based methods—on land-use changes, climate changes, weather extremes, episodes of atmospheric and surface water pollution, and other observations has become critical to understanding how population and economic changes throughout the globe affect our common well-being. The panel considered issues of environmental factors pertinent to its charge, identified various kinds of human health and security risks, and then evaluated how remote sensing data from space might contribute to a better understanding of relationships between those factors and risks.

Over the past couple of decades, health and environmental scientists have used remote sensing data in diverse analyses of how environmental factors have altered the risk of various health effects in time and space, and how these insights might eventually be used to make observations and evaluate and manage risk. The basis for such research is the long-term availability of remote sensing data, combined with in situ observations (such as disease surveillance and reporting) that permit analyses necessary to uncover patterns and develop forecasts (NRC, 2007). Such research is impossible without continued capture and dissemination of remote sensing data, information that has served as the basis for understanding many larger-scale spatial environmental patterns. These data, combined with in situ epidemiological observations of disease morbidity and mortality, have served as the mainstay of research on environmental factors and disease and recommendations related to human health and security. Many studies successfully demonstrate the application of remote sensing data to identification of spatial or temporal variation in disease incidence or to assessment of the quantity or quality of air, food, and potable water, for example. The aim of such studies typically is to enhance forecasts of future outbreaks or to understand pathways by which environmental features are linked to increased health risks. Although the research being undertaken has been productive in identifying environmental links to human health risk, the confidence with which most diseases and other health effects can be forecast is still very weak. For this reason, the continued availability of space-based observations of land use and land cover, oceans, weather and climate, and atmospheric pollutants is critical to further enhancing the understanding of links to diseases and to expanding capacity for early warning of times and places where risk is elevated. Only through analyses of long-term time series will such patterns be understood and capabilities developed that will be useful to risk managers and health responders.

In general, knowledge of changing risk across regions and habitats, or over weeks to a few years, should improve forecasts, and hence detection capabilities and possible interventions and adaptation. For example, new higher-spatial-resolution satellite data may increase understanding of some infectious diseases whose risk to people is influenced by changes in microhabitat conditions. Also, such data can enhance understanding of relationships between human health effects and UV radiation dosage levels. Likewise better remote sensing capabilities should enhance the capacity to detect and track risk agents, including local drought conditions, harmful algal blooms, regional air pollution, and many acute releases of environmental contaminants. Anticipated health and security benefits currently drive most of the basic research agenda that employs space-based observations, yet public health practitioners and risk managers are only slowly expanding their use of these results. Future research is more likely to be useful if it is closely linked with the needs of the public health community, risk mangers, emergency responders, and specific components of human well-being.

Prioritization of Needs

The approach taken by this panel differed somewhat from that of most other panels, in that it intentionally began by identifying important health threats that are related to environmental factors and desired health outcomes (societal benefits). The panel then identified the kinds of Earth observation parameters and variables (environmental data) it considered important to informing relevant research and applications, and finally determined which platforms, sensors, and remote sensing data could provide the appropriate



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