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Models for creating population databases and their consequences

Models for creating population databases and their consequences. Gene Fosnight UNEP GRID Sioux Falls. Population Models. Sampling models: control data collection and compilation Simple redistribution models: Minimum bias models Complex redistribution models: Maximum information models.

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Models for creating population databases and their consequences

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  1. Models for creating population databases and their consequences Gene Fosnight UNEP GRID Sioux Falls

  2. Population Models • Sampling models: control data collection and compilation • Simple redistribution models: Minimum bias models • Complex redistribution models: Maximum information models

  3. Applications that need human population information • Analysis at the level of the sampling unit • Application models seeking relationships between spatially distributed variables • Application models seeking patterns within the population information or between the population model and exogenous variables • Population migrations

  4. NCGIA Composite CIESIN Landscan

  5. NCGIA Composite CIESIN Landscan

  6. NCGIA Composite CIESIN Landscan

  7. Issues - Opinions • Quality of source data is of supreme importance • City lights data can be an important contribution • We’re a long way from handling population migrations • We’re a long way from handling complex data involving rural/urban, economic, cultural or age distributions • A need for longitudinal (time series) data exists • Over-modeling: real versus perceived resolution

  8. Concern • Have the two most recent global population databases improved the state-of-the-art of population modeling?

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