GIS 2, Final Project: Creating a Dasymetric Map for Two Counties in Minnesota By: Hamidreza Zoraghein Melissa Cushing Caitlin Lee Fall 2013

General Outline  Study area  Delineating residential areas  Rural residential areas  Urban residential areas  Redistributing population density variation  Another approach: Area Modified Weighting  Limitations and outlooks

Study Area  Two counties in Minnesota  Criteria:  Diversity in population density  Having both urban and rural areas

Delineating Residential Areas  Different approaches for rural and urban areas  Rural Areas  NLCD  Block boundary density  Urban Areas  NLCD

Rural Areas Block Areas Block Boundaries Raster Boundaries Polygon to Line To Raster Focal Stats. Focal Output Raster Calc. Rural Mask Rural Landcover NLCD 21, 22 First Refinement Second Refinement Extraction Shrink Clear Boundary Dense Cells Mosaic

Rural Areas  Some patterns which don’t pass the threshold (33)  Some patterns which pass the threshold Pics fro Uhl (2011)

Urban Areas  Three different approaches were tested:  Extraction of classes 21, 22  Extraction of classes 21, 22, 23  Extraction of classes 21, 22, 23, 24  Further Refinement  Applying NHD layers

Urban Areas Urban Landcover Water Areas To Raster Extraction Initial Urban Mask Rasterized Water Times Final Urban Mask

Urban Areas

Redistributing Population Density Variation  Urban Areas  DEM  Slope  Road Density  Distance to Flow Lines  Distance to Rivers  Rural Areas  DEM  Slope  Road Density  Distance to Flow Lines

Creating Random Points Modified Pop Density Calculation Attributing Points by Mod Pop Density Extracting Rasters to Points Summarizing by Tracts Correlation Coefficients Calculation Reclassifying and Masking Applying The Weights Tool(s): Zonal Statistics as Table Tool(s): Raster to Polygon, Create Random Points Tool(s): Spatial Join Tool(s): Extract Values to Points Tool(s): Summary Statistics Tool(s): Excel Tool(s): Reclassify, Times Tool(s):Weighted Sum

Redistributing Population Density Variation Residential Area ElevationSlopeDistance to Rivers Distance to Flows Road Density Urban (21, 22, 23) ** * *0.1788*** Urban (21, 22, 23, 24) *** **0.2953*** Rural **0.5267*0.4386

Another Approach  Based on:  Polygon three class method (Eicher and Brewer 2001)  Sampling along with Area refinement on the above (Mennis 2003)  Applied on:  Urban part of the study area  Type of the method here:  Vector based

Vectorizing Land Cover Removing Unlikely Classes Consolidating Classes Sampling Pop Density for Classes Overlaying Tracts on Land Cover Calculating Elements per Tract Pop Density per Class per Tract Tool(s): Extraction Tool(s): Raster to Polygon Tool(s): Dissolve Tool(s): Select by Location Tool(s): Union Tool(s): Summary Stats, Join, Calculate Field Tool(s): Join, Calculate Field Land Cover ClassSampled Pop Density Number of Sampled Tracts Class Fraction

Another Approach

Limitations and Outlooks  Limitations  Lack of statistical analysis and validation  Not utilizing parcel data  Not very good for rural areas  Outlooks  Using smaller areas for establishing the correlations (e.g. block groups or blocks)  Simulation  Create random points based on the area of the tracts  Using parcel data  Exploring other potential related variables  Exploring other sampling strategies and making comparisons

Resources  Eicher, C. L., & Brewer, C. A. (2001). Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation. Cartography and Geographic Information Science, 28(2), 125–138. doi: /  Mennis, J. (2003). Generating Surface Models of Population Using Dasymetric Mapping ∗. The Professional Geographer, 55(1), 31–42.  Uhl, J. H. (2011). Master ’ s Thesis: “ Limiting and Related Variables for Dasymetric Analysis of U. S. Census Demography.” University of Colorado Boulder.

Thank you for your patience! Questions?