Case12A Deriving Urban Population Density Functions by Monte Carlo Simulation

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Chapter 12 Monte Carlo Method and Applications in Urban Population and Traffic Simulations

Case Study 12A: Deriving Urban Population Density Functions in Uniform Area Unit in Chicago by Monte Carlo Simulation

This case study is based on the work reported in Wang, Liu & Xu (2019). The study area is the seven-county Chicago CMSA. Main data sources include the 2010 Census data and the 2010 Land Use Inventory data. We limit the simulation of population to the residential land use category so that simulated residents can better resemble the actual settlement pattern.
As stated in section 6.3 of Chapter 6 in the main book, it is desirable to have analysis areas of identical or similar area size in fitting urban density functions. Wang, Liu & Xu (2019) designed six area units with three distinctive shapes (square, triangle, and hexagon) and two scales to capture both zonal and scale effects. This case study uses only one shape (hexagon) in one size (1 km2) for illustration. A small number of areas on the edge of the study area are truncated and thus smaller.

The sub-folder ZoneEffect under the data folder Chicago includes:
1) feature residential.zip represents residential land use,
2) feature block.zip represents census blocks with field POP100 for population in 2010,
3) features tract.zip and blockgroup.zip represent census tracts and block groups, respectively, and
4) feature citycenter.zip is the city center.

URL: GitHub for Geospatial Analytics https://github.com/spatial-data-lab/knime-geospatial-extension
URL: GitHub for Workbook Issue Report https://github.com/UrbanGISer/CGA-KNIME-Workbook/tree/main

Case12A Deriving Urban Population Density Functions by Monte Carlo Simulation

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