Ikuho YAMADA Associate Professor 2010-  (Division of Spatial Information Analysis)
Further information available at http://www.csis.u-tokyo.ac.jp/‾iku.yamada/

Spatial Analysis on network space and detection of local spatial patterns

While the majority of traditional spatial analysis methodology relies on the planar space assumption, there exist spatial phenomena where occurrence of events is ruled by a given network space such as a highway network or a river system. To investigate such network-constrained spatial phenomena in an effective and appropriate manner, it is necessary to develop specific methodology that explicitly incorporates various constraints imposed by the network space. Similarly, as detailed spatial data have increasingly become available to researchers, analysis of more localized spatial patterns is called for. Local Indicators of Network-Constrained Clusters (LINCS) framework combines the two concepts to facilitate development of exploratory data analysis methodology for detecting local-scale clustering in network-constrained spatial phenomena.

Spatial monitoring

Spatial monitoring is a type of spatial-temporal analysis that is designed to detect changes in spatial data updated regularly (and preferably in real time) in a prospective manner, while traditional spatial analysis is generally concerned with data collected for a given point or points in time in a retrospective manner. Spatial monitoring combined with GIS techniques is applicable to broad scope of spatial problems such as detection of disease outbreaks and bioterrorism, and my colleagues and I developed GeoSurveillance software to facilitate such applications.

Neighborhood effects on human health (especially on the obesity epidemic)

Influence of neighborhood living environments on human health has long been recognized and recent advancement in GIS and availability of detailed spatial data enables micro-scale investigation of potential relationships between the environments and health. Obesity is one of the health problems for which such neighborhood effects are of great interest since individual-level risk factors such as behavioral characteristics and genetics alone cannot explain the current serious epidemic. Neighborhood walkability and food environment are considered to be important contextual factors to understand the mechanism of the current obesity epidemic.