Georeferencing/spatial analysis Flashcards by Sophia Easter

what is georeferencing

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

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what are examples of data NOT georeferenced

satellite and aerial images

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what are control points

locations that are identifiable and have known coordinates

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why are control points important for georeferencing

used to TIE unreferenced data to the dataset with known coordinates

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what are good control points

road intersections
corners of budlings
boulders
mountain peaks

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what are bad control points

tops of buildings
trees
center of field
shoelines

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what transformation can be done with 1 control point

shifts the map, NO change in scale or rotation

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what transformation can be done with 3 control point

can shift and scale and rotate the map

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what transformation can be done with 6 control point

can bend the image

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what transformation can be done with 10 control point

twist the image

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what is the shift called with 1 control point

zero order shift

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what is the shift called with 6 control point

second order shift

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what is the shift called with 3 control point

first order affine

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what is the shift called with 10 control point

third order shift

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what is calculated when a transformation is done

residual error

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what is a residual error

difference between where the georeferenced point is and the specific location

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what is the RMSE

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

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do you want a high or low residual error

LOW

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what is the MINIMUM control points to calculate the RMSE

FOUR

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what is the amount of residual error based on

the quality of the control points

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what is high RMSE caused by

poor control points

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what are the three residuals

forward
inverse
forward-inverse

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forward residual

shows the error in the SAME units as the data frame

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inverse residual

shows you the error in pixel units

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forward inverse residual

measure of overall accuracy measured by pixels in the image

what is resampling during a transformation

each cell is given a new value based on its location

three types of resampling

1. nearest neighbour 2. bilinear interpolation 3. cubic convolution

what is nearest neighbour resampling

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

what are issues with nearest neighbour resampling

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

what kind of data is nearest neighbour resampling good for

discrete data (zoning, roads)

what is bilinear interpolation

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

what is bilinear interpolation not suitable for

discrete data

what is bilinear interpolation used for

continuous data

how does cubic convolution differ from bilinear interpolation

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

what is cubic convolution good for

continuous data

what is cubic convolution NOT good for

discrete data

what types of resampling produce SHARPER images

bilinear interpolation cubic convolution

what type of resampling is generally avoided for GIS

nearest neighbour

what is spatial analysis

how features are spatially related to one another

what are some uses of spatial analysis

1. cause and effect 2. suitability assessment 3. predict outcomes

what are four types of spatial analysis

1. constraints 2. proximity 3. networks 4. clustering

what is constraints spatial analysis

selections and queries to identify features that meet criteria

what is proximity spatial analysis

how close one feature is to another feature

what is networks spatial analysis

1. what is the shortest route to a location

what is clustering spatial analysis

are nearby features similar to one another

what is an example of proximity

Thiessen polygons

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

what are buffers

spatial proximity built around a point, line or polygon

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

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

how are networks measured

Manhattan distance

what is the manhattan distance

distance between two points on a grid

what is near

measures the distance between input features and near features

what does kernel density calculate

the density of point features around each output raster cell

what is kernel density an example of

clustering

what kind of features can be used in kernel density

point and line features

what are some uses for kernel density

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

can coordinates have a z coordinate

yes

what is the z coordinate

the vertical datum

what does the vertical datum measure

baseline for measuring elevation

what is elevation represented by ion topographic maps

contour lines

what is photogrammetry

stereo pairs used to calculate elevation

what is LIDAR

emits a laser pulse to the earth's surface and measures the return

what is the accuracy of LIDAR

ranges from 3 to 30 cm

what is digital elevation model

representation of the surface of the earth

does DEM include features on earth's surface

NO - bare earth model

what is TIN

vector based approach to creating digital elevation models

contrast TIN and DEM

TIN is vector based models and DEM is raster based models

how are points represented in TIN

connected by lines to create a network of non overlapping triangles

is this DEM or TIN

DEM

is this DEM or TIN

TIN

what does TIN stand for

triangulated irregular network

advantages of DEM and TIN

DEM - accepts data directly from matrix cell - less complex and faster to process TIN - randomly sample data - displays linear features - accepts point features

disadvantages of DEM and TIN

DEM - must be resampled if irregular data - may miss complex topography - includes redundant data in low relief areas TIN - data is intense and takes longer to process - each vertex stores x, y, z data

what is DSM

measurements of ground elevation height as well as objects on the ground

How des DSM differ from DEM

DSM measures earth with the features while DEM measures bare earth elevation

what are some applications of spatial analysis

1. slope 2. aspect 3. hill shade 4. contour lines 5. viewshed 6. surface drape

is it DEM or DSM that analyzed watersheds

DEM