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TerraPop Vision. An organizational and technical framework to preserve , integrate , disseminate , and analyze global-scale spatiotemporal data describing population and the environment. Develop tools to make data interoperable across data formats and subject areas

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terrapop vision
TerraPop Vision

An organizational and technical framework to preserve, integrate, disseminate, and analyze global-scale spatiotemporal data describing population and the environment.

  • Develop tools to make data interoperable across data formats and subject areas
  • Break down disciplinary silos
terrapop goals
TerraPop Goals

Lowerbarriers to conducting interdisciplinary human-environment interactions research by making data with different formats from different scientific domains easily interoperable

source data
Source Data

Domains & Formats

Population Microdata

Area-Level Data

making disparate data formats interoperable
Making disparate data formats interoperable

Microdata:

Characteristics of individuals and households

Area-level data:Characteristics of places defined by boundaries

Raster data:

Values tied to spatial coordinates

slide6

Age

Birthplace

Mother’s birthplace

Sex

Relationship

Race

Occupation

Microdata

Structure

Geographic and housing

characteristics

Household record

(shaded) followed

by a person record

for each member

of the household

For each type of

record, columns

correspond to

specific variables

the power of microdata
The Power of Microdata
  • Customized measures: Variables based on combined characteristics of family and household members, capitalizing on the hierarchical structure of the data
  • Multivariate analysis: Analyze many individual, household, and community characteristics simultaneously
  • Interoperability: Harmonize data across time and space

Age classification for school enrollment

in published U.S. Census

slide12

Growth of Public-Use Microdata

(number of person-records available)

We are Here

ipums international microdata
IPUMS-International Microdata

Over 100 Collaborating National Statistical Agencies

area level vector data
Area Level (Vector) Data

Describing characteristics of geographic polygons

Median Household Income by Census Tract

area level data sources
Area-level Data Sources
  • Census tables, especially where microdata is unavailable
  • Other types of surveys, data
    • Agricultural surveys
    • Economic surveys, data
    • Election data
    • Disease data
  • Legal/policy information
    • Environmental policy
    • Social policy
    • Human rights
raster data
Raster Data

Represented as pixels in a grid

Mean Precipitation

raster data1
Raster Data
  • Beta system
    • Global Land Cover 2000
    • Harvested Area and Yield for 175 crops (Global Landscapes Initiative)
    • Temperature and precipitation (WorldClim)
  • Future additions
    • Additional LU/LC and climate datasets
    • Elevation
    • Vegetation characteristics
    • Bioclimatic & ecologic zones
location based integration
Location-Based Integration

Microdata  Area-level  Raster

location based integration1
Location-Based Integration

Microdata

Mix and match variables originating in any of the data structures

Obtain output in the data structure most useful to you

Area-level data

Rasters

location based integration2
Location-Based Integration

Microdata

Individuals and households

with their environmental

and social context

Area-level data

Rasters

location based integration3
Location-Based Integration

Microdata

Summarized environmental and population

characteristics for administrative districts

Area-level data

Rasters

location based integration4
Location-Based Integration

Microdata

Rasters of population and environment data

Area-level data

Rasters

rasterization
Rasterization
  • Beta system – Uniform distribution assumption
    • Use lowest level units available
    • Rates – same value for all cells in unit
    • Counts – evenly distributed across cells in unit
  • Future – Distribute based on ancillary data
  • Requires research on available methods
  • May provide as service – users select:
    • Ancillary data
    • Weights
    • Spatial distribution parameters
general workflow
General Workflow
  • Browse variables and metadata
  • Select variables and datasets
  • View data cart contents
  • Select output options