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GIS > Georeferencing/spatial analysis > Flashcards

Georeferencing/spatial analysis Flashcards

1
Q

what is georeferencing

A

the process of aligning an unreferenced dataset to one that has a spatial reference system

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2
Q

what are examples of data NOT georeferenced

A

satellite and aerial images

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3
Q

what are control points

A

locations that are identifiable and have known coordinates

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4
Q

why are control points important for georeferencing

A

used to TIE unreferenced data to the dataset with known coordinates

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5
Q

what are good control points

A
  • road intersections
  • corners of budlings
  • boulders
  • mountain peaks
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6
Q

what are bad control points

A
  • tops of buildings
  • trees
  • center of field
  • shoelines
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7
Q

what transformation can be done with 1 control point

A

shifts the map, NO change in scale or rotation

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8
Q

what transformation can be done with 3 control point

A

can shift and scale and rotate the map

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9
Q

what transformation can be done with 6 control point

A

can bend the image

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10
Q

what transformation can be done with 10 control point

A

twist the image

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11
Q

what is the shift called with 1 control point

A

zero order shift

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12
Q

what is the shift called with 6 control point

A

second order shift

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13
Q

what is the shift called with 3 control point

A

first order affine

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14
Q

what is the shift called with 10 control point

A

third order shift

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15
Q

what is calculated when a transformation is done

A

residual error

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16
Q

what is a residual error

A

difference between where the georeferenced point is and the specific location

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17
Q

what is the RMSE

A

root mean squared error (square root of the mean value of all squared residual)

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18
Q

do you want a high or low residual error

A

LOW

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19
Q

what is the MINIMUM control points to calculate the RMSE

A

FOUR

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20
Q

what is the amount of residual error based on

A

the quality of the control points

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21
Q

what is high RMSE caused by

A

poor control points

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22
Q

what are the three residuals

A
  1. forward
  2. inverse
  3. forward-inverse
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23
Q

forward residual

A

shows the error in the SAME units as the data frame

24
Q

inverse residual

A

shows you the error in pixel units

25
Q

forward inverse residual

A

measure of overall accuracy measured by pixels in the image

26
Q

what is resampling during a transformation

A

each cell is given a new value based on its location

27
Q

three types of resampling

A
  1. nearest neighbour
  2. bilinear interpolation
  3. cubic convolution
28
Q

what is nearest neighbour resampling

A

does not alter the original values but adopts the value of the nearest pixel

29
Q

what are issues with nearest neighbour resampling

A
  1. may result in blocky images
  2. may duplicate or lose data
30
Q

what kind of data is nearest neighbour resampling good for

A

discrete data (zoning, roads)

31
Q

what is bilinear interpolation

A

weighted average of four pixels in the original grid nearest the new pixel

32
Q

what is bilinear interpolation not suitable for

A

discrete data

33
Q

what is bilinear interpolation used for

A

continuous data

34
Q

how does cubic convolution differ from bilinear interpolation

A

calculates a distanced weighed of 16 pixels NOT 4 pixels from the original grid that surrounds the new output

35
Q

what is cubic convolution good for

A

continuous data

36
Q

what is cubic convolution NOT good for

A

discrete data

37
Q

what types of resampling produce SHARPER images

A

bilinear interpolation
cubic convolution

38
Q

what type of resampling is generally avoided for GIS

A

nearest neighbour

39
Q

what is spatial analysis

A

how features are spatially related to one another

40
Q

what are some uses of spatial analysis

A
  1. cause and effect
  2. suitability assessment
  3. predict outcomes
41
Q

what are four types of spatial analysis

A
  1. constraints
  2. proximity
  3. networks
  4. clustering
42
Q

what is constraints spatial analysis

A

selections and queries to identify features that meet criteria

43
Q

what is proximity spatial analysis

A

how close one feature is to another feature

44
Q

what is networks spatial analysis

A
  1. what is the shortest route to a location
45
Q

what is clustering spatial analysis

A

are nearby features similar to one another

46
Q

what is an example of proximity

A

Thiessen polygons

47
Q

Thiessen polygons

A

a set of polygons that define areas of influence around points in a space

48
Q

what are buffers

A

spatial proximity built around a point, line or polygon

49
Q

what kind of data do buffers use and what is the issue

A

Euclidean distance (straight line that doesn’t account for restrictions in topography; rivers)

50
Q

how are networks measured

A

Manhattan distance

51
Q

what is the manhattan distance

A

distance between two points on a grid

52
Q

what is near

A

measures the distance between input features and near features

53
Q

what does kernel density calculate

A

the density of point features around each output raster cell

54
Q

what is kernel density an example of

A

clustering

55
Q

what kind of features can be used in kernel density

A

point and line features

56
Q

what are some uses for kernel density

A
  1. house density
  2. crime reports
  3. wildlife habitats

GIS (7 decks)

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