Geog 461 Test 2

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Geog 461 Test 2
2012-03-06 02:33:10

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  1. Early studies & methodologies (EJ)
    •1979: Bean v. Southwestern Waste Management

    •1983: “Siting of Hazardous Waste Landfills and Their Correlation with Racial and Economic Status of Surrounding Communities” (Gov‟t Accountability Office, in response to Congress)

    •1987: UCC Commission on Racial Justice Toxic Waste and Race
  2. Executive Order #12989, 1994
    "Each Federal agency will make achieving environmental justice part of its mission by identifying and addressing…disproportionately high and adverse human health or environmental effects of its programs, policies, and activities on minority population and low-income population…"
  3. EJ as a social/spatial question
    • •What is the spatial distribution of environmental hazards?
    • Now includes additional disamenities (disease, crime, payday lenders)
    • And amenities (parks, hospitals, etc)

    • •Are burdens born unevenly by social groups?
    • Originally race/income
    • Now other social categories, vulnerabilities (age, language, etc).
  4. GIS & spatial methods: EJ research, activism, public policy
    •Explore the significance of different factors

    •Analyze degree of spatial clustering of toxic sites, hazards

    •Produce analysis/mapping for advocacy and activism
  5. Commonly used methods (EJ)
    •Descriptive statistics

    •Multivariate statistics

    •GIS-based spatial analysis (often in combo w/ above)
  6. Challenges for GIS-based analysis of Env’tl Justice:
    •Race, poverty, land market dynamics?

    • •What about MAUP / spatial scale of analysis
    • Modifiable Areal Unit Problem
    • Changing the scale/resolution changes the analysis!

    •Who is a „minority‟ / „at risk‟ population

    •Limitations of demographic data sources (typically Census in U.S.)

    •Overlay challenges (i.e. road buffers & Tracts)

    What if the areas we want to analyze are not the same size/shape as the areas into which the demographic data is aggregated?
  7. Some options (EJ challenges)
    • “Within analysis”
    • Only those tracts completely within

    • “Adjacency analysis”
    • Tracts that are completely within AND intersect

    • “Centroid containment”
    • Only those tracts whose centroids are contained by the overlay polygon

    • Areal weighting
    • Clip or buffer the tracts, then estimate the population that will be contained in these areas
    • E.g. if 75% is covered by buffer polygon, allocate 75% of population in that Census Tract

    • Critiques of all these methods:
    • Ineffective in highly populated areas
    • Tend to underestimates minority, low income pops
  8. Cadastral-based expert dasymetric system (CEDS, Maantay & Marakov)
    Disaggregate using cadastral data – use residential units as proxy for population

    Select parcels that intersect the buffer polygons (in this case, flood zones)

    Improved results with respect to undercount and distribution of population in dense/heterogeneous urban area.

    But – what are dasymetric maps?
  9. Dasymetric Mapping
    • Like choropleth mapping except
    • Boundaries of enumeration units do not necessarily match the symbol

    Helps avoid the ecological fallacy
  10. But how do you draw the regions, if they are not pre-determined?
    “Ancillary Information”

    Uses this additional data to help you determine where your thematic phenomena may or may not be located.

    Ancillary data used as a sort of mask to help you determine appropriate regions for your data.
  11. Community-based approaches to using GIS in environmental justice activism
    Expand the notion of what counts as an environmental hazard

    Challenge the completeness, accuracy, appropriateness of „official‟ data

    Use traditional GIS techniques

    • Incorporate local community-produced knowledge
    • “Toxic tours”
    • Community risk & asset mapping
    • Neighborhood-based environmental monitoring
  12. Persistent questions and struggles (EJ)
    Histories of residential and labor market segregation?

    Urban investment, disinvestment histories?

    Risk, exposure, harm

    Which injustices are legally „actionable‟ and where?

    “official” data on contamination / exposure vs. unreported/undoc‟d data
  13. Data surfaces – what & why?
    Creates a surface from a collection of points

    Continuous data (we have sampled points, but we need to estimate the values everywhere)

    Elevation, temperature

    Pollution, traffic accidents
  14. Example: Nas & Berktay