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Introduction

The gathering of data is a vital step in the map making process

The procedures followed will strongly influence the resulting map:

• what we are mapping is not the environment

• but data which represents the environment

Several important issues in the data gathering process

1. Phenomena and Data: Individual & Aggregate, Continuous & Discrete

2. Creating & Geting Data

3. Data Organization

4. Transforming Data

5. Time & Data

6. Data Accuracy

7. Digital Data

1. Phenomena and Data: individual & aggregate, continuous & discrete

• Phenomena are all the stuff out in the real world. Data capture specific phenomena.
  

  

  Making Maps p. 42-43

2. Creating & Geting Data

We have already engaged the oldest and most basic way of acquiring data:

• direct environmental perception with our senses: Exercise 1

Limited in its usefulness for making cartographic maps in most cases

• why?

We may use what we know via environmental perception to check other forms of data

• how?

Systematic data collection methods

• systematic: following a set arrangement, design, or pattern.
  • primary methods: direct collection of environmental data
    • look at four: ground survey, GPS, census, remote sensing (briefly)

  • secondary methods: using already collected environmental data
    • look at compiled data

2a. Ground Survey: Primary Systematic Data Collection

WWW) Land Surveying

Ground survey is based on the idea that we can specify the positions of environmental features in terms of other features with known positions.

Using surveying instruments, a surveyor works from a known position / elevation then calculates accurate new locations by measuring distances and angles away form that known, accurate position

Bench mark: a known location/elevation that meets a defined standard of accuracy

• on topo maps ... and on the ground

Handout) Delaware Topo

• extra credit! find a benchmark, do a rubbing on paper (with pencil, crayon)

• turn it in and get 10 pts (due one week from today)!

Calculating the positions of other features can be done by hand with geometry and trigonometry or with computers

• Positional information can then be augmented with additional attribute information

• Drawback with ground survey:

2b. Global Positioning Systems: Primary Systematic Data Collection

Global Positioning Systems (GPS): global network of satellites orbiting the earth and generating signals which can be used in tandem with GPS receiving units to pinpoint location and elevations

• GPS has revolutionized primary systematic data collection

• inexpensive units: accuracy within 10 meters or less
  • GPS everywhere: a 'consumer electronics' item

• drawbacks:
  • necessary for 3 - 4 satellites to be in 'view'

  • problems in urban areas, forests: no reading due to obstructions

  • inexpensive units: accuracy of 10 meters not acceptable for some uses

  • Does GPS make you stupid? Yes and Yes and Yes and Yes and Yes...

Origins and Development of GPS:

• LORAN (and DECCA): ship navigation system (late 1930s-50s)
  • ground stations transmit signals; LORAN receivers calculate position based on relation to signals from different stations

  • limitations: major water areas; 300 meter accuracy

• GPS: 1976 funding approved for US Military development of satellite based system for determining locations
  • immediate concern: logistics problems in Vietnam War

  • functioning in early 1980s

  • Gulf War (1990): test of the technology: organizing ground troops, integrating location of planes, vehicles, and use of GIS for military planning.

  
  

• Non-military uses: first commercial GPS receiver 1984
  • 1997: $2 billion dollar industry

    
    

• Selective availability: intentional garbling of GPS signals by military to non-military users: 100 meter accuracy for non-military uses
  • development of differential correction (DGPS): correction of inaccuracies

  • European Galileo system: competition

  • Selective availability removed in 2000

    
    

21 (+spares) GPS satellites in orbit around the earth



GPS tracking stations: measure GPS satellite signals, compute orbital locations, send this data to the satellites, which in turn send data to Earth-based GPS receivers.

Calculating locations on Earth with GPS

• GPS satellites continuously transmit signals indicating each satellites:
  • position in space

  • exact time signal was sent

• how long does it take signal to travel from satellite to ground receiver?

• with three satellite signals (position + time signal sent from each): calculate location (in coordinate system such as latitude/longitude)
  • problem: very slight inaccuracies in time (hundredth of second) can skew location by thousands of miles

  • solution: use reading from 4th satellite: provides very accurate locations and can also determine elevation of receiver

    
    

• ...but will the iPhone (and other smart, location aware phones) kill off much of the popular GPS industry?

• iPhone is "location aware": combination of GPS, cell tower triangulation, and wi-fi (whatever is available).

• iPhone GPS: but small built in antenna and poor GPS reception sometimes... so...

• Supplement with Wifi Positioning System ...and...
  • Cell Tower Maps

• Supplement with Cell phone tower triangulation
  

  
  

• Karen Steed-Terry. 2000. Integrating GIS and the Global Positioning System. Redlands CA: ESRI Press

• Peter Dana's other GPS Overview

• GPS FAQ

• GPS Links

• GPS FAQ

2c. Census & Sampling: Primary Systematic Data Collection

A census (or population count) is an inventory of individual environmental features (human or physical) in terms of some predefined region

• examples
  WWW) U.S. Census Bureau

The characteristic of a census is

1. we know the area in which the data was collected

2. we know how many of some feature are in the area

3. but we don't know where, in the area, the features are located

Census data is generalized.

Take this into account when using and mapping the data

WWW) Choropleth map of Census Population Counts
example) Delaware, OH 2000 Census

A sample is he systematic collection of a limited number of instances of environmental features in a given area, then a systematic estimate of the rest of the features in the area

Necessary for continuous environmental features such as temperature and elevation

• we sample temperatures at a series of recording stations, not everywhere

• we sample elevations, using surveying instruments, at a few key locations

Then we estimate (predict, educated guess at) the rest

• process of interpolation and extrapolation

  
  

  

Interpolation: predicting the value at a location between two known values

• example) Buffalo = 60 degrees, Syracuse = 70 degrees, halfway between = ?

  
  

• example) elevations

Extrapolation: predicting the value that falls beyond the location of known values

example) measure of toxic chemical in the ground

• 100' south of spill site = 10% above acceptable levels
  
• 200' south of spill site = 5% above acceptable levels
  
• 400' south of spill site = 2.5% above acceptable levels
  
• 800' south of spill site = unknown
  
• extrapolate that it is 1.75%

Accuracy issues

Sampling is also used for discrete environmental features

• sample # of birds in a 10000 acre reserve at 10 equally spaced locations

• assume the percentages of different species at the 10 locations represent the actual percentages in the entire reserve

• sampling allows us to take a small part of the population and infer what the larger population is like

  
  

  

  variations in the size of the sampling area

  random vs systematic sample locations

Decisions about how to sample are based on the nature of the distribution

Most important aspect of sampling:

• methods that determine the characteristics of a larger population given a sample
  
• complex but well tested and used all the time
  
• ex) opinion polls: presidential election: accurate

2d. GeoCoding / Address Matching

• GeoCoding is the conversion of street addresses into mappable data (data that has geographic coordinates). Also known as address matching.

• Exercise 3: GeoCoding with GPS Visualizer

2e. Remote Sensing: Primary Systematic Data Collection

• Google Earth

• Earth From Space

• False Color Imagery: Earth Shots

• We need an entire course on this at OWU!

Remote Sensing is the indirect collection of environmental data, with mechanical instruments; they serve as data collection means, "remote" from us.

Some remote sensing mechanisms are situated in a particular location

• examples

Data collected from numerous set locations can be compiled and mapped

• example

Other remote sensing mechanisms are mobile

• examples

Remotely sensed data is best for recording physical features in the environment

3e. Compiled Data: Secondary Systematic Data Collection

Data based on secondary sources: published tables, text, or graphic sources

Compiled data is data gathered from such secondary sources

• advantage:

• disadvantage:

Maps often consist of a mixture of data from different sources

• Making Maps p. 46

3. Data Organization

• In order to effectively gather, store, and manipulate geographical data, we need a way to organize it.

• Level of Measurement / Quantification

• Digital Data Organization: two basic types: raster and vector

3a. Level of Measurement / Quantification

When data is collected and organized it must also have an associated level of measurement

Basic levels of measurement

• Making Maps p. 48

• qualitative data: what? and examples

  
  
  

• quantitative data: how much? and examples

More sophisticated measurement levels: NOIR

Nominal: equivalent to qualitative data

• example: land use (commercial, agricultural, residential, industrial)

Ordinal: simplest form of quantitative data: just order

Can quantitatively order from low to high, but with no numeric difference between the classes

• example: feeling of fear in neighborhood: low, medium, high

Interval: order with numeric difference

Can order from low to high, with a numeric difference between the classes, but with no absolute value for the numbers

• example: temperature fahrenheit: 60 deg. is 30 deg. more than 30 deg. but 60 deg. is NOT twice as warm as 30 deg. (the zero is arbitrary)

Ratio: order with numeric difference and absolute zero

Can order from high to low, with a numeric difference between classes, and with an absolute value for the numbers

• example: population by county in Ohio: a county with 10,000 people has twice as many people as a county with 5,000 people.

Why does this matter?

• shapes statistical manipulations of data

• helps select appropriate symbolization methods for mapping
  WWW) Visual Variables

  WWW) Visual Variables: Appropriate Symbolization

  ArcGIS: Hispanic Population Map

3b. Digital Data Organization

Object Oriented Data Model: Vector Data Model

Based on recognized environmental entities: points, lines, areas

Point features: mountain, town, well

• with the coordinates of its location (lat / long)

Line features: river, road

• with a string of coordinates defining its location

Area features: lake, state forest

• with a string of coordinates which closes, defining its location
  

  
  

Location Oriented Data Model: Raster Data Model

Impose a grid over an area and record if some phenomena is or is not in each cell

• example:
  

Why does this matter?

• example:

4. Transforming Data

Geographic data is often transformed and available in derived forms

Raw information - whole numbers are manipulated into some kind of form more suitable for mapping

• examples) averages, ratios, indexes, deviations, regressions

  
  

  

  
  
  

  ArcGIS) Choropleth map of Census Data

  whole numbers: choropleth map: problem

  states with larger population tend to have more Hispanics

  makes more sense to look at the percent Hispanic population

  how many Hispanics per 100 total population?

  derived data

Often need to derive data in order to map it effectively

5. Time & Data

• Making Maps p. 51-53

6. Data Accuracy

Accuracy is complicated!

• Making Maps p. 54-55

7. Digital Data

Geographic data, metadata, and copyright

• Making Maps pp. 56-57

Conclusions

The quality and usefulness of any given map is in large part based on the nature and quality of the geographic data used to make the map

Vital to remember that we are not mapping what is out there in the environment

• we are mapping data that represents what is out there

We conceptualize and categorize the world

• features and their dimensions and their assumed characteristics

Then we collect and organize and quantify and inventory and derive the data

• based on those conceptualizations

And it is this highly manipulated data upon which we base our maps

E-mail: jbkrygier@owu.edu

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