Geography 222 The Power of Maps

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Geog 222 Lecture Outline: Geographic Data and Data Sources
Update: 2/24/14

Introduction

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

The procedures followed will strongly influence the resulting map:


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



2. Creating & Geting Data

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

Limited in its usefulness for making cartographic maps in most cases

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



Systematic data collection methods



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




Handout) Delaware Topo


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



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


Origins and Development of GPS:


How GPS works


Calculating locations on Earth with GPS

GPS Industry Now: +$50 billion by 2010.

GPS Sources:



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



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



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

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


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



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

example) measure of toxic chemical in the ground


Accuracy issues


Sampling is also used for discrete environmental features



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

Most important aspect of sampling:




2d. GeoCoding / Address Matching



2e. Remote Sensing: Primary Systematic Data Collection


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



Data collected from numerous set locations can be compiled and mapped



Other remote sensing mechanisms are mobile



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

Maps often consist of a mixture of data from different sources





3. Data Organization


3a. Level of Measurement / Quantification

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

Basic levels of measurement



More sophisticated measurement levels: NOIR

Nominal: equivalent to qualitative data



Ordinal: simplest form of quantitative data: just order

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



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



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



Why does this matter?



3b. Digital Data Organization

Object Oriented Data Model: Vector Data Model

Based on recognized environmental entities: points, lines, areas



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



Why does this matter?



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


Often need to derive data in order to map it effectively





5. Time & Data





6. Data Accuracy

Accuracy is complicated!





7. Digital Data

Geographic data, metadata, and copyright





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 conceptualize and categorize the world

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

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




E-mail: jbkrygier@owu.edu

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