Brainscape's Knowledge GenomeTM


Top Flashcards (Certified)
All Flashcards

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

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

A

Spatial interpolation

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

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

A

Spatial prediction

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

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

A

Core area

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

What are three different methods of spatial interpolation?

A
  1. Creating isoclines; 2. Polygons; 3. Raster
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

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

A

Some data is withheld

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

What are four sampling methods used in spatial interpolation?

A
  1. Systematic; 2. Random; 3. Cluster; 4. Adaptive
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

This sampling method collects points on a uniform grid

A

Systematic

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

This sampling method uses randomly distributed points

A

Random

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

This sampling method uses grouped points

A

Cluster

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

This sampling method uses more points in variable areas

A

Adaptive

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

This type of spatial interpolation creates polygons around sample points

A

Nearest neighborhood interpolation

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

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

A

Thiessen polygons

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

This is conceptually the simplest type of spatial interpolation

A

Nearest neighborhood interpolation

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

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

A

Continuous data

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

In nearest neighborhood interpolation, points inside polygons have this

A

Same value

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

Is nearest neighborhood interpolation an exact interpolator?

A

Yes

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

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

A

Fixed radius (or local averaging)

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

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

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

A

Zero or null

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

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

A

Many nulls created

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

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

A

Data is smoothed too much

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

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

A

No

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
This type of a spatial interpolation uses a set of known sample points with different weights given to each known point
Inverse distance weighting
26
In inverse distance weighting spatial interpolation, weights are inversely proportioned to this
Distance
27
Do distant or near points have less weight in inverse distance weighting spatial interpolation?
Distant points
28
Is inverse distance weighting an exact interpolator?
Yes
29
This spatial interpolation method fits a smooth line or surface through a set of points
Spline
30
Spline spatial interpolation uses these to describe a surface
Polynomial equations
31
This is a flexible ruler used for drawing smooth curves
Spline
32
Is spline spatial interpolation an exact interpolator?
Yes
33
This type of spatial estimation predicts values of variable at missing sites using statistical models
Spatial prediction
34
Spatial prediction statistical models use these two things to predict values
Coordinate data and independent variables
35
Spatial prediction uses these two types of correlation
Spatial autocorrelation and cross-correlation
36
What is the First Law of Geography?
Everything is related to everything else, but near things are more related than distant things
37
Who is the First Law of Geography attributed to?
Waldo Tobler
38
This is correlation of a variable with itself over space
Spatial autocorrelation
39
These measure the degree of spatial autocorrelation
Different indices
40
This spatial autocorrelation index ranges from -1 to +1
Moran's index
41
A positive spatial autocorrelation has this type of trend when plotted
Upward trend
42
A random spatial autocorrelation has this type of trend when plotted
No trend
43
What are two types of spatial prediction?
Trend surface and kriging
44
This type of spatial prediction fits a 2D surface to a set of sample points using statistical methods
Trend surface
45
Trend surface uses this type of polynomial equation
Low-order polynomial
46
Is trend surface spatial prediction an exact predictor?
No
47
This type of spatial prediction is central to geostatistics
Kriging
48
What type of spatial interpolation is kriging similar to?
Inverse distance weighting
49
This type of spatial prediction uses neighboring values weighted by distance
Kriging
50
Kriging uses this to assign weights
Spatial autocorrelation
51
Are weights arbitrary in kriging?
No
52
Is kriging an exact predictor?
No
53
Data is sorted into these in the kriging method
Lag distance bins
54
This is calculated and plotted for each kriging lag distance bin
Variance
55
The kriging method produces this graph
Variogram
56
What are three components of a variogram?
Nugget, sill, range
57
This component of a variogram is where the line intercepts the y-axis
Nugget
58
This component of a variogram is just above the asymptote
Sill
59
This component of a variogram is the distance between the asymptote and the x-axis
Range
60
This model statistically fits through semi-variance points in the kriging method
Variogram model
61
What three types of spatial estimation are exact, with predicted values equally observed?
1. Thiessen polygons; 2. Inverse distance weighting; 3. Spline
62
What three types of spatial estimation are not exact, with predicted values that may not be equally observed?
1. Fixed-radius; 2. Trend surface; 3. Kriging
63
This group of spatial estimation methods identifies areas of high density
Core area
64
This group of spatial estimation methods is based on a distribution of known observations
Core areas
65
Core area spatial estimation methods create these from polygons
Regions or territories
66
Core area spatial estimation methods create these from rasters
Density fields
67
What are the three types of core area spatial estimation?
1. Mean center; 2. Hulls; 3. Kernel mapping
68
This is the simplest core area method
Mean center
69
This core area method averages x-y coordinates for observed values
Mean center
70
This is often added to a mean center
Mean circle
71
Can a mean circle radius mean different values?
Yes
72
This is the simplest core area method for an irregular core area
Hulls
73
This core area method creates a polygon enveloping all points
Hulls
74
Hulls ignore these
Clusters in data points
75
Hulls can be treated as this for points
A natural boundary
76
This core area method makes a continuous density surface
Kernel mapping
77
Peaks are areas of this in kernel mapping
High density
78
This is a density function assigned to each data point in kernel mapping
Kernel
79
What type of kernel is the most common?
Gaussian kernel
80
This is the width of kernel defined by the user
Bandwidth
81
In kernel mapping, this is applied to each sample point
Kernel function
82
In kernel mapping, point kernels are summed for this
Composite density function
83
In kernel mapping, a narrow bandwidth creates this type of surface
Spiky surface
84
In kernel mapping, a broad bandwidth creates this type of surface
Broader/flatter surface
85
These are used to determine optimum bandwidth in kernel mapping
Formulas
86
Kernel mapping is used to create this
2D density surface
87

Fundamentals of GIS (13 decks)

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