Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

GIS > Chap 2 > Flashcards

Chap 2 Flashcards

1
Q

CMYK

A

a method of specifying color using mixtures of cyan, magenta, yellow, and black; primarily used in printing and publishing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

RGB

A

a method of specifying color using mixtures of red, green, and blue on scales of 0 to 255 each

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

HSV

A

a method of specifying color based on hue saturation, or value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Hue

A

the shade of a color, such as red, green, or blue, measured on a 0 to 360 scale

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Saturation

A

the intensity of a color measured on a scale of 0 to 100

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Value

A

the darkness or lightness of a color on a scale of 0 to 100

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

alpha

A

a color parameter that defines the opacity or transparency of a color

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

divergent color set

A

a set of colors with a neutral middle value that grades to increasingly saturated colors of different hues above and below

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

convention

A

a symbol for mapping that is commonly chosen and understood to have particular meaning

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

connotation

A

a typical emotional reaction elicited by certain colors or symbols

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

nominal data

A

values that name or identify an objet, such as a street name

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

categorical data

A

data that place objects into unranked groups; examples are land use and geology data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

unique values map

A

a map in which each attribute value is assigned its own symbol

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

ordinal data

A

data values that indicate a rank or ordering system

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

quantitative data

A

data represent phenomena that fall along a regularly spaced measurement scale, such as distance or rainfall

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

ratio data

A

data having a regular scale of measurement and a natural zero point, such as precipitation or population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

interval data

A

values that follow a regular scale but have no natural zero point, such as degrees Celsius or pH

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

graduated symbol map

A

a map that divides numeric data from a line or point feature class into classes based on value and displays the classes with different size or thickness of symbols

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

proportional symbol map

A

a map that displays attribute values with marker or line symbols that are proportional in size relative to the value of the feature

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

graduated color map

A

a map that divides numeric data from a polygon feature class into classes based on value and displays the classes with different colors

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

choropleth map

A

a map in which each feature, such as a state, is colored according to the values in a data field

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

aggregate

A

to combine measurements from one set of spatial units to a larger unit using regular or hierarchical scheme, such as adding county populations to determine the state populations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

modifiable areal unit problem (MAUP)

A

statistical and visual issues caused by aggregating measured data using arbitrary areal units such as political boundaries

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

normalize

A

to divide the values of an attribute field by the total of the field or by the values in another field

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

dot density map

A

a map representing attribute values by a proportional number of randomly placed dots

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

chart map

A

a map showing several different attributes in chart form, with one chart for each feature

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

bivariate choropleth map

A

a graduated colors map that compares the spatial patterns of two different numeric attributes by mixing two ranges of colors together

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

thematic raster

A

a raster that contains categorical or nominal data values, such as land use codes or soil types

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

continuous

A

data that take on a variety of values and that change rapidly across a data set, such as elevation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

discrete

A

described data that represent distinct spatial objects such as wells, roads, or counties

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

classified

A

a raster display method that divides values into two or more groups based on their numeric values

32
Q

stretched

A

a display method that spreads the data values over the entire range of symbols available; see also stretch

33
Q

slice

A

to divide the values in a raster into a specified number of even classes

34
Q

Tobler’s law

A

measurements taken at locations close together are more likely to be similar than measures taken at locations further apart

35
Q

image

A

a raster data layer, usually referring to a taster that displays brightness values, as in a photograph

36
Q

RGB composite

A

an image displayed by assigning one band of brightness information to each red, green, and blue color gun in a display monitor

37
Q

histogram

A

a graph showing the number of values from a data set that occur in evenly spaced ranges known as bins

38
Q

colormap

A

a set of defined colors matched to specific image pixel values, which determines how the image will appear

39
Q

classification

A

assigning features to two or more groups based on numeric values in an attribute field

40
Q

Jenks method

A

a way to classify numeric data into ranges defined by naturally occurring gaps in the data histogram

41
Q

equal interval

A

a classification method in which the user specifies a number of classes that have equal size ranges

42
Q

defined interval

A

a classification method in which the user specifies a size range for all the classes

43
Q

quantile

A

a classification method that divides the data into the specified number of quantiles so that each class has the same number of features

44
Q

geometric interval

A

a classification method that bases the class intervals on a geometric series in which each class is multiplied by a constant coefficient to produce the next higher class

45
Q

standard deviation

A

a classification scheme in which the class breaks are based on the standard deviation values of the data being mapped

46
Q

layer

A

a reference to a feature class and its associated properties

47
Q

source data (2)

A

1) a spatial data file that provides the features for a map layer
2) the original information used to develop a spatial data set

48
Q

layer properties

A

settings that control how a data set is to be displayed or viewed

49
Q

layer file

A

a file that stores a pointer to spatial data along with information on how to display it

50
Q

style

A

a collection of map symbols and colors that are stored together and used together

51
Q

How does a map layer differ from its source data?

a-It stores only the data location and its display properties, not the actual features.
b-It refers only to spatial features and not to the attribute values.
c-It refers only to data stored in the home geodatabase, not data outside the project.
d-If refers only to local data, not data accessed through an Internet portal.

A

a- it stores only the data location and its display properties, not the actual features

52
Q

In a(n) _____________ classification, the user defines the number of classes and the software determines a single range width for all classes.

a- quantile
b- defined interval
c- equal interval
d- standard deviation
e- Jenks

A

c- equal interval

53
Q

The ____________ classification is especially useful for strongly skewed map values.

a- defined interval
b- equal interval
c- standard deviation
d- geometric interval
e- quantile

A

d- geometric interval

54
Q

To create a map showing median rent with evenly spaced classes $100 apart, you would use the _____________ classification.

a- standard deviation
b- equal interval
c- Jenks Natural Breaks
d- quantile
e- defined interval

A

e- defined interval

55
Q

A map based on categorical data is by its nature unaffected by MAUP issues.

a- True, because categorical data can’t be normalized.
b- True, because aggregation only affects quantities data.
c- False, because categories can still be affected by the visual MAUP issue.
d- False, because categories are portrayed by hues instead of values.

A

c- False, because categories can still be affected by the visual MAUP issue

56
Q

MAUP issues are usually addressed in a map by

a-normalizing the feature value by the feature area
b- using a divergent rather than a monochromatic color scheme
c- changing the scale of the map
d- changing the classification method

A

a- normalizing the feature value by the feature area

57
Q

A soil classification (sandy, loamy, silty, etc.) would be considered to be ______________ data.

a- ordinal
b- categorical
c- interval
d- ratio

A

b- categorical

58
Q

A map of land use in Boston could be best portrayed using the ____________ map type.

a- dot density
b- graduated color
c- graduated symbol
d- unique values
e- chart

A

d- unique values

59
Q

Which one of these map types should NOT be used for a map of county populations?

a- graduated color
b- graduated symbol
c- unique values
d- chart
e- proportional symbol

A

c- unique values

60
Q

Normalizing data in a graduated color map means that you

a- divide each mapped value by the total of all values in the field
b- divide each mapped value by the value in a different field
c- either of these responses
d- neither of these responses

A

c- either of these responses

61
Q

If the following information is being displayed on a map, for which one is MAUP most likely to be an issue?

a- earthquake magnitudes
b- county alcohol sales
c- river flow volumes
d-soil type

A

b- county alcohol sales

62
Q

The number of bushels of wheat per county would be considered to be _____________ data.

a- categorical
b- ratio
c- interval
d- ordinal

A

b- ratio

63
Q

definition of the term “RGB composite”.

A

method used to display three raster bands simultaneously

64
Q

definition of the term “aggregation”.

A

to sum measurements within pre-defined boundaries

65
Q

definition of the term “stretched”.

A

method to enhance image display across the entire range of available symbols

66
Q

definition of the term “interval data”.

A

data values measured on a regular scale but without a natural zero

67
Q

definition of the term “geometric interval”.

A

a classification that multiplies each class range by a constant coefficient

68
Q

definition of the term “chart map”.

A

a map that shows a small graph from several fields instead of a symbol from one field

69
Q

definition of the term “dot density” map.

A

a map that places random points in polygons using a given proportion

70
Q

Tobler’s Law states that _________.

a- unclassed maps are more objective than classed maps
b- hue should be used to represent categories; saturation/value for quantities
c- arbitrary aggregation schemes may result in MAUP issues
d- nearby measurements tend to be more similar than values at greater distances
e- none of these responses describes Tobler’s Law

A

d- nearby measurements tend to be more similar than values at greater distances

71
Q

Why is it usually okay to use more classes for continuous raster data than for polygon data?

a- because the raster values often have an underlying structure or trend
b- because rasters have more pixels than maps have polygons
c- because the raster classification method is more sophisticated
d- because rasters do not have boundaries

A

a- because the raster values often have an underlying structure or trend

72
Q

Which one of the following would be considered a thematic raster?

a- a screenshot of a radar precipitation map
b- a raster of geologic rock units
c- a raster image from an aerial photograph
d- a raster image from a satellite

A

b- a raster of geologic rock units

73
Q

Which one of the following map variables would be best represented by changes in symbol size?

a- winning political party of counties
b- differences in land cover class
c- status of a state-managed highway versus a county-managed highway
d-number of lanes of roads

A

d- number of lanes of roads

74
Q

Which one of the following map variables would be best represented by changes in symbol size?

a- magnitudes of earthquakes
b- types of volcanos
c- classification of well categories
d- political party winners of congressional districts

A

a- magnitudes of earthquakes

75
Q

The saturation vector in the HSV model can be described as

a- which color pigment is added to a can of white base paint.
b- how much color pigment is added to a can of white base paint.
c-how much black pigment is added to a can of base paint.
d-how full a can of base paint is.

A

b- how much color pigment is added to a can of white base paint

GIS (5 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2025 Bold Learning Solutions. Terms and Conditions