$30 off During Our Annual Pro Sale. View Details »

Creating and disseminating GIS data for the US ...

Creating and disseminating GIS data for the US and the World

David Van Riper
Jonathan Schroeder
Tracy Kugler

#NACIS2015

Nathaniel V. KELSO

October 14, 2015
Tweet

More Decks by Nathaniel V. KELSO

Other Decks in Education

Transcript

  1. Creating and disseminating GIS data for the US and the

    World David Van Riper Jonathan Schroeder Tracy Kugler NACIS 2015
  2. GIS technology stack •  Esri §  Editing and data processing

    in ArcGIS §  Best tools for large-scale data production •  NHGIS §  Currently disseminates only shapefiles §  Moving to PostGIS back-end to facilitate additional data formats •  TerraPop §  Currently disseminates only shapefiles §  Uses PostGIS back-end so easy to extend to additional data formats
  3. NHGIS •  Started in 2001 with a major grant from

    the National Science Foundation •  Received two additional NSF grants and two NICHD (NIH) grants •  First MPC project to create and disseminate GIS data •  NHGIS also disseminates aggregate census data to link with GIS data
  4. Initial GIS data •  Census tracts §  1910-2000 §  Constructed

    from TIGER/Line 2000 data and scanned census tract maps •  Counties §  1790-2000 §  Constructed from TIGER/Line 2000 data, scanned census maps, Thorndale & Dollarhide’s Map Guide to the US Federal Censuses 1790-1920, and other sources
  5. Current work •  Historic place and county subdivision points § 

    County subdivisions back to 1930 §  Places back to 1790 §  Using TIGER, GNIS, and scanned census maps §  Create new summary data from 100% census microdata
  6. Current work •  Historic place and county subdivision points § 

    County subdivisions back to 1930 §  Places back to 1790 •  Conflation §  Aligning historic census tract and county boundaries with 2010 TIGER data
  7. IPUMS-USA Integrated – consistent codes, labels and docs Public –

    anonymized, downloadable Microdata – individual-level Series – pooled data over time and place
  8. Microdata •  Shows full range of individual responses •  Enables

    custom tables and sophisticated analyses •  BUT, suppression is an major issue
  9. Public Use Microdata Areas (PUMAs) •  Smallest geographic unit identified

    in microdata •  Minimum population = 100,000 •  Delineated by states (not Census Bureau) after each decennial census
  10. Limitations •  Delineation rules change = inconsistent boundaries over time

    •  We created consistent PUMAs covering the 1980-2000 time period (through visual inspection) and the 2000-2010 time period (through an automated algorithm)
  11. Location-Based Integration Summarized   environmental   and  popula1on   Microdata

    Area-level data Rasters characteris1cs  for   administra1ve   districts   County ID G01001 G01003 G01005 G01007 County ID Mean Ann. Precip. Median HH Income G01001 768 50,500 G01003 589 48,500 G01005 867 51,000 G01007 701 50,750
  12. Boundaries are Key •  Linkages across data formats rely on

    administrative unit boundaries §  Containers for summarizing raster data to area- level data §  Containers for distributing area-level data to raster cells §  Codes link area-level and summarized raster data to microdata •  Sets of units and codes must match census data
  13. Terra Populus – GIS data •  Create an ‘authoritative’ (as

    possible) set of first and second administrative level boundaries •  From most recent census back to ~1960s •  Disseminate freely
  14. GIS data – non-IPUMS countries Afghanistan   Bosnia  and  

    Herzegovina   Denmark   Georgia   Laos   Mauri1us   North  Korea   Saudi  Arabia   Tajikistan   Albania   Botswana   Djibou/   Guatemala   Latvia   Moldova   Norway   Serbia   Timor  Leste   Algeria   Bulgaria   Dominican   Republic   Guinea  Bissau   Lebanon   Montenegro   Oman   Singapore   Togo   Angola   Burundi   Equatorial   Guinea   Guyana   Lesotho   Mozambique   Papua  New   Guinea   Slovakia   Trinidad  and   Tobago   Azerbaijan   Central  African   Republic   Eritrea   Honduras   Liberia   Myanmar   Paraguay   South  Korea   Tunisia   Bahrain   Chad   Estonia   Hong  Kong   Libya   Namibia   Poland   Sri  Lanka   Turkmenistan   Bangladesh   Comoros   Ethiopia   Ivory  Coast   Lithuania   Nepal   Qatar   Swaziland   Ukraine   Belgium   Croa1a   Finland   Japan   Macedonia   New  Zealand   Republic  of   Congo   Sweden   United  Arab   Emirates   Benin   Cyprus   Gabon   Kazakhstan   Madagascar   Niger   Reunion   Syria   Yemen   Bhutan   Czech  Republic  Gambia   Kuwait   Mauritania   Nigeria   Russia   Taiwan   Zambia   Zimbabwe  
  15. NSF and NIH All staff and graduate students who have

    worked on these projects All of our users