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Class 7

Spatial Data

Geog 215

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AGENDA

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Today’s Class …

  • Data Accuracy
  • Foundation Data
  • Types of Data
  • Accessing Spatial Data

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During Class …

  • Usable Spatial Data Exercise

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Next Class …

  • Mapping

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Data Accuracy

Authoritative Data:

  • Authoritative data is held to the highest standards of data production and management
  • Authoritative data is usually regulated
  • Accuracy/documentation standards and protocols
  • Metadata provided

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Other Data:

  • Often lacks metadata
  • Accuracy is not documented
  • Be cautious, but can still be helpful

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Foundation Data

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  • Foundation data is the “background” spatial data used as reference
  • Can sometimes be referred to as “base map” data
  • Often is not analyzed by itself, but can be

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Vector Foundation Data

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    • States, cities, countries

Administrative boundaries/locations

    • Tracts, block groups, blocks

Enumeration Units

    • Lakes, rivers

Natural (physical) features

    • Roads, trails, railways

Transportation (or other) infrastructure

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Raster Foundation Data

  • Imagery
    • Aerial photos, satellite imagery
  • Elevation/terrain
    • Digital Elevation Model
  • Land cover/use

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Geographic Entities

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Enumeration Units

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Demographic Data

  • Population attributes
    • Counts
    • Age, gender, race/ethnicity, etc.
  • Census/survey data
    • Data resolution and availability will vary
  • Generally, higher spatial resolution = less detailed data

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Socioeconomic Data

  • Population attributes
    • Education, Income, Employment, etc.
  • Often, used as a proxy for health or health-related behaviors
  • Often, used to assign neighborhood attributes
  • Census/survey data
    • Data resolution and availability will vary
  • Generally, higher spatial resolution = less detailed data

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Environmental/Neighborhood Data

  • Neighborhood attributes
    • Environmental hazards
  • Air pollution, water pollution, etc.
    • Environmental conditions
  • Temperature, precipitation, humidity
    • Disease transmission
  • Vector distribution (and/or habitat)
    • Amenities
  • Neighborhood features
    • Parks, produce stores, etc.

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Health Related Data

  • Vital statistics
    • Births and deaths
  • Morbidity Data
    • Data about the “health” or “health conditions” in the population
  • Health care providers
    • Locations of hospitals, physicians, emergency
    • services, clinics, etc.
  • Often, is non-spatial data

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Components of Spatial Data

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Metadata

Describes data and assumptions

Time

Often a snapshot but may include a variable

Attribute

Some measurable or observable property

Location

Often defined in 2-D space, but can be 3-D

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Developing Spatial Data

Creating and/or developing spatial data requires a large amount of time, effort, and money

  • Good news: a large amount of foundation data has already been created and is freely available on the internet
  • Bad news: the availability and quality of this data varies significantly from place to place

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Considerations

  • Topic / Data
    • Data exist?... and available?...
  • If so, are they appropriate?
    • e.g., correct format, resolution, time period
  • Data integration
    • Rarely do we work with a single data sources
    • Do data align?
  • Temporal, spatial

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Acquiring Spatial Data

  • Data access and sharing
    • In the past, data was highly guarded
  • Generally, movement has been towards sharing via open availability and unrestrictive use agreements
  • It can still be very frustrating to acquire spatial data!

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Points to Consider

  1. What format is the data in?
  2. Does the data meet your needs?
  3. Can you access the data?

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Acceptable Data Formats

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Modes of Access

  • Actual steps to acquire the data (web-based)
  • Examples
    • Web GIS (must manually point/click)
    • Web links (must manually point/click or directly read)
    • FTP site (can manually point/click or directly read)
    • API (request / response approach)

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How to Access Data on the Web

Two main ways to access data from the web:

  • Direct Downloads
  • API (Applied Programming Interfaces)

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Disadvantages to Direct Downloads

  • Direct downloads can be time consuming when you want to download a lot of data. They can also sometimes be challenging for replicability
  • When you automate data access, download or retrieval and embed it in your code, you are directly linking your analysis to your data. 

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Analysis

  • Data found on the internet is RARELY analysis-ready. That is why so much of this course is focused on data cleaning
  • Do not underestimate the amount of time it may take to get data ready for analysis

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Usable Spatial Data

  • Is the data easily downloadable?
  • Is the data spatial, or can it be made spatial?
  • Is the data from a reputable source and does it have metadata?
  • Does the data meet your analytical requirements?

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