Professor, Division of Spatial Information Analysis

Further information is available at https://sites.google.com/g.ecc.u-tokyo.ac.jp/ikuho-yamada/

My research specialty is urban spatial analysis, which aims at understating various phenomena occurring in urban spaces in terms of their spatial distributions and latent systems ruling them. My research covers both theoretical and application aspects of urban spatial analysis. Theoretical themes that I work on include development and improvement of spatial statistical methodology to explicitly incorporate real-world considerations of urban spaces and spatial data and development of spatio-temporal analytical methodology focusing on temporal changes in spatial distributions. As an application field, my primary interest lies in urban environments that support health and healthy lifestyles of residents.

Development and improvement of spatial statistical methodology to explicitly incorporate real-world considerations of urban spaces and spatial data

While spatial statistical methodology usually assumes infinite and uniform spaces, actual urban spaces tend to be finite and not uniform as a variety of physical and social constraints are imposed on them. In addition, spatial data to be analyzed also contain some errors, constraints, and/or ambiguities that are not explicitly considered in spatial statistical methodology. For example, movement of people and location of urban facilities are strongly influenced by street networks, so that they would be better understood in the context of a network space rather than a Euclidean space. I thus developed a series of cluster detection methods on the network space, named Local Indicators of Network-constrained ClusterS (LINCS), and some of the methods are implemented in SANET software provided by CSIS. Another research topic I currently deal with is if and how ambiguity of sample data influences on spatial statistical analysis.

Spatio-temporal analysis, spatial surveillance

As availability of spatio-temporal data has gradually increased these days, importance of spatio-temporal analysis focusing on detection and assessment of changes in spatial patterns has also increased. In particular, I am interested in spatial surveillance, which aims at quick detection of changes in spatial patterns by continuously analyzing spatial data collected over time. This type of analysis is called “prospective analysis” in comparison with “retrospective analysis,” which examines spatial data collected in a time point (or points) in the past. Spatial surveillance has been receiving much attention in relation to disease and syndromic surveillance to monitor spatial diffusion of infectious and other diseases.

Urban environments that support healthy lifestyles of residents

By applying spatial analytical methodologies explained above, I conduct various studies that attempt to capture relationships between neighborhood environments and health of residents quantitatively and then identify characteristics of environments supporting their health and healthy lifestyles. Research topics that I currently work on include, but are not limited to, relationships between neighborhood walkability and physical activities of residents as well as those between accessibility to health care services and medical behaviors of patients.

Note: Feel free to contact me if you are interested in collaborative research.