Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods


Book Description

Environmental health researchers have long used concepts like the neighborhood effect to assessing people’s exposure to environmental influences and the associated health impact. However, these are static notions that ignore people’s daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.




Human Mobility, Spatiotemporal Context, and Environmental Health: Recent Advances in Approaches and Methods


Book Description

Environmental health researchers have long used concepts like the neighborhood effect to assessing people's exposure to environmental influences and the associated health impact. However, these are static notions that ignore people's daily mobility at various spatial and temporal scales (e.g., daily travel, migratory movements, and movements over the life course) and the influence of neighborhood contexts outside their residential neighborhoods. Recent studies have started to incorporate human mobility, non-residential neighborhoods, and the temporality of exposures through collecting and using data from GPS, accelerometers, mobile phones, various types of sensors, and social media. Innovative approaches and methods have been developed. This Special Issue aims to showcase studies that use new approaches, methods, and data to examine the role of human mobility and non-residential contexts on human health behaviors and outcomes. It includes 21 articles that cover a wide range of topics, including individual exposure to air pollution, exposure and access to green spaces, spatial access to healthcare services, environmental influences on physical activity, food environmental and diet behavior, exposure to noise and its impact on mental health, and broader methodological issues such as the uncertain geographic context problem (UGCoP) and the neighborhood effect averaging problem (NEAP). This collection will be a valuable reference for scholars and students interested in recent advances in the concepts and methods in environmental health and health geography.




Uncertainty and Context in GIScience and Geography


Book Description

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.




Comprehensive Geographic Information Systems


Book Description

Geographical Information Systems, Three Volume Set is a computer system used to capture, store, analyze and display information related to positions on the Earth’s surface. It has the ability to show multiple types of information on multiple geographical locations in a single map, enabling users to assess patterns and relationships between different information points, a crucial component for multiple aspects of modern life and industry. This 3-volumes reference provides an up-to date account of this growing discipline through in-depth reviews authored by leading experts in the field. VOLUME EDITORS Thomas J. Cova The University of Utah, Salt Lake City, UT, United States Ming-Hsiang Tsou San Diego State University, San Diego, CA, United States Georg Bareth University of Cologne, Cologne, Germany Chunqiao Song University of California, Los Angeles, CA, United States Yan Song University of North Carolina at Chapel Hill, Chapel Hill, NC, United States Kai Cao National University of Singapore, Singapore Elisabete A. Silva University of Cambridge, Cambridge, United Kingdom Covers a rapidly expanding discipline, providing readers with a detailed overview of all aspects of geographic information systems, principles and applications Emphasizes the practical, socioeconomic applications of GIS Provides readers with a reliable, one-stop comprehensive guide, saving them time in searching for the information they need from different sources




Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases


Book Description

Features modern research and methodology on the spread of infectious diseases and showcases a broad range of multi-disciplinary and state-of-the-art techniques on geo-simulation, geo-visualization, remote sensing, metapopulation modeling, cloud computing, and pattern analysis Given the ongoing risk of infectious diseases worldwide, it is crucial to develop appropriate analysis methods, models, and tools to assess and predict the spread of disease and evaluate the risk. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features mathematical and spatial modeling approaches that integrate applications from various fields such as geo-computation and simulation, spatial analytics, mathematics, statistics, epidemiology, and health policy. In addition, the book captures the latest advances in the use of geographic information system (GIS), global positioning system (GPS), and other location-based technologies in the spatial and temporal study of infectious diseases. Highlighting the current practices and methodology via various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features: Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes Examples of disease spreading dynamics, including West Nile virus, bird flu, Lyme disease, pandemic influenza (H1N1), and schistosomiasis Modern techniques such as Smartphone use in spatio-temporal usage data, cloud computing-enabled cluster detection, and communicable disease geo-simulation based on human mobility An overview of different mathematical, statistical, spatial modeling, and geo-simulation techniques Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases is an excellent resource for researchers and scientists who use, manage, or analyze infectious disease data, need to learn various traditional and advanced analytical methods and modeling techniques, and become aware of different issues and challenges related to infectious disease modeling and simulation. The book is also a useful textbook and/or supplement for upper-undergraduate and graduate-level courses in bioinformatics, biostatistics, public health and policy, and epidemiology.




Handbook of Spatial Analysis in the Social Sciences


Book Description

Providing an authoritative assessment of the current landscape of spatial analysis in the social sciences, this cutting-edge Handbook covers the full range of standard and emerging methods across the social science domain areas in which these methods are typically applied. Accessible and comprehensive, it expertly answers the key questions regarding the dynamic intersection of spatial analysis and the social sciences.




Health Literacy in Context- Settings, Media, and Populations


Book Description

This book is a printed edition of the Special Issue "Health Literacy in Context—Settings, Media, and Populations" that was published in IJERPH




Traffic-Related Air Pollution


Book Description

Traffic-Related Air Pollution synthesizes and maps TRAP and its impact on human health at the individual and population level. The book analyzes mitigating standards and regulations with a focus on cities. It provides the methods and tools for assessing and quantifying the associated road traffic emissions, air pollution, exposure and population-based health impacts, while also illuminating the mechanisms underlying health impacts through clinical and toxicological research. Real-world implications are set alongside policy options, emerging technologies and best practices. Finally, the book recommends ways to influence discourse and policy to better account for the health impacts of TRAP and its societal costs. - Overviews existing and emerging tools to assess TRAP's public health impacts - Examines TRAP's health effects at the population level - Explores the latest technologies and policies--alongside their potential effectiveness and adverse consequences--for mitigating TRAP - Guides on how methods and tools can leverage teaching, practice and policymaking to ameliorate TRAP and its effects




Artificial Intelligence in Performance-Driven Design


Book Description

ARTIFICIAL INTELLIGENCE IN PERFORMANCE-DRIVEN DESIGN A definitive, interdisciplinary reference to using artificial intelligence technology and data-driven methodologies for sustainable design Artificial Intelligence in Performance-Driven Design: Theories, Methods, and Tools explores the application of artificial intelligence (AI), specifically machine learning (ML), for performance modeling within the built environment. This work develops the theoretical foundations and methodological frameworks for utilizing AI/ML, with an emphasis on multi-scale modeling encompassing energy flows, environmental quality, and human systems. The book examines relevant practices, case studies, and computational tools that harness AI’s capabilities in modeling frameworks, enhancing the efficiency, accuracy, and integration of physics-based simulation, optimization, and automation processes. Furthermore, it highlights the integration of intelligent systems and digital twins throughout the lifecycle of the built environment, to enhance our understanding and management of these complex environments. This book also: Incorporates emerging technologies into practical ideas to improve performance analysis and sustainable design Presents data-driven methodologies and technologies that integrate into modeling and design platforms Shares valuable insights and tools for developing decarbonization pathways in urban buildings Includes contributions from expert researchers and educators across a range of related fields Artificial Intelligence in Performance-Driven Design is ideal for architects, engineers, planners, and researchers involved in sustainable design and the built environment. It’s also of interest to students of architecture, building science and technology, urban design and planning, environmental engineering, and computer science and engineering.




Frankenstein Urbanism


Book Description

This book tells the story of visionary urban experiments, shedding light on the theories that preceded their development and on the monsters that followed and might be the end of our cities. The narrative is threefold and delves first into the eco-city, second the smart city and third the autonomous city intended as a place where existing smart technologies are evolving into artificial intelligences that are taking the management of the city out of the hands of humans. The book empirically explores Masdar City in Abu Dhabi and Hong Kong to provide a critical analysis of eco and smart city experiments and their sustainability, and it draws on numerous real-life examples to illustrate the rise of urban artificial intelligences across different geographical spaces and scales. Theoretically, the book traverses philosophy, urban studies and planning theory to explain the passage from eco and smart cities to the autonomous city, and to reflect on the meaning and purpose of cities in a time when human and non-biological intelligences are irreversibly colliding in the built environment. Iconoclastic and prophetic, Frankenstein Urbanism is both an examination of the evolution of urban experimentation through the lens of Mary Shelley’s Frankenstein, and a warning about an urbanism whose product resembles Frankenstein’s monster: a fragmented entity which escapes human control and human understanding. Academics, students and practitioners will find in this book the knowledge that is necessary to comprehend and engage with the many urban experiments that are now alive, ready to leave the laboratory and enter our cities.