Space Time Integration In Geography And Giscience
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Space-Time Integration in Geography and GIScience
Space-time analysis is a rapidly growing research frontier in geography, GIS, and GIScience. Advances in integrated GPS/GIS technologies, the availability of large datasets (over time and space), and increased capacity to manage, integrate, model and visualize complex data in (near) real time, offer the GIS and geography communities extraordinary opportunities to begin to integrate sophisticated space-time analysis and models in the study of complex environmental and social systems, from climate change to infectious disease transmission. This volume specifically focuses on research frontiers, comparative research, and research and application interactions in this field in the US and China, arguably the two most dynamic loci for this work today. The contributions to this book, by top researchers in China and the US, productively highlight the differences and similarities in approaches and directions for space-time analysis in the two countries. In light of the recent rapid progress in GIScience research on space-time integration in both countries, the book’s focus on research frontiers in these two countries will attract great interest in both countries and in other parts of the world as well as among related disciplines. In addition, the book also explores the impact of collaborative research and publications underway in this area between the US and China and will provide an overview of these collaborative efforts and programs. This book will not only be of interest to university-based GIS researchers and students, but also to those interested in this new area of research and applications like researchers and developers in business, internet mapping and GIS and location based services (LBS).
Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics
This book discusses theoretical backgrounds, techniques and methodologies, and applications of the current state-of-the-art human dynamics research utilizing social media and geospatial big data. It describes various forms of social media and big data with location information, theory development, data collection and management techniques, and analytical methodologies to conduct human dynamics research including geographic information systems (GIS), spatiotemporal data analytics, text mining and semantic analysis, machine learning, trajectory data analysis, and geovisualization. The book also covers applied interdisciplinary research examples ranging from disaster management, public health, urban geography, and spatiotemporal information diffusion. By providing theoretical foundations, solid empirical research backgrounds, techniques, and methodologies as well as application examples from diverse interdisciplinary fields, this book will be a valuable resource to students, researchers and practitioners who utilize or plan to employ social media and big data in their work.
Uncertainty and Context in GIScience and Geography
Uncertainty and context pose fundamental challenges in GIScience and geographic research. Geospatial data are imbued with errors (e.g., measurement and sampling) and various types of uncertainty that often obfuscate any understanding of the effects of contextual or environmental influences on human behaviors and experiences. These errors or uncertainties include those attributable to geospatial data measurement, model specifications, delineations of geographic context in space and time, and the use of different spatiotemporal scales and zonal schemes when analyzing the effects of environmental influences on human behaviors or experiences. In addition, emerging sources of geospatial big data – including smartphone data, data collected by GPS, and various types of wearable sensors (e.g., accelerometers and air pollutant monitors), volunteered geographic information, and/ or location- based social media data (i.e., crowd- sourced geographic information) – inevitably contain errors, and their quality cannot be fully controlled during their collection or production. Uncertainty and Context in GIScience and Geography: Challenges in the Era of Geospatial Big Data illustrates how cutting- edge research explores recent advances in this area, and will serve as a useful point of departure for GIScientists to conceive new approaches and solutions for addressing these challenges in future research. The seven core chapters in this book highlight many challenges and opportunities in confronting various issues of uncertainty and context in GIScience and geography, tackling different topics and approaches. The chapters in this book were originally published as a special issue of the International Journal of Geographical Information Science.