Joint International Conference on
Theory, Data Handling and Modelling in
GeoSpatial Information Science

Hong Kong, 26-28 May, 2010









Michael F. Goodchild, Professor, University of California, Santa Barbara
Title: Twenty years of progress: Giscience in 2010

Abstract: The concept of a science of geographic information has its roots in the early 1990s, and discussions over whether GIS is more than a tool. Three major lines of thought developed at that time: those centered on the individual, on society, and on technology. Many substantial research results have been obtained in all three areas.
Today geospatial technology is more important than ever, and new research directions are emerging, again based in the same conceptual framework. The presentation ends with some speculations on the future of GIScience.

Michael F. Goodchild is Professor of Geography at the University of California, Santa Barbara, and Director of spatial@ucsb. He received his BA degree from Cambridge University in Physics in 1965 and his PhD in Geography from McMaster University in 1969.

He currently chairs the Advisory Committee on Social, Behavioral, and Economic Sciences of the National Science Foundation. His current research interests center on geographic information science, spatial analysis, and uncertainty in geographic data.












Deren Li, Proffessor, Wuhan University
Title: The new era for Geo-infomation

Abstract: Along with the forthcoming of Google Earth, Virtual Earth, the next generation of Internet, Web 2.0, Grid Computing and smart sensor web, comes the new era for Geo-Information. In this paper, main features of new Geo-Information era are discussed. This new era is characterized by these features: serviced users are extended from professionals to all public users, the users are data and information providers as well, provided geospatial data are no longer measurement-by-specification but measurement-on-demand through smart sensor web, and services are transferred from data-driving to application-driving. Such problems as out-of-order issues in geographic data collection and information proliferation, quality issues in geographic information updating, security issues in geographic information services, privacy issues in sharing geographic information and property issues on sharing geographic information, which are brought about by new geo-information era, especially problems and challenges confronted in geo-information science and geo-spatial information industry, are analyzed. Then strategies concerning standards, planning, laws, technology and applications are proposed.

Prof. Li Deren is professor and PhD supervisor of Wuhan University, member of the Chinese Academy of Sciences, the Chinese Academy of Engineering and the Euro-Asia International Academy of Science.

He has concentrated on the research and education in spatial information science and technology including remote sensing (RS), global positioning system (GPS) and geographic information system (GIS). His recent research interests include theories and methods for spatial information multi-grid, data mining and knowledge discovery, theories and applications of generalized and specialized spatial information grid, etc.








Daniel Griffith, Professor, University of Texas at Dallas
Title: Deriving space-time variograms from space-time autoregressive (STAR) model specifications
Abstract: Many geospatial science subdisciplines analyze variables that vary over both space and time. The space-time autoregressive (STAR) model is one specification formulated to describe such data. This paper summarizes STAR specifications that parallel geostatistical model specifications commonly used to describe space-time variation, with the goal of establishing synergies between these two modeling approaches. Resulting expressions for space-time correlograms derived from 1st-order STAR models are solved numerically, and then linked to appropriate space-time semivariogram models.

Daniel A. Griffith is an Ashbel Smith Professor of Geospatial Information Sciences in the School of Economic, Political and Policy Sciences at the U. of Texas at Dallas.

He received his PhD in geography from the U. of Toronto, his MS in statistics from the Pennsylvania State U., and his MA in geography and his BSc in mathematics from Indiana U. of Pennsylvania.

His hundreds of publications appear in geography, regional science, and statistics, as well as ecology, economics, epidemiology, and mathematics outlets.























Manfred Fischer, Full Professor, Vienna University of Economics and Business
Title: Principles of neural spatial interaction modelling

Abstract: Spatial interaction modelling of the gravity type is one of the major intellectual achievements and at the same time, perhaps the most useful contribution of spatial analysis to social science literature. The interest in such models is motivated by the need to explain flows of tangible entities such as persons and commodities or flows of intangible entities such as information and knowledge across space. The models make use of a discrete representation of space and typically rely on three types of variables to explain mean interaction frequencies between origins and destinations of interaction: (i) origin-specific variables that characterize the ability of the origins to generate flows, (ii) destination-specific variables that represent the attractiveness of destinations, and (iii) origin-destination-specific variables that characterize the way spatial separation of origins from destinations constrains or impedes the interaction.
The focus of this speech is on neural spatial interaction models that are closely related to spatial interaction models of the gravity type. Such models are termed neural in the sense that they are based on neurocomputing, inspired by neuroscience. We start with clarifying the problem of neural spatial interaction modelling, the problem to approximate an unknown spatial interaction function on the basis of given samples, and will consider approximations obtained using single hidden layer feedforward networks with one output node representing the OD flows. The network inputs represent origin, destination and origin-destination variables, and the network weights the model parameters.

Building a neural network model for a particular spatial interaction problem is a non-trivial task that typically involves three types of problems: first, the problem of choosing an appropriate network architecture (the model selection problem), second, the problem of determining the network parameters given the architecture (the parameter estimation problem), and third, the problem of assessing the generalization performance of the model (the testing problem). We will discuss these problems in some detail and suggest some solutions based upon current state-of-the-art principles.

Manfred Fischer is a Full Profssor in Institute for Economic Geography and GIScience, Dean, Department of Social Sciences, and Head, Institute for Economic Geography and GIScience.

He finish his Doctoral Studies in Geography and Mathematics in Friedrich Alexander University of Erlangen in 1975, and got his Post-doctoral qualification in 1982.

His research experties covers Spatial Economics and Economic Geography, Regional Science and Regional Economics, Spatial Analysis, GeoComputation and Spatial Econometrics, Innovation Economics, Transportation and GIS-T. He has published more than 100 journal articles, 31 monographs/edited books, 19 invited contributions to handbooks and encyclopedia, and 94 book chapters.




















Anthony G.O. Yeh, Chair Professor, The University of Hong Kong
Title: GIS as planning support system

Abstract: The development of GIS has a very close relationship with urban planning. GRIDS in the 1960s and IMGRID in the 1970s were developed to carry out map overlap analysis which is fundamental to urban and regional planning. In the early days of the development of GIS in the 1960s and 1970s, there were very few planning departments that installed GIS because of their expensive hardware and limited software and data. The decrease in the price of hardware, computer storage and devices, and accompanying improvement in the performance of hardware and software (particularly the speed of computer processors) and advancement in the data structure and related algorithms of vector-based GIS, has made the once expensive and time consuming GIS to be more affordable and workable. GIS is now more accessible to planners and is an important tool and database for urban planning both in the developed and developing countries. Recent development in the integration of GIS with planning models, 3-D visualization, virtual reality and the internet will make GIS more useful as a planning support system for urban and regional planning. Today, the main constraints in the use of GIS in urban planning are no longer technical issues, but the availability of data, organizational change, and training. If these constraints can be removed, GIS will be a more effective planning support system for urban and regional planning.

Anthony G.O. Yeh is Chair Professor of the Department of Urban Planning and Design and Director of Manfred of the Centre of Urban Studies and Urban Planning and GIS Research Centre at the University of Hong Kong. He is an Academician of the Chinese Academy of Sciences and a Fellow of the Hong Kong Institute of Planners (HKIP), Royal Town Planning Institute (RTPI), Planning Institute of Australia (FPIA), British Computer Society (BCS) and the Chartered Institute of Logistics and Transport (CILT). He received the UN-HABITAT Lecture Award in 2008.

His main areas of specialization are in the applications of geographic information systems (GIS) as planning support system, and urban development and planning in Hong Kong, China, and S.E. Asia. At present, he is the Secretary-General of the Asian Planning Schools Association and Asia GIS Association. He has been the Founding President of the Hong Kong GIS Association, Vice President of the Commonwealth Association of Planners, Vice President of the Hong Kong Institute of Planners, Chairman of the Geographic Information Science Commission of the International Geographic Union (IGU).