciences of Wuhan University, Yi Zhirui Information Technology Co., Ltd. Pay attention to the typical and innovative application of geographic information technology by users in various industries. The conference will bring together scholars, experts, enterprises, education and other forces in the field of geographic information to explore the innovative value of geographic information technology in promoting information exchange and information management in the human world. Professor Yu Zhaoyuan reports online, which explores the theoretical methods, key technologies and typical applications of the urban information model (CIM) based on holographic map technology, starting from the concept and connotation of the urban information model. Read More
From September 10 to 11, 2020, the 255th Shuangqing Forum of the National Natural Science Foundation of China (NSC) was held in Beijing. Professor Yuan Linwang participated in the forum and made a special report on “Digital Twins and Virtual Experiments for Multi-Scale Modeling of Land and Sea Interfaces”, which reads: Digital Twin and Virtual Experimental Technology establishes digital mapping of the real world and its features, processes and mechanisms by integrating all kinds of observation data and model patterns under a unified space-time framework, and using virtual simulation and other means. The sustainable development of coastal zone involves the interaction of multi-layer, multi-domain and multi-scale elements, the development of digital twin technology and virtual experimental method of multi-scale modeling of land-sea interface, the convergence of multi-domain and multi-scale space-time data under the unified space-time framework, the integrated modeling and big data intelligent analysis of multi-pattern coupling across the circle layer, and the provision of virtual twin coastal multi-modal fusion expression and multi-scenario virtual experiment with real perception and feedback control. Read More
Results Demonstrate
The Latest Publishment
Irregular geographic spatio-temporal-field data have been rapidly accumulating; however, data organizations and operations for different irregular types are often segregated, leading to systematic drawbacks, such as interface expansion difficulty and high coupling codes in GIS implementations. The paper proposes a unified approach to organizing and operating irregular geographic spatio-temporal-field data. The proposed approach has two components, namely ‘concepts and definitions’, and ‘logical model’. The first component introduces the concept of primitive elements, which are formal sets of data points, to serve as the smallest building blocks in the data organization. We define the corresponding primitive elements for three prevalent irregularity types (including sparse, imbalanced, and heterogeneous). The second component utilizes object-oriented programming to support the implementation of various operators. Additionally, we develop the layered architecture to decouple data organization, operation, and visualization to assure low coupling among layers. For demonstrations, we conduct case studies to show the effectiveness of our approach. Additionally, we conduct experiments to new irregularity types and illustrate the flexibility and scalability of our approach. Comparisons with classic tensor methods and spatio-temporal analysis methods show that our approach has more comprehensive supports for different data types.
At small granularity (e.g., 10-minutes to hourly), expressway traffic volumes rely heavily on drivers' driving habits heterogeneity and decision randomness, making it challenging for accurate modeling. In this paper, we propose a small granularity simulation model named Small-Granularity Expressway Traffic Volumes with Quantum Walks (SGETV-QW). The proposed model adopts quantum walks to generate probability patterns of the exiting time of drivers from the expressway. Then, we refine and map the generated probability patterns to empirical traffic-volume data via a stepwise regression and quantify the modeling accuracy in both the time and frequency domain. We validate SGETV-QW for traffic volume data from seven stations along the Nanjing-Changzhou Expressway in China and compare it with Autoregressive Integrated Moving Average Model (ARIMA) and Long and Short-Term Memory (LSTM) networks. The results show that SGETV-QW improves the simulation accuracy at small granularity. In addition, traffic volumes simulated by SGETV-QW have almost the same frequency spectrum as observed traffic volumes. Finally, we conduct a sensibility analysis and show that SGETV-QW can adapt its parameters to model traffic volumes at different granularities.
Lossy compression has been applied to the data compression of large-scale Earth system model data (ESMD) due to its advantages of a high compression ratio. However, few lossy compression methods consider both global and local multidimensional coupling correlations, which could lead to information loss in data approximation of lossy compression. Here, an adaptive lossy compression method, adaptive hierarchical geospatial field data representation (Adaptive-HGFDR), is developed based on the foundation of a stream compression method for geospatial data called blocked hierarchical geospatial field data representation (Blocked-HGFDR). In addition, the original Blocked-HGFDR method is also improved from the following perspectives. Firstly, the original data are divided into a series of data blocks of a more balanced size to reduce the effect of the dimensional unbalance of ESMD. Following this, based on the mathematical relationship between the compression parameter and compression error in Blocked-HGFDR, the control mechanism is developed to determine the optimal compression parameter for the given compression error. By assigning each data block an independent compression parameter, Adaptive-HGFDR can capture the local variation of multidimensional coupling correlations to improve the approximation accuracy. Experiments are carried out based on the Community Earth System Model (CESM) data. The results show that our method has higher compression ratio and more uniform error distributions compared with ZFP and Blocked-HGFDR. For the compression results among 22 climate variables, Adaptive-HGFDR can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity and fast changing rate. This study provides a new potential method for the lossy compression of the large-scale Earth system model data.
Due to the increasing complexity of GIS data and service modes, there is an urgent need for the next generation of GIS with new representation and computation methods. A number of spatiotemporal models, analytical and visualization methods, as well as system architectures have been proposed. However, previous studies failed to integrate basic geographical theories with latest computing technologies. Without a well-defined body of underlying theories, new models and methods are limited in scope and not able to meet the ultimate requirements of the next-generation GIS, which demands multidimensional, highly dynamic and semantic-rich representations and computational power. Geometric algebra (GA) provides an ideal tool for the expression and calculation of multidimensional geometric objects, and has proved to be effective for GIS representation and computation applications in our previous studies. We propose to use GA as the basic mathematical language for the establishment of the next-generation GIS. We present the framework of a GA-based next-generation GIS and describe the representation space, data structure, and computational models in this paper. A few issues that have not been sufficiently addressed by previous studies are discussed in detail with potential solutions proposed. These include multi-scale representations, modelling of geographic processes, simulation of geographic interactions, and multi-element modelling. The GA-based next-generation GIS uses an integrated structure consisting of a theoretical architecture, model for information expression, and computational methods. Implementation of the approach aims to improve GIS capacities in applications such as global spatiotemporal modelling and analysis, regional geographic modelling and simulation, smart city applications, and many others.