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Nominal Data

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34 Terms

1

Nominal Data

Data that can be labeled or categorized but there is no inherent order between categories.

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2

Ordinal Data

Data that can be categorized and ranked, where you can’t measure the interval between rankings.

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3

Interval Data

Data that can be categorized or ranked, and the degree of difference between intervals can be measured, but there is no true zero.

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4

Ratio Data

Data that can be categorized or ranked, and there is a true zero.

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5

Entity

A real-world object or phenomenon.

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6

Feature

A single record or row in a table that represents an entity.

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7

Attribute

A characteristic or measurement about a feature.

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8

Vector Pros

Good for discrete data, can represent complex shapes, more precise, efficient for data storage.

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9

Raster Cons

Lose precision when the cell size is large, can take up lots of room on a computer.

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10

Shapefile Required Files

.shp, .shx, .dbf.

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11

.shp File

The main file that stores the geometry.

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12

.shx File

The index file that stores the index of the feature geometry.

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13

.dbf File

The database that stores the attribute information of features.

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14

Measures of Central Tendency

Mean, median, and mode.

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15

Euclidean Distance

Measures distance on a flat map surface.

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16

Geodesic Distance

Accounts for the shape of the earth, distances are calculated on the curved surface.

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17

Buffering

A specified distance around a point, line, or polygon.

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18

Union

All features and attributes are written to the output feature class.

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19

Intersection

Portions of features that overlap in all layers will be written to the output feature class.

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20

Clipping

Uses one vector dataset to cut out a piece of another vector dataset.

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21

Pattern Analysis

Using techniques to assess the proximity and density of features in space.

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22

Spatial Interpolation

Analysis where we use points with known values to estimate values at unknown points.

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23

Choropleth Maps

Polygon-based maps that divide geographic areas into colours or patterns depending on one of the data attributes.

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24

MAUP

A problem in spatial analysis where the results depend on the shape or size of zones used for analysis.

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25

Nulls vs Zeros

Zero may indicate an absence of something, while null means data wasn’t collected or is missing.

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26

Placeholder Number

An obvious number that stands out in your dataset when a number is required.

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27

How do you create centroids from polygons?

Takes a polygon layer, finds the centre, and creates a new point feature

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28

When would it be useful to make centroids from polygons?

Running analyses that need points as the shape, if you are interested in spatial relationships from the centre of polygons, or for visual displays

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29

How does the find closest analysis work?

  • Takes 2 input layers, the one you are moving away from and the one you are moving towards

  • Can get routes in straight lines or following roadways

    • Uses ESRI’s datasets for roadways

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30

What are travel areas?

  • Input is a point layer, output is a polygon layer

  • Creates a layer that shows the area that can be reached within a certain time or distance of either walking or driving

  • Combining multiple travel areas can give you an indication of what areas are being affected/serviced by the feature

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31

What is summarize withins?

  • Input to summarize can be points, lines, or polygons

  • Summary areas can be another input polygon layer, or a grid or a “sketch” on the map

  • Calculates statistics of the number of features within another polygon layer

    • count/number of features

    • mean, median, mode, standard deviation

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32

What is calculate density?

  • Input is points or lines, input is a polygon feature

  • Many different ways to visualize

  • Shows the density or spread of features

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33

How do you generalize data?

Group individual results by a larger area, exact locations aren’t shared but a polygon with aggregated data is, need to aggregate or group to a meaningful size

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34

What is geographic masking?

Publicly providing the exact location can cause harms, often knowing the exact location isn’t needed for the purpose of publication/data sharing, geographic masking allows us to shift the locations in a GIS to protect exact locations

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