Applications of Big Spatial Data: Health
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The term “big spatial data” encompasses all types of big data with the addition of geographic reference information, typically a location associated with a point in space (e.g., latitude, longitude, and altitude coordinates), an area (e.g., a country, a district, or a census enumeration zone), a line or curve (e.g., a river or a road), or a pixel (e.g., high-resolution satellite images or a biomedical imaging scan). When applied to questions of health, big spatial data can aid in attempts to understand geographic variations in the risks and rates of disease (e.g., is risk here greater than risk there?), to identify local factors driving geographic variations in risks and rates (e.g., does local nutritional status impact local childhood mortality?), and to evaluate the impact of local health policies (e.g., district-specific adjustments to insurance reimbursements).
In addition to defining big spatial data, it is also important to define what is meant by “health.” The World...
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