Predictive Surfaces Flashcards

1
Q

what are predictive surfaces

A

measurements at a set of locations to predict values in locations that WERE NOT MEASURED

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2
Q

are predictive surfaces used for discrete or continuous data

A

continuous data

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3
Q

what can predictive surfaces be used to do

A

interpolate and extrapolate

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4
Q

interpolate vs extrapolate

A

interpolate
- predicting values between known points

extrapolate
- predicting values outside of the known points

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5
Q

exact vs approximate interpolation

A

exact
- creates a surface that passes through ALL known points

approximate
- creates a surface that MAY vary from known values

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6
Q

local vs global methods

A

local
- uses spatially defined data (uses data around specific points)

global
- uses al data in the study area

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7
Q

what are potential predictive surfaces

A

Inverse Distance Weighting (IDW)
Natural Neighbour
Spline
Trend

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8
Q

is inverse distance weighting local or global interpolation

A

local

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9
Q

is inverse distance weighting exact or approximate interpolation

A

exact

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10
Q

benefits and limitations of is inverse distance

A

benefits
- known influence of proximity
- uniform distribution of points
- can control the smoothness

limitations
- doesn’t handle sharp changes in data
- creates bullseye pattern around points
- does NOT extrapolate

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11
Q

what does IDW predict

A

values using a weighted combination of sample points

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12
Q

what does the power control in IDW

A

the significance of points based on their distance

(increased power = more emphasis on nearest points)

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13
Q

contrast fixed vs variable search radius in IDW

A

fixed
- searched radius will remain constant unless min number of points not met

variable
- search radius will change to include a minimum number of sample points

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14
Q

what is natural neighbor

A

finds the nearest input samples to grid cells and weights them based on proportionate areas overlapping grid cell area

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15
Q

is natural neighbors local or global interpolation

A

local

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16
Q

is natural neighbors exact or assumptions interpolation

17
Q

benefits and limits of natural neighbor

A

benefits
- ideal for irregular spaced data
- resistance to cluster bias or overrepresentation

limitations
- does not represent peaks, ridges or valleys
- does NOT extrapolate

18
Q

what is spline

A

users can control the number of points used to calculate each interpolated cell value

19
Q

does spline with more points create a smooth or rough surface

20
Q

regularized vs tension spline

A

regular
- allows users to adjust the weight parameter to SMOOTH the surface

tension
- allows users to adjust the weight parameter to STIFFEN the surface

21
Q

is tension spline exact or approximate interpolation

A

becomes approximate

22
Q

what is spline

A

minimizes the curvature to create a smooth surface

23
Q

is spline local or global interpolation

24
Q

is spline exact or approximate interpolation

A

exact but CAN extrapolate

25
benefits and limitations of spline
benefits - estimates beyond max and min values - captures subtle variations - best for gentle varying surfaces - CAN extrapolate limitations - can miss sharp changes in elevation - can create unrealistic values - not ideal for dense points with extreme differences
26
what is trend
global polynomial interpolation method used to capture coarse scale patterns
27
is trend global or approximate interpolation
global
28
is trend exact or approximate interpolation
approximate
29
what is trend used for
bending the surfaces
30
contrast trend with 0 to 12 polynomials
0 = less complex 12 = most complex
31
contrast first order, second order and third order polynomials
first - linear surface second order - one bend surface tthird order - two bends
32
what does trend minimize
residual error at each point
33
benefits vs limitations of trend
benefits - large scale pattern recognition - extrapolates data limitations - oversimplifies data - miss local variability - not accurate for small scale analysis