Introduction - Space-Time Integration in Geography and GIScience - page 4

Wang and Stewart develop a method for automatically representing the spa-
tiotemporal information and tracking moving entities over space-time to show the
spatial extent and trends of the dynamics of hazard-related events. The method
automatically processes event semantics to add meaning to the information mapped
from documents. The chapter also discusses methods for combining natural lan-
guage processing techniques and ontologies to improve the extraction of semantics
of hazard-related events sourced from web text. Using their recent projects as
examples, the chapter by Yang et al. discusses how cutting-edge computing
technologies can be utilized to handle and process spatiotemporal big data. The
technologies discussed in the chapter include: (1) grid and cloud computing;
(2) sensor web, Earth observations, and simulation models; (3) standard-based
systems; and (4) multidimensional visual analytics.
Yuan and Nara provide an overview of space-time trajectory analysis and
discusses the challenges of scaling it up to spatiotemporal big data. The chapter
provides a conceptual framework and methodology for performing space-time
analysis with a massive number of space-time tracks and illustrates its usefulness
for extracting complex activity patterns with several examples.
The chapter by Zhou, Shekhar, and Mohan seeks to provide an interdisciplinary
perspective on methods for mining spatiotemporal change patterns and promotes
cross-fertilization of ideas among researchers of diverse backgrounds. The chapter
analyzes these taxonomies and patterns from a space-time perspective to compare
related concepts from different disciplines.
In the concluding chapter, Richardson addresses the origins and emergence
of real-time space-time integration in GIScence and geography, and develops a
working research agenda for moving this dynamic field forward. He also explores
the concept of transformational research in geography and GIScience, and raises
key questions about how innovation and discovery in GIScience might be better
fostered by examining the actual practices of GIScience research and innovation,
and the social structures and contexts which constrain or enable our science.

1.2 Synopsis of Chapters Led by China-Based Authors

The contributions by China-based scholars cover various spatiotemporal issues at
scales spanning global to micro levels. They include methodological developments
and a review of the state-of-the-art research and applications in different fields.
Many of these chapters also provide case studies in China. They reflect not only the
progress in space-time research in China, but also examine prominent environment,
social, and urban issues in China.
Lee and Zhang explore the association between climate change and human
crises in pre-industrial societies. Addressing a spatiotemporal issue at the global
and geological time scale, this study seeks to establish potential linkages between
climate changes and population checks, population collapses, and socio-political
chaos in China, Europe, and other countries/regions in the Northern Hemisphere