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

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Presentation on theme: "GIS 2, Final Project: Creating a Dasymetric Map for Two Counties in Minnesota By: Hamidreza Zoraghein Melissa Cushing Caitlin Lee Fall 2013."— Presentation transcript:

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

2 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

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

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

5 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

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

7 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

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

9 Urban Areas

10 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

11 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

12 Redistributing Population Density Variation Residential Area ElevationSlopeDistance to Rivers Distance to Flows Road Density Urban (21, 22, 23) **-0.2666-0.0898*-0.1923*0.1788***0.4469 Urban (21, 22, 23, 24) -0.12736-0.1888***-0.3712**0.2953***0.4788 Rural0.01238-0.2318-**0.5267*0.4386

13 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

14 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 211307.199190.105 221959.088600.158 232342.447430.189 242417.448150.195 411055.519140.085 42589.12310.047 81775.01440.062 901138.8110.092 95823.10910.066

15 Another Approach

16 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

17 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:10.1559/152304001782173727  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.

18 Thank you for your patience! Questions?


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