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