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Erica Quintana

Erica Quintana. GIS Final 2012. Policy Question. What areas in LA County should United Way target for engagement and resource development and why? Steps to address this: What factors lead to homelessness and/or have high estimates of homeless populations?

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Erica Quintana

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  1. Erica Quintana GIS Final 2012

  2. Policy Question • What areas in LA County should United Way target for engagement and resource development and why? • Steps to address this: • What factors lead to homelessness and/or have high estimates of homeless populations? • Create an index to identify areas with high risk • Identify current resources in the area • Identify radius to surrounding resources to determine need

  3. Extent of Study

  4. Creation of an Index • Variables used to create an index: • Homelessness Estimates from Census data • Predictors of homelessness: • Percent of population in poverty • Percent of population unemployed • Percent of population that is rent burdened

  5. Extent of Study: Los Angeles County

  6. Areas Scoring High on Index

  7. Area #1: Palmdale/Lancaster • Basic Data: • Index: Lancaster and Palmdale both have areas that score high on the Index

  8. Lancaster/palmdale Mismatch

  9. Area #2: Irwindale

  10. Irwindale mismatch Irwindale didn’t have any PSH locations but they had an estimated 50 homeless individuals in the Census Tract

  11. Area #3: Pomona

  12. Mismatch in pomona

  13. Area #4: Compton

  14. Mismatch in compton

  15. Required Skills Used • Modeling: I used modeling to create rasters and then reclassify the rasters to create an index • Measurement/Analysis: I created buffers around the PSH locations to include an 3 mile radius from the point then used this distance to pro-rate the mismatch of units to estimated homeless counts • Original Data: I received an excel spreadsheet containing information for the PSH Locations including addresses and total unit numbers

  16. Additional Skills • Spatial Statistics: I created a statistic for the mismatch of PSH units to homeless populations in the 3 mile buffer surrounding the PSH locations • Inset Maps: I created inset maps for most of my maps to give audience an idea of placement within the county • Point/Graduated Symbol: I created a graduated symbol for the PSH locations to show the difference in total number of units within each location • Aggregating Attribute Fields: I aggregated the attribute fields in the Rent Burden data from the census to get total number of people with rent burden of ≥ 30% income (aggregated from all income brackets) • Creating Indices: I created an index from my raster data sets to show areas of greatest need/highest risk in LA County variables included homeless population estimates, percent of people in a census tract living below the poverty line, percent of people in census tract with ≥ 30% rent burden, and unemployment rate in census tract • Geocoding: I geocoded the addresses from the original Excel data on PSH locations from United Way • Attribute Sub-selection: In order to show the cities/communities of focus I selected by city name to make the map readable and show clearly the area of focus

  17. Sources • United Way: PSH data • American Community Survey: Employment: Table DP03, Poverty: B17001, Rent Burden: B25106, Homeless Population Estimates: PCT20 variable “other non-institutional facilities” coded as soup kitchen lines or emergency shelters like motel room vouchers • GIS: Basemaps, Address locators, etc.

  18. Models

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