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Fundamentals of GIS > Chapter 12 - Spatial Estimation > Flashcards

Chapter 12 - Spatial Estimation Flashcards

1
Q

What are three common spatial estimation methods?

A
  1. Spatial interpolation; 2. Spatial prediction; 3. Core area
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2
Q

This estimation method estimates values at unmeasured locals using measured values of the same variable

A

Spatial interpolation

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3
Q

This spatial estimation method predicts values at unmeasured locals using measured values of other variables

A

Spatial prediction

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4
Q

This spatial estimation method predicts the chance of occurence of an object or event using probability theory

A

Core area

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5
Q

What are three different methods of spatial interpolation?

A
  1. Creating isoclines; 2. Polygons; 3. Raster
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6
Q

To test spatial interpolation accuracy what is done with some data?

A

Some data is withheld

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7
Q

What are four sampling methods used in spatial interpolation?

A
  1. Systematic; 2. Random; 3. Cluster; 4. Adaptive
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8
Q

This sampling method collects points on a uniform grid

A

Systematic

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9
Q

This sampling method uses randomly distributed points

A

Random

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10
Q

This sampling method uses grouped points

A

Cluster

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11
Q

This sampling method uses more points in variable areas

A

Adaptive

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12
Q

What are four types of spatial interpolation?

A
  1. Nearest neighborhood interpolation; 2. Fixed radius (or local averaging); 3. Inverse distance weighting; 4. Spline
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13
Q

This type of spatial interpolation creates polygons around sample points

A

Nearest neighborhood interpolation

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14
Q

What is another name for the polygons created in nearest neighborhood interpolation?

A

Thiessen polygons

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15
Q

This is conceptually the simplest type of spatial interpolation

A

Nearest neighborhood interpolation

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16
Q

What type of data are poorly represented by nearest neighborhood interpolation?

A

Continuous data

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17
Q

In nearest neighborhood interpolation, points inside polygons have this

A

Same value

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18
Q

Is nearest neighborhood interpolation an exact interpolator?

A

Yes

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19
Q

In this type of spatial interpolation, a circle is placed over each raster cell

A

Fixed radius (or local averaging)

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20
Q

What is done with sample points within a circle in fixed radius/local averaging spatial interpolation?

A

Points are averaged and output to cell

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21
Q

What are cells without points assigned in fixed radius/local averaging spatial interpolation?

A

Zero or null

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22
Q

What happens if a circle radius is too small in fixed radius spatial interpolation?

A

Many nulls created

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23
Q

What happens if a circle radius is too large in fixed radius spatial interpolation?

A

Data is smoothed too much

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24
Q

Is fixed radius/local averaging spatial interpolation an exact interpolator?

A

No

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25
Q

This type of a spatial interpolation uses a set of known sample points with different weights given to each known point

A

Inverse distance weighting

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26
Q

In inverse distance weighting spatial interpolation, weights are inversely proportioned to this

A

Distance

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27
Q

Do distant or near points have less weight in inverse distance weighting spatial interpolation?

A

Distant points

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28
Q

Is inverse distance weighting an exact interpolator?

A

Yes

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29
Q

This spatial interpolation method fits a smooth line or surface through a set of points

A

Spline

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30
Q

Spline spatial interpolation uses these to describe a surface

A

Polynomial equations

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31
Q

This is a flexible ruler used for drawing smooth curves

A

Spline

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32
Q

Is spline spatial interpolation an exact interpolator?

A

Yes

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33
Q

This type of spatial estimation predicts values of variable at missing sites using statistical models

A

Spatial prediction

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34
Q

Spatial prediction statistical models use these two things to predict values

A

Coordinate data and independent variables

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35
Q

Spatial prediction uses these two types of correlation

A

Spatial autocorrelation and cross-correlation

36
Q

What is the First Law of Geography?

A

Everything is related to everything else, but near things are more related than distant things

37
Q

Who is the First Law of Geography attributed to?

A

Waldo Tobler

38
Q

This is correlation of a variable with itself over space

A

Spatial autocorrelation

39
Q

These measure the degree of spatial autocorrelation

A

Different indices

40
Q

This spatial autocorrelation index ranges from -1 to +1

A

Moran’s index

41
Q

A positive spatial autocorrelation has this type of trend when plotted

A

Upward trend

42
Q

A random spatial autocorrelation has this type of trend when plotted

A

No trend

43
Q

What are two types of spatial prediction?

A

Trend surface and kriging

44
Q

This type of spatial prediction fits a 2D surface to a set of sample points using statistical methods

A

Trend surface

45
Q

Trend surface uses this type of polynomial equation

A

Low-order polynomial

46
Q

Is trend surface spatial prediction an exact predictor?

A

No

47
Q

This type of spatial prediction is central to geostatistics

A

Kriging

48
Q

What type of spatial interpolation is kriging similar to?

A

Inverse distance weighting

49
Q

This type of spatial prediction uses neighboring values weighted by distance

A

Kriging

50
Q

Kriging uses this to assign weights

A

Spatial autocorrelation

51
Q

Are weights arbitrary in kriging?

A

No

52
Q

Is kriging an exact predictor?

A

No

53
Q

Data is sorted into these in the kriging method

A

Lag distance bins

54
Q

This is calculated and plotted for each kriging lag distance bin

A

Variance

55
Q

The kriging method produces this graph

A

Variogram

56
Q

What are three components of a variogram?

A

Nugget, sill, range

57
Q

This component of a variogram is where the line intercepts the y-axis

A

Nugget

58
Q

This component of a variogram is just above the asymptote

A

Sill

59
Q

This component of a variogram is the distance between the asymptote and the x-axis

A

Range

60
Q

This model statistically fits through semi-variance points in the kriging method

A

Variogram model

61
Q

What three types of spatial estimation are exact, with predicted values equally observed?

A
  1. Thiessen polygons; 2. Inverse distance weighting; 3. Spline
62
Q

What three types of spatial estimation are not exact, with predicted values that may not be equally observed?

A
  1. Fixed-radius; 2. Trend surface; 3. Kriging
63
Q

This group of spatial estimation methods identifies areas of high density

A

Core area

64
Q

This group of spatial estimation methods is based on a distribution of known observations

A

Core areas

65
Q

Core area spatial estimation methods create these from polygons

A

Regions or territories

66
Q

Core area spatial estimation methods create these from rasters

A

Density fields

67
Q

What are the three types of core area spatial estimation?

A
  1. Mean center; 2. Hulls; 3. Kernel mapping
68
Q

This is the simplest core area method

A

Mean center

69
Q

This core area method averages x-y coordinates for observed values

A

Mean center

70
Q

This is often added to a mean center

A

Mean circle

71
Q

Can a mean circle radius mean different values?

A

Yes

72
Q

This is the simplest core area method for an irregular core area

A

Hulls

73
Q

This core area method creates a polygon enveloping all points

A

Hulls

74
Q

Hulls ignore these

A

Clusters in data points

75
Q

Hulls can be treated as this for points

A

A natural boundary

76
Q

This core area method makes a continuous density surface

A

Kernel mapping

77
Q

Peaks are areas of this in kernel mapping

A

High density

78
Q

This is a density function assigned to each data point in kernel mapping

A

Kernel

79
Q

What type of kernel is the most common?

A

Gaussian kernel

80
Q

This is the width of kernel defined by the user

A

Bandwidth

81
Q

In kernel mapping, this is applied to each sample point

A

Kernel function

82
Q

In kernel mapping, point kernels are summed for this

A

Composite density function

83
Q

In kernel mapping, a narrow bandwidth creates this type of surface

A

Spiky surface

84
Q

In kernel mapping, a broad bandwidth creates this type of surface

A

Broader/flatter surface

85
Q

These are used to determine optimum bandwidth in kernel mapping

A

Formulas

86
Q

Kernel mapping is used to create this

A

2D density surface

87
Q
A

Fundamentals of GIS (13 decks)

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