1. Geocoding and Census Mapping: Conceptual Framework and Different Approaches Lisa Jordan Florida State University Department of Geography, Center for Demography and Population Health

2. Geographic census data are valuable Planning of social and educational services, poverty analysis, utility service planning, labor force analysis, marketing analysis, voting district delineation, emergency planning, epidemiology analysis, flood plain analysis, and agriculture (including famine early warning systems)

3. Types of InterpolationSource(s) for Interpolation Simple Interpolation: Gridded Population of the World (GPW) Data Set Population Census Estimates Smart Interpolation: Land-use: Roads: City Lights: IKONOS, LANDSAT TIGER DMPS-OLS Advanced Interpolation: LandScan: Surface Modelling of Population Distribution (SMPD): Gridded Rural-Urban Mapping Project (GRUMP): Land-use, roads, slope, elevation Land-use, Net Primary Productivity (NPP), elevation, city distribution, transportation infrastructure Human settlement data, night-time lights, defense population databases GPWLand-use: IKONOSLand-use: Landsat Roads Reibel and Bufalino, 2005 LandScan: Nighttime Lights:GRUMP:Surface Modeling: citiesrailways roadsland-use NPPelevation

4. Growing Open Source and Public Application of Census Information Public, web-based geocoding and GIS, batchgeocode.com

5. gCensus, by Imran Haque, gCensus – GT, allows import of raster files, GeoTiffs, for example Growing Open Source and Public Application of Census Information San Francisco, population, census block groupsSan Francisco, population, interpolated

6. Growing Open Source and Public Application of Census Information QGIS MapWindow uDig Saga

7. Geocoding Concepts Address Matching Assignment to Enumeration Areas

8. Geocoding Concepts Census HierarchyAddress Hierarchy

9. Geocoding Concepts pre-enumerationenumerationpost-enumeration Applications and Limitations

10. Suggested Updates to the Handbook Updates on software/hardware discussion - mentioning the potential advantages of investing in open source GIS Include suggestions for assessing data quality, such as the geocoding certainty indicator (GCI) (Davis and Fonseca 2007) More and updated case studies (as presented here this week) Perhaps mention the valuable role of the United Nations in facilitating an international spatial data infrastructure that brings disparate national information together