Gis Midterm

Front 1

GISystems

Back 1

has an emphasis on technology and tools (software)

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GIScience

Back 2

fundamental isses raised by the use of GIS and related technologies (how info is represented)

Front 3

4 aspects of GIScience

Back 3

1. spatial analysis
2. accuracy
3. map projections
4. scientific visualization

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(geographic) information system

Back 4

(within a specific location) helps manage what is known by making it easier to store, access, retrieve, manipulate, and apply knowledge to a process of solving a problem

Front 5

5 categories of 'What We Know'

Back 5

1. Data
2. Information
3. Evidence
4. Knowledge
5. Wisdom

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Geographic vs. Spatial

Back 6

geographic refers to the Earth's surface, while spatial refers to any space (medical imaging, DNA sequencing)

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Geographic Problem

Back 7

a problem that involves any aspect of location, either in the information used to solve it or the solutions themselves

Front 8

Pattern vs. Process

Back 8

knowledge about how the world works is more valuable than how the world looks because the knowledge can be used for prediction

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Overlay Examples

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1. Battle of Yorktown
2. Irish Railroad
3. Cholera epidemic

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Remote Sensing

Back 10

measuring or observing something indirectly, without coming into contact

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Birds-eye view is used for... (2)

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1. General mapping (property lines)
2. War reconnaissance efforts

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photogrammetry

Back 12

makes measures from photographs by using tone, size, shape, texture, patterns, and shadow

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Father of GIS

Back 13

Roger Tomlinson

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Topology

Back 14

EXPLICIT information on spatial relationships (invariance of shapes)

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Peuquet's Levels of Data Abstraction (4)

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1. Reality
2. Data Model
3. Data Structure
4. File Structure

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2 fundamental ways of represnting geographical space

Back 16

raster and vector

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Raster

Back 17

(continuous fields) divides space into uniformly spaced cells, doesn't provide precise locational info

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resolution

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(relates to raster) amount of Earths surface represented by a single grid cell

(larger grid cells contain less land area and has a finer resolution)

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Vector

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(discrete objects) represented by exact X and Y coordinates, and geographic space is continuous rather than quantized

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Attributes

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consist of any NONSPATIAL information that describes the information

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Nominal

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(classification) "named" qualitative data; no comparisons can be made (apples and oranges)

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Ordinal

Back 22

ordered qualitative data- ranking is specific to to what you want to know and cannot be used for anything else

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Interval

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quantitative data; ables to compare and express as the difference between things

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Ratio

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can compare and express the difference of things (like interval) PLUS a natural origin of zero

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Representation

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focuses on conceptual and scientific issues

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Data Model

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set of constructs for representing objects and processes in the digital environment; also impacts what kind of analysis can be done

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theme/layer

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collection of entities of the same dimensionality

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Spaghetti Models

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NO topology- lines aren't connected and have no intelligence

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Topology uses:

Back 29

- data validation
- spatial analysis

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temporal autocorrelation

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relationship between consecutive events in TIME (for prediction and explanation) (scale-dependent)

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spatial autocorrelation

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relationship between things across SPACE (may be positive or negative) (scale-dependent)

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Tobler's First Law of Geography

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things closer together are more related than those father apart

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spatial heterogeneity

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tendency of geographic places to be different from one another

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map scale

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representative fraction given on a map

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Types of Samples

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1. Random
2. Systematic
3. Stratified
4. Cluster
5. Transect

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Uncertainty

Back 36

umbrella term to describe the problems associated with the necessarily imperfect representation of the real world in GIS

AKA the difference between GIS representation and the real world

error, inaccuracy, ambiguity, vagueness

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fuzzy approaches

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assign probability of membership and capture the uncertainty of the attribute assignment

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vagueness

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uncertainty in boundaries and attributes

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ambiguity

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direct and indirect indicators ('across' and 'over')

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The Confusion Matrix

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compares the recorded classes (observations) with classes obtained by some more accurate process, or from a more accurate source (the reference)

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accuracy

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refers to the amount of distortion from the true value

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precision

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refers to the variation between repeated measurements and the amount of detail in the reporting of a measurement

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RMSE

Back 43

the square root of the average squared error

primary measure of accuracy in maps and GIS databases

often follows a bell curve distribution

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bell curve

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Gaussian or normal distribution (68% of the area under the curve)

Front 45

Ecological Fallacy

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inappropriate inference from aggregate data about the characteristics of individuals

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MAUP

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combined effects of scale and aggregation

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scale effect (within MAUP)

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tendency within a system of modifiable areal units for different statistical results to be obtained from the same set of data when the info is grouped at diff levels of spatial resolution (census tracts, cities, region)

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aggregation or zoning effect

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the variability in statistical results obtained within a set of modifiable units as a function of the various ways these results can be grouped at a given scale