Task Three: Linking settlement structure with changing land use intensity

and population distribution

Major Objective of Task Three

Demonstrate and Test the second level of the
Integrated Modeling Environment (IME-2)

Brief History/Trajectory of Modeling Efforts

1) UGM modeling Urban vs. Non-Urban utilizing
     Historical Maps of Urban, Road Networks,
     Elevation, and excluded Lands

2) Present Modeling attempts to Model Land Use
     at the Anderson Level I classification with data
     used in (1) and 2 or more historical land use maps

3) Future Modeling hopes to Model Land Use at the
     Anderson Level II classification level

Example of Anderson Level II for URBAN

1 Urban or Built-Up Land

     11 Residential
     12 Commercial Services
     13 Industrial
     14 Transportation, Communications
     15 Industrial and Commercial
     16 Mixed Urban or Built-Up Land
     17 Other Urban or Built-Up Land

Year One
 

  • Build a better-integrated picture of Land-use, Land-cover,  changing intensity of use, and population distribution for urban areas
  • How to build a better picture? Validate with existing census data, existing Anderson Level II land-use maps, and Nighttime Satellite imagery
  • Goal: Use this information with models capable of coupling such properties with urban structure and change

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    Year Two
     

  • Assemble data at a range of spatial and temporal scales for these four selected urban areas.
  • Use data to evaluate the accuracy and scalability of the estimates derived from the nighttime satellite imagery
  • Provide insight as to how these estimates can be used to inform and/or validate the more comprehensive models being investigated.


    • Year Three

    We will then use our models to anticipate the results of the 2000 census for
    these urban areas. The availability of the actual census data in the third year of
    the study will allow validation of the coupled models' predictions. An important
    outcome here will be the ability to evaluate not only the actual model outputs,
    but also to assess levels of uncertainty and error, so that confidence limits may be
    placed on the models' performance.
     
     

    Support for this project is from the National Science Foundation :

    Contact the project Web Master.