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geospatial analysis

This definition is part of our Essential Guide: Advanced data visualization guide: How visualizing data can boost BI
Contributor(s): Matthew Haughn

Geospatial analysis is the gathering, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly, in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

Geospatial analysis originated in Canada for cataloging natural resources in the 1960s, using the first geographic information systems (GIS). Geographic information systems are used to predict, manage and learn about all kinds of phenomena affecting the earth, its systems and inhabitants.

The many applications of geospatial analysis include crisis management, climate change modeling, weather monitoring, sales analysis, human population forecasting and animal population management.

Geospatial analyst filter out relevant from irrelevant data and apply it to conceptualize and visualize the order hidden within the apparent disorder of geographically sorted data.  Doing so allows them to provide accurate trend analysis, modeling and predictions. However, analysts must remain vigilant to try to avoid spatial fallacies, biases or misunderstanding effects and causal relationships: Geospatial analysis is sometimes considered to encompass as much intuition as it does science.

This was last updated in January 2014

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