立命館大学グローバルCOE　GCOEセミナー

2009年4月13日

番外編（Vol.10）　GCOEセミナー

ゲストの講師をお迎えしてのセミナーになります。

1.「移送モデリングと伝染病感染分析のための、行動をベースとした時空間データモデル」
An Activity-Based Spatio-Temporal Data Model for Transport Modelling and Epidemics Transmission Analysis

講師：Dr. Tao Cheng　（Dept of Civil, Environmental & Geomatic Engineering, University College London）

2.「Geodemographics 2.0―地理的人口統計学モデルの仕様・評価・テストにおけるいくつかの展開」
Geodemographics 2.0: Some Developments in the Specification, Estimation and Testing of Geodemographic Models

講師：Dr. Alex Singleton　（Centre for Advanced Spatial Analysis (CASA), University College London）

日時：2009年4月13日（月）　11:30～13:00
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場所：【衣笠】立命館大学アート・リサーチセンター　多目的ルーム
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https://www.arc.ritsumei.ac.jp/dhjac/ppt2009/haihusiryo-index.html
 

【要　旨】
1.Dr. Tao Cheng
Title: An Activity-Based Spatio-Temporal Data Model for Transport Modelling and Epidemics Transmission Analysis
Abstract: Recently GIS have been used in the surveillance and monitoring of diseases and control of epidemics. Most of those mapping systems use aggregated datasets. This aggregated datasets are not sufficient to support the analysis of epidemiological transmission if the disease is spread mostly person by person from region to region such as SARS - Severe acute respiratory syndrome. This paper develops a mobility-oriented spatio-temporal data model to support SARS transmission analysis in a GIS environment by identifying spatial and temporal opportunities for activity participation. The model can support the tracing and predication of spatially varying, temporally dynamic and individually based epidemiological phenomena. A prototype system based on the data model is implemented by a case study based in Hong Kong.

2.Dr. Alex Singleton
Title: Geodemographics 2.0: Some Developments in the Specification, Estimation and Testing of Geodemographic Models
Abstract: The world is becoming increasingly urbanized, complex and connected.These changes are driving a demand for better information that can be used to make effective decisions about the organisation, flows and connectivity of people, processes and place. While decennial census have in the past been appropriate to monitor these changes, the rate and scale of current population change is making these large surveys increasingly redundant. Through better integration of a range of data sources it is proposed that new horizons can be opened up for analysing the different characteristics of populations and their behaviours. Key to making effective choices across a range of spatial problems is the ability of decision support tools to present areal data from a range of attributes in an understandable format. For example, one may be interested in a local measure which represents school attainment, deprivation and GP referrals for obesity. The dimensions in this example could all be measured independently from national coverage datasets, however, there are a series of challenges related to their amalgamation into a single measure including considerations of scale differences, data normalisation, weighting, method to reduce dimensions and presentation/ visualisation. The core challenge of this research agenda is how a range of attributes across multiple scales can be easily manipulated, interpreted, and displayed as online maps, graphs and descriptions by end users with limited statistical ability. This raises a range of technical computational challenges relating to the integration of large and possibly disparate spatial databases, data normalisation and optimisation for fast transactions related to on-the-fly computation of bespoke classification or measures, and the presentation of these data using GIS Map Servers.
 

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