This division develops methods for extracting spatial characteristics such as the shape and distribution of various spatial phenomena including landforms, hydrology, vegetation, society, culture, language, and economy. The division also develops and applies spatial analysis theory to uncover the underlying mechanisms. In addition, the division developed a system to support spatial decision-making that contributes to the planning processes of real society, for example, to predict future phenomena or analyze policies.

This division conducts research on various techniques and integrates and mines methods to efficiently obtain an enormous volume of data connected to location and time generated by various sensors dispersed throughout a real space. Furthermore, data reflecting the conditions of real spaces dispersed on the Internet are collected. This division also studies extensive applications based on spatio-temporal data such as data visualization, location information services, and future prediction.

The aim of this division is to promote theoretical and empirical studies on diverse social and economic phenomena, focusing on their spatio-temporal characteristics. Furthermore, the division develops methods to statistically analyze the spatio-temporal data needed in empirical analyses. It also constructs spatio-temporal databases that are made available to researchers across Japan to enhance empirical research in the social sciences, in particular, in urban and regional economics.

This division reconstructs scattered spatial data and spatial knowledge to compile a spatial information base. It conducts research and development activities focused on environments that support research and educational activities related to these data and that use them in sophisticated applications. In addition to designing, implementing, and validating initiatives directed at the development of research communities, this division studies the environments, methods, and systems needed to promote social applications of the spatial information base.

The Joint Organization of Digital Spatial Society Research centrally aggregates diverse and dynamic real-time spatio-temporal big data such as data from IoT devices. data-driven technology and science, while organically linking researchers in related fields within the university while constructing a digital social space that encompasses the expansion and changes in the environment, as well as the transformation and fluctuation of socio-economic systems. We will deepen it further and build new theories of real-time spatio-temporal data analysis and application. At the same time, we aim to develop research results into data-driven industries and help solve international social issues.